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  <title>AI &amp; Data Democratization Podcast</title>

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  <itunes:author>Alexandra Ebert </itunes:author>
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  <description><![CDATA[<p>A podcast about data innovation, regulations and data privacy. We will bring you exciting and inspiring stories from the frontiers of data and privacy management. Think AI, fairness, privacy-compliance, synthetic data, data literacy, and more. Hosted by Alexandra Ebert, MOSTLY AI's Chief AI &amp; Data Democratization Officer.<br><br>If you have any suggestions or questions, send a voice recording or DM to Alexandra on LinkedIn.</p>]]></description>
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    <itunes:title>53. “The EU Policy Machine Is Broken. Brussels Lacks Courage!”—Kai Zenner on Europe’s Digital Future and the Steps We Must Take in 2026 to Reclaim It</itunes:title>
    <title>53. “The EU Policy Machine Is Broken. Brussels Lacks Courage!”—Kai Zenner on Europe’s Digital Future and the Steps We Must Take in 2026 to Reclaim It</title>
    <itunes:summary><![CDATA[In the first episode of season 6, Alexandra Ebert sits down with Kai Zenner, Head of Office and Digital Policy Adviser to MEP Axel Voss at the European Parliament, for a deep dive into Europe’s digital future. They outline what Brussels is still not getting right on AI and debate what is urgently needed in 2026: a long-term AI, data &amp; digital strategy for Europe, the courage for bold political leadership, and taking action where it matters most.    KEY TOPICS: 00:00 — Intro07:08 — Da...]]></itunes:summary>
    <description><![CDATA[<p>In the first episode of season 6, <b>Alexandra Ebert </b>sits down with <b>Kai Zenner</b>, Head of Office and Digital Policy Adviser to MEP Axel Voss at the <b>European Parliament</b>, for a deep dive into Europe’s digital future. They outline what Brussels is still not getting right on AI and debate what is urgently needed in 2026: a long-term AI, data &amp; digital strategy for Europe, the courage for bold political leadership, and taking action where it matters most. <br/><br/></p><p><b>KEY TOPICS:</b></p><ul><li><b>00:00 — Intro</b></li><li><b>07:08 — Davos and the geopolitics of AI</b></li><li><b>12:03 — Why the EU lacks a long-term strategy for AI and digital policy</b></li><li><b>16:09 — The “European Way”: Partnerships and more focus on  areas where the EU could actually lead</b></li><li><b>24:00 — Beyond scattered Moonshots: Making AI work across the European economy</b></li><li><b>27:58 — AI Factories and Digital Innovation Hubs? That&apos;s not enough! The EU needs an AI innovation ecosystem</b></li><li><b>31:09 — The EU&apos;s opportunity costs of chasing frontier models and more compute. Let&apos;s focus on AI adoption instead!</b></li><li><b>36:52 — Proprietary business data: The EU’s real competitive AI advantage?</b></li><li><b>39:05 — Where the Data Act &amp;  Data Governance Act fall short</b></li><li><b>50:08 — Why the EU policy cycle is broken — and why Kai calls for more courage and bold political leadership</b></li><li><b>53:25 — The biggest risks &amp; opportunities in 2026 for the EU&apos;s digital policy </b></li><li><b>57:42 — The surprising impact of public procurement on the AI startup ecosystem</b></li></ul><p><br/></p><p><b>Follow Kai Zenner on:</b></p><p>LinkedIn: https://www.linkedin.com/in/kzenner/?skipRedirect=true</p><p>Website: https://www.kaizenner.eu/</p>]]></description>
    <content:encoded><![CDATA[<p>In the first episode of season 6, <b>Alexandra Ebert </b>sits down with <b>Kai Zenner</b>, Head of Office and Digital Policy Adviser to MEP Axel Voss at the <b>European Parliament</b>, for a deep dive into Europe’s digital future. They outline what Brussels is still not getting right on AI and debate what is urgently needed in 2026: a long-term AI, data &amp; digital strategy for Europe, the courage for bold political leadership, and taking action where it matters most. <br/><br/></p><p><b>KEY TOPICS:</b></p><ul><li><b>00:00 — Intro</b></li><li><b>07:08 — Davos and the geopolitics of AI</b></li><li><b>12:03 — Why the EU lacks a long-term strategy for AI and digital policy</b></li><li><b>16:09 — The “European Way”: Partnerships and more focus on  areas where the EU could actually lead</b></li><li><b>24:00 — Beyond scattered Moonshots: Making AI work across the European economy</b></li><li><b>27:58 — AI Factories and Digital Innovation Hubs? That&apos;s not enough! The EU needs an AI innovation ecosystem</b></li><li><b>31:09 — The EU&apos;s opportunity costs of chasing frontier models and more compute. Let&apos;s focus on AI adoption instead!</b></li><li><b>36:52 — Proprietary business data: The EU’s real competitive AI advantage?</b></li><li><b>39:05 — Where the Data Act &amp;  Data Governance Act fall short</b></li><li><b>50:08 — Why the EU policy cycle is broken — and why Kai calls for more courage and bold political leadership</b></li><li><b>53:25 — The biggest risks &amp; opportunities in 2026 for the EU&apos;s digital policy </b></li><li><b>57:42 — The surprising impact of public procurement on the AI startup ecosystem</b></li></ul><p><br/></p><p><b>Follow Kai Zenner on:</b></p><p>LinkedIn: https://www.linkedin.com/in/kzenner/?skipRedirect=true</p><p>Website: https://www.kaizenner.eu/</p>]]></content:encoded>
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    <pubDate>Fri, 27 Mar 2026 14:00:00 +0100</pubDate>
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  <psc:chapter start="16:09" title="The European Way: What to do?" />
  <psc:chapter start="24:00" title="Focus on entire economy, not moonshots" />
  <psc:chapter start="27:58" title="EU needs AI innovation ecosystem" />
  <psc:chapter start="31:09" title="Opportunity costs of chasing frontier models" />
  <psc:chapter start="36:52" title="The EU&#39;s data advantage?" />
  <psc:chapter start="39:05" title="Where DA &amp; DGA fall short" />
  <psc:chapter start="50:08" title="The broken EU policy cycle" />
  <psc:chapter start="53:25" title="2026 AI Policy: Risks &amp; opportunities" />
  <psc:chapter start="57:42" title="Public procurement&#39;s role in AI innovation" />
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    <itunes:duration>3628</itunes:duration>
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    <itunes:title>52. Synthetic Data as a Strategic Enterprise Data Asset with AWS&#39; Faris Haddad</itunes:title>
    <title>52. Synthetic Data as a Strategic Enterprise Data Asset with AWS&#39; Faris Haddad</title>
    <itunes:summary><![CDATA[Welcome back to season 5 of the Data Democratization Podcast - and our first-ever live studio recording.  In this episode, Alexandra Ebert sits down with Faris Haddad, AWS' Global AI Technical Strategy Lead. Together, they delve into the transformative role of synthetic data in modern enterprises.   Faris shares his journey into the world of synthetic data, highlighting its evolution from a niche solution to a cornerstone of enterprise data strategy. He discusses the challenges organizat...]]></itunes:summary>
    <description><![CDATA[<p>Welcome back to season 5 of the Data Democratization Podcast - and our first-ever live studio recording.<br/><br/>In this episode, Alexandra Ebert sits down with Faris Haddad, AWS&apos; Global AI Technical Strategy Lead. Together, they delve into the transformative role of synthetic data in modern enterprises.  </p><p>Faris shares his journey into the world of synthetic data, highlighting its evolution from a niche solution to a cornerstone of enterprise data strategy. He discusses the challenges organizations face with data silos, legacy systems, and privacy concerns, and how synthetic data offers a pathway to overcome these hurdles.  <br/><br/>Whether you&apos;re grappling with data accessibility issues or exploring innovative ways to leverage your organization&apos;s data assets, this episode offers valuable perspectives on integrating synthetic data into your enterprise data strategy. </p>]]></description>
    <content:encoded><![CDATA[<p>Welcome back to season 5 of the Data Democratization Podcast - and our first-ever live studio recording.<br/><br/>In this episode, Alexandra Ebert sits down with Faris Haddad, AWS&apos; Global AI Technical Strategy Lead. Together, they delve into the transformative role of synthetic data in modern enterprises.  </p><p>Faris shares his journey into the world of synthetic data, highlighting its evolution from a niche solution to a cornerstone of enterprise data strategy. He discusses the challenges organizations face with data silos, legacy systems, and privacy concerns, and how synthetic data offers a pathway to overcome these hurdles.  <br/><br/>Whether you&apos;re grappling with data accessibility issues or exploring innovative ways to leverage your organization&apos;s data assets, this episode offers valuable perspectives on integrating synthetic data into your enterprise data strategy. </p>]]></content:encoded>
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    <pubDate>Fri, 06 Jun 2025 10:00:00 +0200</pubDate>
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    <itunes:duration>2728</itunes:duration>
    <itunes:keywords>Artificial Intelligence, AWS</itunes:keywords>
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    <itunes:title>Democratizing AI? Not Without Data Intelligence &amp; Synthetic Data—Ari Kaplan on the Biggest Roadblocks to Scaling AI</itunes:title>
    <title>Democratizing AI? Not Without Data Intelligence &amp; Synthetic Data—Ari Kaplan on the Biggest Roadblocks to Scaling AI</title>
    <itunes:summary><![CDATA[AI democratization sounds great in theory, but why do so many enterprises struggle to make it work? In this episode, Ari Kaplan, Head of Tech Evangelism at Databricks, breaks down the biggest roadblocks to scaling AI—and what’s needed to overcome them. From data intelligence and synthetic data to why leading enterprises rely on unified data and analytics Platforms to cut costs, reduce governance complexity, and streamline AI adoption—we explore how organizations can move beyond AI pilot purga...]]></itunes:summary>
    <description><![CDATA[<p><b>AI democratization</b> sounds great in theory, but why do so many enterprises struggle to make it work? In this episode, <b>Ari Kaplan, Head of Tech Evangelism</b> at <b>Databricks</b>, breaks down the biggest roadblocks to scaling AI—and what’s needed to overcome them. From data intelligence and synthetic data to why leading enterprises rely on unified data and analytics Platforms to cut costs, reduce governance complexity, and streamline AI adoption—we explore how organizations can move beyond AI pilot purgatory and use AI to drive tangible impact at scale.</p><p>Ari dives into the hard truths about AI implementation, including why companies still face governance hurdles, siloed data, and inefficient infrastructure. Ari and I discuss how organizations can get more value from their data, deploy AI responsibly, and use synthetic data to scale securely.<br/><br/>Plus, Ari shares his personal approach to balancing a global career, thought leadership, and content creation—including how he manages to make time for writing books while advising enterprises worldwide. We also discuss his take on social media strategy, the skills he’s encouraging his kids to develop for an AI-driven world, and the future of work in an era of intelligent automation.</p><p>If you care about AI democratization, enterprise AI strategy, and staying ahead of the curve, this is an episode you won’t want to miss!</p><p><br/><br/></p>]]></description>
    <content:encoded><![CDATA[<p><b>AI democratization</b> sounds great in theory, but why do so many enterprises struggle to make it work? In this episode, <b>Ari Kaplan, Head of Tech Evangelism</b> at <b>Databricks</b>, breaks down the biggest roadblocks to scaling AI—and what’s needed to overcome them. From data intelligence and synthetic data to why leading enterprises rely on unified data and analytics Platforms to cut costs, reduce governance complexity, and streamline AI adoption—we explore how organizations can move beyond AI pilot purgatory and use AI to drive tangible impact at scale.</p><p>Ari dives into the hard truths about AI implementation, including why companies still face governance hurdles, siloed data, and inefficient infrastructure. Ari and I discuss how organizations can get more value from their data, deploy AI responsibly, and use synthetic data to scale securely.<br/><br/>Plus, Ari shares his personal approach to balancing a global career, thought leadership, and content creation—including how he manages to make time for writing books while advising enterprises worldwide. We also discuss his take on social media strategy, the skills he’s encouraging his kids to develop for an AI-driven world, and the future of work in an era of intelligent automation.</p><p>If you care about AI democratization, enterprise AI strategy, and staying ahead of the curve, this is an episode you won’t want to miss!</p><p><br/><br/></p>]]></content:encoded>
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    <pubDate>Thu, 20 Feb 2025 16:00:00 +0100</pubDate>
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    <itunes:duration>3240</itunes:duration>
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    <itunes:title>50. How to Democratize Data and Bridge AI&#39;s Tech/Business-Gap with Erste Group&#39;s Anna Lishchenko</itunes:title>
    <title>50. How to Democratize Data and Bridge AI&#39;s Tech/Business-Gap with Erste Group&#39;s Anna Lishchenko</title>
    <itunes:summary><![CDATA[For the 50th episode of the Data Democratization Podcast, I sat down with Anna Lishchenko, Data &amp; Analytics for Business Platform Lead at Erste Group. As a true champion of data democratization, Anna shares invaluable insights into how to make data widely accessible, actionable, and impactful across a large, decentralized organization. 💡 What you'll learn: The essential elements of building a data-driven culture, including data literacy, governance, and community building.Laying the found...]]></itunes:summary>
    <description><![CDATA[<p>For the 50th episode of the Data Democratization Podcast, I sat down with Anna Lishchenko, Data &amp; Analytics for Business Platform Lead at Erste Group. As a true champion of data democratization, Anna shares invaluable insights into how to make data widely accessible, actionable, and impactful across a large, decentralized organization.</p><p>💡 <b>What you&apos;ll learn:</b></p><ul><li><b>The essential elements</b> of building a data-driven culture, including data literacy, governance, and community building.</li><li><b>Laying the foundation for success:</b> How to align data and AI initiatives with business goals and secure buy-in from key stakeholders.</li><li><b>Breaking barriers to experimentation:</b> Using synthetic data to democratize access and accelerate innovation.</li><li><b>Bridging silos:</b> Connecting business and technical teams to drive collaboration and create real impact.</li><li><b>Scaling AI and data initiatives:</b> Turning one-off projects into sustainable enterprise-wide strategies.</li></ul><p>Whether you&apos;re just starting on your AI journey or scaling data initiatives, this episode is packed with actionable insights and practical advice. Don’t miss this engaging conversation about the status-quo and the future of data democratization!</p>]]></description>
    <content:encoded><![CDATA[<p>For the 50th episode of the Data Democratization Podcast, I sat down with Anna Lishchenko, Data &amp; Analytics for Business Platform Lead at Erste Group. As a true champion of data democratization, Anna shares invaluable insights into how to make data widely accessible, actionable, and impactful across a large, decentralized organization.</p><p>💡 <b>What you&apos;ll learn:</b></p><ul><li><b>The essential elements</b> of building a data-driven culture, including data literacy, governance, and community building.</li><li><b>Laying the foundation for success:</b> How to align data and AI initiatives with business goals and secure buy-in from key stakeholders.</li><li><b>Breaking barriers to experimentation:</b> Using synthetic data to democratize access and accelerate innovation.</li><li><b>Bridging silos:</b> Connecting business and technical teams to drive collaboration and create real impact.</li><li><b>Scaling AI and data initiatives:</b> Turning one-off projects into sustainable enterprise-wide strategies.</li></ul><p>Whether you&apos;re just starting on your AI journey or scaling data initiatives, this episode is packed with actionable insights and practical advice. Don’t miss this engaging conversation about the status-quo and the future of data democratization!</p>]]></content:encoded>
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    <pubDate>Thu, 21 Nov 2024 13:00:00 +0100</pubDate>
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    <itunes:duration>3235</itunes:duration>
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    <itunes:title>49. &quot;Forget copying others — every organization needs to build their own AI muscle&quot; with Microsoft&#39;s Daragh Morrissey</itunes:title>
    <title>49. &quot;Forget copying others — every organization needs to build their own AI muscle&quot; with Microsoft&#39;s Daragh Morrissey</title>
    <itunes:summary><![CDATA[In episode 2 of the new season, Alexandra Ebert chats with Daragh Morrissey, Microsoft’s Director of AI for Worldwide Financial Services, recorded live at Money2020 US. Daragh offers a global perspective on AI adoption in financial services, highlighting unique strategies and challenges faced by institutions worldwide. He explains why Canada and Australia stand out in AI progress and why succeeding with Gen AI requires financial institutions to shift from over-strategizing to focusing on tang...]]></itunes:summary>
    <description><![CDATA[<p>In episode 2 of the new season, Alexandra Ebert chats with Daragh Morrissey, Microsoft’s Director of AI for Worldwide Financial Services, recorded live at Money2020 US. Daragh offers a global perspective on AI adoption in financial services, highlighting unique strategies and challenges faced by institutions worldwide. He explains why Canada and Australia stand out in AI progress and why succeeding with Gen AI requires financial institutions to shift from over-strategizing to focusing on tangible outcomes.<br/><br/>Daragh also shares insights on impactful AI applications in financial services, from automating contact centers to upselling, enhancing customer relationships, and modernizing legacy code. Lastly, Alexandra and Daragh take a look at the future of work and the role autonomous agents might play. They also debate whether AI will free up advisors time and whether, as a result, banks will have many more human advisors, or if the future of personalized banking will be more automated, yet transformative in enhancing individual financial health and fostering greater inclusivity. <br/><br/>Daragh’s compelling anecdotes and strategic insights make this episode a must-listen for anyone interested in AI’s future in financial services.<br/><br/><br/><b>Table of Contents:</b></p><ul><li><b>0:00 - 2:39</b> Introduction to the Episode and Guest</li><li><b>2:39 - 4:42</b> Daragh&apos;s Role and Microsoft&apos;s AI Approach in Financial Services</li><li><b>4:42 - 6:37</b> Patterns in Successful AI Adoption Globally</li><li><b>6:37 - 8:20</b> Gen AI Adoption: Early Success Stories and Lessons Learned</li><li><b>8:20 - 10:59</b> Overcoming Challenges: Moving Beyond Perfectionism in AI Projects</li><li><b>10:59 - 12:14</b> The Shift in Financial Services AI Use Cases</li><li><b>12:14 - 14:36</b> Regional Differences in AI Approaches in Financial Services</li><li><b>14:36 - 17:55</b> AI Use Cases in Financial Services: From Advisors to Autonomous Agents</li><li><b>17:55 - 20:00</b> Ethical Challenges and Responsible AI in Financial Services</li><li><b>20:00 - 23:25</b> The Future of Financial Services AI: Customer Relationship Innovations</li><li><b>23:25 - 27:32</b> Expanding Financial Inclusion with AI and Responsible AI Practices</li><li><b>27:32 - 29:41</b> Closing Thoughts on AI’s Impact on Financial Services</li></ul>]]></description>
    <content:encoded><![CDATA[<p>In episode 2 of the new season, Alexandra Ebert chats with Daragh Morrissey, Microsoft’s Director of AI for Worldwide Financial Services, recorded live at Money2020 US. Daragh offers a global perspective on AI adoption in financial services, highlighting unique strategies and challenges faced by institutions worldwide. He explains why Canada and Australia stand out in AI progress and why succeeding with Gen AI requires financial institutions to shift from over-strategizing to focusing on tangible outcomes.<br/><br/>Daragh also shares insights on impactful AI applications in financial services, from automating contact centers to upselling, enhancing customer relationships, and modernizing legacy code. Lastly, Alexandra and Daragh take a look at the future of work and the role autonomous agents might play. They also debate whether AI will free up advisors time and whether, as a result, banks will have many more human advisors, or if the future of personalized banking will be more automated, yet transformative in enhancing individual financial health and fostering greater inclusivity. <br/><br/>Daragh’s compelling anecdotes and strategic insights make this episode a must-listen for anyone interested in AI’s future in financial services.<br/><br/><br/><b>Table of Contents:</b></p><ul><li><b>0:00 - 2:39</b> Introduction to the Episode and Guest</li><li><b>2:39 - 4:42</b> Daragh&apos;s Role and Microsoft&apos;s AI Approach in Financial Services</li><li><b>4:42 - 6:37</b> Patterns in Successful AI Adoption Globally</li><li><b>6:37 - 8:20</b> Gen AI Adoption: Early Success Stories and Lessons Learned</li><li><b>8:20 - 10:59</b> Overcoming Challenges: Moving Beyond Perfectionism in AI Projects</li><li><b>10:59 - 12:14</b> The Shift in Financial Services AI Use Cases</li><li><b>12:14 - 14:36</b> Regional Differences in AI Approaches in Financial Services</li><li><b>14:36 - 17:55</b> AI Use Cases in Financial Services: From Advisors to Autonomous Agents</li><li><b>17:55 - 20:00</b> Ethical Challenges and Responsible AI in Financial Services</li><li><b>20:00 - 23:25</b> The Future of Financial Services AI: Customer Relationship Innovations</li><li><b>23:25 - 27:32</b> Expanding Financial Inclusion with AI and Responsible AI Practices</li><li><b>27:32 - 29:41</b> Closing Thoughts on AI’s Impact on Financial Services</li></ul>]]></content:encoded>
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    <pubDate>Thu, 14 Nov 2024 14:00:00 +0100</pubDate>
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    <itunes:duration>2810</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:season>1</itunes:season>
    <itunes:episode>49</itunes:episode>
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  <item>
    <itunes:title>48. Driving Impact with (Gen) AI for Financial Services with NVIDIA&#39;s Malcolm deMayo</itunes:title>
    <title>48. Driving Impact with (Gen) AI for Financial Services with NVIDIA&#39;s Malcolm deMayo</title>
    <itunes:summary><![CDATA[Welcome back to Season 4 of the Data Democratization Podcast! In the 1st episode of the new season, Alexandra Ebert sat down with Malcolm DeMayo, NVIDIA's VP of Global Financial Services, live at Money2020 US to dive into what it takes for financial services organizations to succeed with data and AI at scale.   Malcolm shares insights on using data as a true differentiator, why Responsible AI practices are more important than ever, and how modern privacy-enhancing technologies - like fed...]]></itunes:summary>
    <description><![CDATA[<p>Welcome back to Season 4 of the Data Democratization Podcast! In the 1st episode of the new season, Alexandra Ebert sat down with Malcolm DeMayo, NVIDIA&apos;s VP of Global Financial Services, live at Money2020 US to dive into what it takes for financial services organizations to succeed with data and AI at scale. <br/><br/>Malcolm shares insights on using data as a true differentiator, why Responsible AI practices are more important than ever, and how modern privacy-enhancing technologies - like federated learning and synthetic data - help tackle common data challenges. He also sheds light on how Gen AI is impacting talent and the surprising ways AI assistants might help organizations counteract the negative effects of employee churn. And, of course, Alexandra asks Malcolm for his vision for the future of AI in financial services. </p><p>Check out<a href='https://mostly.ai/data-democratization-podcasts'> other episodes of the Data Democratization Podcast</a> for more stories about data, privacy, responsible AI and how to do data democratization well.</p>]]></description>
    <content:encoded><![CDATA[<p>Welcome back to Season 4 of the Data Democratization Podcast! In the 1st episode of the new season, Alexandra Ebert sat down with Malcolm DeMayo, NVIDIA&apos;s VP of Global Financial Services, live at Money2020 US to dive into what it takes for financial services organizations to succeed with data and AI at scale. <br/><br/>Malcolm shares insights on using data as a true differentiator, why Responsible AI practices are more important than ever, and how modern privacy-enhancing technologies - like federated learning and synthetic data - help tackle common data challenges. He also sheds light on how Gen AI is impacting talent and the surprising ways AI assistants might help organizations counteract the negative effects of employee churn. And, of course, Alexandra asks Malcolm for his vision for the future of AI in financial services. </p><p>Check out<a href='https://mostly.ai/data-democratization-podcasts'> other episodes of the Data Democratization Podcast</a> for more stories about data, privacy, responsible AI and how to do data democratization well.</p>]]></content:encoded>
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    <link>https://mostly.ai/data-democratization-podcast/48-driving-impact-with-gen-ai-for-financial-services-with-nvidias-malcolm-demayo</link>
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    <pubDate>Thu, 07 Nov 2024 17:00:00 +0100</pubDate>
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    <podcast:soundbite startTime="443.417" duration="45.5" />
    <itunes:duration>2360</itunes:duration>
    <itunes:keywords>AI, Generative AI, NVIDIA, synthetic data, banking, financial services</itunes:keywords>
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    <itunes:title>47. The secrets of unlocking business value with your data strategy</itunes:title>
    <title>47. The secrets of unlocking business value with your data strategy</title>
    <itunes:summary><![CDATA[In the 47th episode of the Data Democratization Podcast, host Alexandra Ebert talks to Maritza Curry, Head of Data at RCS South Africa, to explore practical insights into developing effective data strategies. The discussion delves into the importance of solid data management and data governance. It also covers the topic of whether an AI strategy is necessary and the critical need for integrating business literacy into AI and data initiatives. Maritza offers valuable tips from her extensive ex...]]></itunes:summary>
    <description><![CDATA[<p>In the 47th episode of the Data Democratization Podcast, host Alexandra Ebert talks to Maritza Curry, Head of Data at RCS South Africa, to explore practical insights into developing effective data strategies. The discussion delves into the importance of solid data management and data governance. It also covers the topic of whether an AI strategy is necessary and the critical need for integrating business literacy into AI and data initiatives. Maritza offers valuable tips from her extensive experience, emphasizing the importance of good communication. She highlights the necessity of talking not only to executives but also to those on the frontlines in order to develop effective data strategies and tailor them to best fit your organizational culture.<br/><br/><a href='https://mostly.ai/data-democratization-podcasts'>Check out the other episodes of the Data Democratization Podcast</a> for more stories about data, privacy, responsible AI and how to do data democratization well. <br/><br/></p>]]></description>
    <content:encoded><![CDATA[<p>In the 47th episode of the Data Democratization Podcast, host Alexandra Ebert talks to Maritza Curry, Head of Data at RCS South Africa, to explore practical insights into developing effective data strategies. The discussion delves into the importance of solid data management and data governance. It also covers the topic of whether an AI strategy is necessary and the critical need for integrating business literacy into AI and data initiatives. Maritza offers valuable tips from her extensive experience, emphasizing the importance of good communication. She highlights the necessity of talking not only to executives but also to those on the frontlines in order to develop effective data strategies and tailor them to best fit your organizational culture.<br/><br/><a href='https://mostly.ai/data-democratization-podcasts'>Check out the other episodes of the Data Democratization Podcast</a> for more stories about data, privacy, responsible AI and how to do data democratization well. <br/><br/></p>]]></content:encoded>
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    <itunes:author>MOSTLY AI</itunes:author>
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    <pubDate>Thu, 14 Dec 2023 10:00:00 +0100</pubDate>
    <itunes:duration>3063</itunes:duration>
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    <itunes:season>1</itunes:season>
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  <item>
    <itunes:title>46. How to (finally) move your AI products to production</itunes:title>
    <title>46. How to (finally) move your AI products to production</title>
    <itunes:summary><![CDATA[In the 46th episode of the Data Democratization Podcast, host Alexandra Ebert is talking to Wolfgang Weidinger, AI, Data Science, and Analytics Coordinator at Generali Insurance, Austria, and Chairman Of The Board at the Vienna Data Science Group.  Wolfgang is a seasoned data scientist with tons of experience managing AI, data science, and analytics projects.   The episode covers a wide range of topics, offering actionable tips for those looking to deploy AI models in large organizations...]]></itunes:summary>
    <description><![CDATA[<p>In the 46th episode of the <a href='https://mostly.ai/data-democratization-podcasts'>Data Democratization Podcast</a>, host Alexandra Ebert is talking to Wolfgang Weidinger, AI, Data Science, and Analytics Coordinator at Generali Insurance, Austria, and Chairman Of The Board at the Vienna Data Science Group.<br/> Wolfgang is a seasoned data scientist with tons of experience managing AI, data science, and analytics projects. <br/><br/>The episode covers a wide range of topics, offering actionable tips for those looking to deploy AI models in large organizations:</p><ul><li>selecting the right tools for AI projects,</li><li>the adoption of AI in various industries,</li><li>the significance of soft skills, collaboration, and domain knowledge,</li><li>the organizational role of the data scientist,</li><li>how to bridge the gap between business and technology.</li></ul><p>If you would like to learn more about data science and AI in practice, we recommend <a href='https://www.hanser-elibrary.com/doi/book/10.3139/9781569908877'>The Handbook of Data Science and AI - Generate Value from Data with Machine Learning and Data Analytics</a>, co-authored by Wolfgang. If you are in Vienna, Austria, follow the <a href='https://viennadatasciencegroup.at/'>Vienna Data Science Group</a> for great meetups and opportunities to connect with the local data science community!</p>]]></description>
    <content:encoded><![CDATA[<p>In the 46th episode of the <a href='https://mostly.ai/data-democratization-podcasts'>Data Democratization Podcast</a>, host Alexandra Ebert is talking to Wolfgang Weidinger, AI, Data Science, and Analytics Coordinator at Generali Insurance, Austria, and Chairman Of The Board at the Vienna Data Science Group.<br/> Wolfgang is a seasoned data scientist with tons of experience managing AI, data science, and analytics projects. <br/><br/>The episode covers a wide range of topics, offering actionable tips for those looking to deploy AI models in large organizations:</p><ul><li>selecting the right tools for AI projects,</li><li>the adoption of AI in various industries,</li><li>the significance of soft skills, collaboration, and domain knowledge,</li><li>the organizational role of the data scientist,</li><li>how to bridge the gap between business and technology.</li></ul><p>If you would like to learn more about data science and AI in practice, we recommend <a href='https://www.hanser-elibrary.com/doi/book/10.3139/9781569908877'>The Handbook of Data Science and AI - Generate Value from Data with Machine Learning and Data Analytics</a>, co-authored by Wolfgang. If you are in Vienna, Austria, follow the <a href='https://viennadatasciencegroup.at/'>Vienna Data Science Group</a> for great meetups and opportunities to connect with the local data science community!</p>]]></content:encoded>
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    <pubDate>Thu, 19 Oct 2023 11:00:00 +0200</pubDate>
    <itunes:duration>3090</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:season>1</itunes:season>
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  <item>
    <itunes:title>45. Mastering AI &amp; Data Governance with Mastercard&#39;s Chief Privacy &amp; Data Responsibility Officer, Caroline Louveaux</itunes:title>
    <title>45. Mastering AI &amp; Data Governance with Mastercard&#39;s Chief Privacy &amp; Data Responsibility Officer, Caroline Louveaux</title>
    <itunes:summary><![CDATA[In this episode of the Data Democratization Podcast, host Alexandra Ebert, Chief Trust Officer at MOSTLY AI, sits down with Caroline Louveaux, Chief Privacy &amp; Data Responsibility Officer at Mastercard, to explore the evolving landscape of data privacy and AI governance. Caroline shares her insights on topics ranging from privacy-enhancing technologies (PETs) to data for social impact. Here is what you'll learn: How to be successful in today's data and AI ecosystem,What is the role of the ...]]></itunes:summary>
    <description><![CDATA[<p><b>In this episode of the Data Democratization Podcast, host Alexandra Ebert, Chief Trust Officer at </b><a href='https://mostly.ai/'><b>MOSTLY AI</b></a><b>, sits down with Caroline Louveaux, Chief Privacy &amp; Data Responsibility Officer at Mastercard, to explore the evolving landscape of data privacy and AI governance. Caroline shares her insights on topics ranging from privacy-enhancing technologies (PETs) to data for social impact. Here is what you&apos;ll learn:</b></p><ul><li><b>How to be successful in today&apos;s data and AI ecosystem,</b></li><li><b>What is the role of the Chief Data Responsibility Officer,</b></li><li><b>How to set up your organization for compliance with the &apos;alphabet soup of EU regulations&apos;,</b></li><li><b>How to make compliance loveable,</b></li><li><b>What&apos;s needed on the regulatory side,</b></li><li><b>How to enable AI innovation,</b></li><li><b>What is an AI governance framework, and how to make it work?</b></li><li><b>How can privacy pros prepare for AI?</b></li><li><b>How can privacy-enhancing technologies facilitate AI innovation?</b></li><li><b>Why is automation so important?</b></li><li><b>Can data and AI positively impact society?</b></li></ul><p><b>Dive into this conversation to better understand the importance of data governance and responsible data usage in the digital age. </b></p>]]></description>
    <content:encoded><![CDATA[<p><b>In this episode of the Data Democratization Podcast, host Alexandra Ebert, Chief Trust Officer at </b><a href='https://mostly.ai/'><b>MOSTLY AI</b></a><b>, sits down with Caroline Louveaux, Chief Privacy &amp; Data Responsibility Officer at Mastercard, to explore the evolving landscape of data privacy and AI governance. Caroline shares her insights on topics ranging from privacy-enhancing technologies (PETs) to data for social impact. Here is what you&apos;ll learn:</b></p><ul><li><b>How to be successful in today&apos;s data and AI ecosystem,</b></li><li><b>What is the role of the Chief Data Responsibility Officer,</b></li><li><b>How to set up your organization for compliance with the &apos;alphabet soup of EU regulations&apos;,</b></li><li><b>How to make compliance loveable,</b></li><li><b>What&apos;s needed on the regulatory side,</b></li><li><b>How to enable AI innovation,</b></li><li><b>What is an AI governance framework, and how to make it work?</b></li><li><b>How can privacy pros prepare for AI?</b></li><li><b>How can privacy-enhancing technologies facilitate AI innovation?</b></li><li><b>Why is automation so important?</b></li><li><b>Can data and AI positively impact society?</b></li></ul><p><b>Dive into this conversation to better understand the importance of data governance and responsible data usage in the digital age. </b></p>]]></content:encoded>
    <enclosure url="https://www.buzzsprout.com/1614655/episodes/13679052-45-mastering-ai-data-governance-with-mastercard-s-chief-privacy-data-responsibility-officer-caroline-louveaux.mp3" length="26477089" type="audio/mpeg" />
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    <pubDate>Thu, 28 Sep 2023 15:00:00 +0200</pubDate>
    <itunes:duration>2201</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:season>1</itunes:season>
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  <item>
    <itunes:title>44. Data Literacy and AI for All with DataCamp</itunes:title>
    <title>44. Data Literacy and AI for All with DataCamp</title>
    <itunes:summary><![CDATA[What is data and AI literacy, and why is it central to DataCamp's mission? In this episode, our host, Alexandra Ebert, MOSTLY AI's Chief Trust Officer, had the chance to talk to truly like-minded people. DataCamp's CEO and co-founder, Jo Cornelissen, and Maggie Remynse, VP of Curriculum, have both seen firsthand how transformative knowledge and access to data is.    If you are interested in Data and AI literacy, make sure you check out the vast resources DataCamp is going to share throug...]]></itunes:summary>
    <description><![CDATA[<p>What is data and AI literacy, and why is it central to DataCamp&apos;s mission? In this episode, our host, Alexandra Ebert, MOSTLY AI&apos;s Chief Trust Officer, had the chance to talk to truly like-minded people. DataCamp&apos;s CEO and co-founder, Jo Cornelissen, and Maggie Remynse, VP of Curriculum, have both seen firsthand how transformative knowledge and access to data is.  <br/><br/>If you are interested in Data and AI literacy, make sure you check out the vast resources DataCamp is going to share throughout September 2023 during their annual Data and AI Literacy Month. There are top-notch experts sharing their knowledge during webinars, podcast episodes, and even a virtual conference on September 28th. And the best of all, it’s completely free of charge. Sign up here: https://bit.ly/3sMu8pJ </p>]]></description>
    <content:encoded><![CDATA[<p>What is data and AI literacy, and why is it central to DataCamp&apos;s mission? In this episode, our host, Alexandra Ebert, MOSTLY AI&apos;s Chief Trust Officer, had the chance to talk to truly like-minded people. DataCamp&apos;s CEO and co-founder, Jo Cornelissen, and Maggie Remynse, VP of Curriculum, have both seen firsthand how transformative knowledge and access to data is.  <br/><br/>If you are interested in Data and AI literacy, make sure you check out the vast resources DataCamp is going to share throughout September 2023 during their annual Data and AI Literacy Month. There are top-notch experts sharing their knowledge during webinars, podcast episodes, and even a virtual conference on September 28th. And the best of all, it’s completely free of charge. Sign up here: https://bit.ly/3sMu8pJ </p>]]></content:encoded>
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    <itunes:image href="https://storage.buzzsprout.com/9a2slkalkgitrdz7sz3x3qlth06i?.jpg" />
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    <pubDate>Thu, 07 Sep 2023 14:00:00 +0200</pubDate>
    <itunes:duration>3465</itunes:duration>
    <itunes:keywords></itunes:keywords>
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    <itunes:episode>44</itunes:episode>
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  <item>
    <itunes:title>43. Driving change in Payments: Strategies for success</itunes:title>
    <title>43. Driving change in Payments: Strategies for success</title>
    <itunes:summary><![CDATA[Recorded live at the Money2020 Europe conference, Alexandra Ebert, MOSTLY AI's Chief Trust Officer talks to Sulabh Agarwal, Accenture's Global Head of Payments. Sulabh shares his insights on the changing landscape of the payments industry and the factors driving its transformation. He highlights the influence of technology and the role of payments as a catalyst for innovation, improved customer experiences, and personalization in the payment process. The episode concludes with a discussion on...]]></itunes:summary>
    <description><![CDATA[<p>Recorded live at the Money2020 Europe conference, Alexandra Ebert, <a href='https://mostly.ai'>MOSTLY AI</a>&apos;s Chief Trust Officer talks to Sulabh Agarwal, Accenture&apos;s Global Head of Payments. Sulabh shares his insights on the changing landscape of the payments industry and the factors driving its transformation. He highlights the influence of technology and the role of payments as a catalyst for innovation, improved customer experiences, and personalization in the payment process. The episode concludes with a discussion on the future of payments and the actions payments executives should take to future-proof their strategies. <br/><br/></p><div><br/></div>]]></description>
    <content:encoded><![CDATA[<p>Recorded live at the Money2020 Europe conference, Alexandra Ebert, <a href='https://mostly.ai'>MOSTLY AI</a>&apos;s Chief Trust Officer talks to Sulabh Agarwal, Accenture&apos;s Global Head of Payments. Sulabh shares his insights on the changing landscape of the payments industry and the factors driving its transformation. He highlights the influence of technology and the role of payments as a catalyst for innovation, improved customer experiences, and personalization in the payment process. The episode concludes with a discussion on the future of payments and the actions payments executives should take to future-proof their strategies. <br/><br/></p><div><br/></div>]]></content:encoded>
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    <itunes:author>MOSTLY AI</itunes:author>
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    <pubDate>Wed, 12 Jul 2023 13:00:00 +0200</pubDate>
    <podcast:soundbite startTime="227.083" duration="18.0" />
    <itunes:duration>1983</itunes:duration>
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    <itunes:episode>43</itunes:episode>
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  <item>
    <itunes:title>42. On the future of digital health - and how to get there with Dr. Meshari Alwashmi</itunes:title>
    <title>42. On the future of digital health - and how to get there with Dr. Meshari Alwashmi</title>
    <itunes:summary><![CDATA[In this episode, we are joined by our esteemed guest, Dr. Meshari Alwashmi, a prominent Digital Health Scientist whose expertise spans not only extensive research but also a successful track record as a serial entrepreneur and trusted advisor to digital health initiatives. Prepare to be enlightened as we uncover the latest trends and advancements propelling the digital health industry forward. Discover the remarkable potential for progress and the direction in which this dynamic industry is h...]]></itunes:summary>
    <description><![CDATA[<p>In this episode, we are joined by our esteemed guest, Dr. Meshari Alwashmi, a prominent Digital Health Scientist whose expertise spans not only extensive research but also a successful track record as a serial entrepreneur and trusted advisor to digital health initiatives.</p><p>Prepare to be enlightened as we uncover the latest trends and advancements propelling the digital health industry forward. Discover the remarkable potential for progress and the direction in which this dynamic industry is heading. Moreover, we will delve into the invaluable contributions that <a href='https://mostly.ai/ebook/synthetic-data-in-healthcare'>synthetic data in healthcare</a> can make to this ongoing revolution.</p><p>This episode offers much more than just a glimpse into the future of digital health. Tune in for actionable advice that will guide your organization toward embracing innovation and achieving success in the realm of digital health.</p>]]></description>
    <content:encoded><![CDATA[<p>In this episode, we are joined by our esteemed guest, Dr. Meshari Alwashmi, a prominent Digital Health Scientist whose expertise spans not only extensive research but also a successful track record as a serial entrepreneur and trusted advisor to digital health initiatives.</p><p>Prepare to be enlightened as we uncover the latest trends and advancements propelling the digital health industry forward. Discover the remarkable potential for progress and the direction in which this dynamic industry is heading. Moreover, we will delve into the invaluable contributions that <a href='https://mostly.ai/ebook/synthetic-data-in-healthcare'>synthetic data in healthcare</a> can make to this ongoing revolution.</p><p>This episode offers much more than just a glimpse into the future of digital health. Tune in for actionable advice that will guide your organization toward embracing innovation and achieving success in the realm of digital health.</p>]]></content:encoded>
    <enclosure url="https://www.buzzsprout.com/1614655/episodes/13087295-42-on-the-future-of-digital-health-and-how-to-get-there-with-dr-meshari-alwashmi.mp3" length="33332593" type="audio/mpeg" />
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    <pubDate>Thu, 22 Jun 2023 10:00:00 +0200</pubDate>
    <itunes:duration>2773</itunes:duration>
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    <itunes:title>41. Synthetic data for impact: how to innovate in health insurance with Daniela Pak-Graf, Merkur Innovation Lab</itunes:title>
    <title>41. Synthetic data for impact: how to innovate in health insurance with Daniela Pak-Graf, Merkur Innovation Lab</title>
    <itunes:summary><![CDATA[In this episode of the Data Democratization Podcast, host Alexandra Ebert interviews Daniela Pak-Graf, the managing director of Merkur Innovation Lab — the innovation arm of Merkur Insurance. Daniela shares her tips and best practices for innovating with data in one of the most conservative and sensitive industries, health insurance. Tune in to find out how to accelerate innovation through effective data management, forward thinking organizational decisions and enabling technologies, like AI-...]]></itunes:summary>
    <description><![CDATA[<p><b>In this episode of the Data Democratization Podcast, host Alexandra Ebert interviews Daniela Pak-Graf, the managing director of </b><a href='https://www.linkedin.com/company/merkur-innovation-lab/'><b>Merkur Innovation Lab</b></a><b> — the innovation arm of Merkur Insurance. Daniela shares her tips and best practices for innovating with data in one of the most conservative and sensitive industries, health insurance. Tune in to find out how to accelerate innovation through effective data management, forward thinking organizational decisions and enabling technologies, like </b><a href='https://mostly.ai/synthetic-data-platform/generate-synthetic-data'><b>AI-powered synthetic data generation</b></a><b>.</b></p>]]></description>
    <content:encoded><![CDATA[<p><b>In this episode of the Data Democratization Podcast, host Alexandra Ebert interviews Daniela Pak-Graf, the managing director of </b><a href='https://www.linkedin.com/company/merkur-innovation-lab/'><b>Merkur Innovation Lab</b></a><b> — the innovation arm of Merkur Insurance. Daniela shares her tips and best practices for innovating with data in one of the most conservative and sensitive industries, health insurance. Tune in to find out how to accelerate innovation through effective data management, forward thinking organizational decisions and enabling technologies, like </b><a href='https://mostly.ai/synthetic-data-platform/generate-synthetic-data'><b>AI-powered synthetic data generation</b></a><b>.</b></p>]]></content:encoded>
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    <pubDate>Thu, 01 Jun 2023 08:00:00 +0200</pubDate>
    <podcast:soundbite startTime="317.0" duration="47.0" />
    <itunes:duration>3116</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:season>1</itunes:season>
    <itunes:episode>41</itunes:episode>
    <itunes:episodeType>full</itunes:episodeType>
    <itunes:explicit>false</itunes:explicit>
  </item>
  <item>
    <itunes:title>40. Synthetic data beyond privacy: data augmentation powered by AI</itunes:title>
    <title>40. Synthetic data beyond privacy: data augmentation powered by AI</title>
    <itunes:summary><![CDATA[The 40th episode is a special one. We invited MOSTLY AI's Chief Product Officer, Mario Scriminaci, to quiz him about synthetic data technology and how the filed is progressing beyond the data privacy use case. Mario will share how MOSTLY AI is developing its synthetic data platform to provide users with easy and fast data augmentation tools. The frontiers of generative synthetic data is exciting - tune in to learn what's already a reality and what the future holds. ]]></itunes:summary>
    <description><![CDATA[<p>The 40th episode is a special one. We invited MOSTLY AI&apos;s Chief Product Officer, Mario Scriminaci, to quiz him about synthetic data technology and how the filed is progressing beyond the data privacy use case. Mario will share how MOSTLY AI is developing its synthetic data platform to provide users with easy and fast data augmentation tools. The frontiers of generative synthetic data is exciting - tune in to learn what&apos;s already a reality and what the future holds.</p>]]></description>
    <content:encoded><![CDATA[<p>The 40th episode is a special one. We invited MOSTLY AI&apos;s Chief Product Officer, Mario Scriminaci, to quiz him about synthetic data technology and how the filed is progressing beyond the data privacy use case. Mario will share how MOSTLY AI is developing its synthetic data platform to provide users with easy and fast data augmentation tools. The frontiers of generative synthetic data is exciting - tune in to learn what&apos;s already a reality and what the future holds.</p>]]></content:encoded>
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    <pubDate>Thu, 11 May 2023 09:00:00 +0200</pubDate>
    <itunes:duration>2763</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:season>1</itunes:season>
    <itunes:episode>40</itunes:episode>
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  </item>
  <item>
    <itunes:title>39. What you didn&#39;t know about AI transparency with Rania Wazir, co-founder and AI expert</itunes:title>
    <title>39. What you didn&#39;t know about AI transparency with Rania Wazir, co-founder and AI expert</title>
    <itunes:summary><![CDATA[In episode 39 of the Data Democratization Podcast, host Alexandra Ebert, Chief Trust Officer at MOSTLY AI, is joined by Rania Wasir, co-founder and CTO of leiwand.ai, to discuss AI transparency, the misconceptions surrounding AI transparency and fairness, and why having a standard for transparency is important. The episode also explores the concepts of fairness and explainability in AI, and how they differ from transparency. The challenges of detecting biases in large language models such as ...]]></itunes:summary>
    <description><![CDATA[<p>In episode 39 of the Data Democratization Podcast, host Alexandra Ebert, Chief Trust Officer at <a href='https://mostly.ai/'>MOSTLY AI</a>, is joined by Rania Wasir, co-founder and CTO of <a href='https://www.leiwand.ai/'>leiwand.ai</a>, to discuss AI transparency, the misconceptions surrounding AI transparency and fairness, and why having a standard for transparency is important. The episode also explores the concepts of fairness and explainability in AI, and how they differ from transparency. The challenges of detecting biases in large language models such as ChatGPT are also explored.</p>]]></description>
    <content:encoded><![CDATA[<p>In episode 39 of the Data Democratization Podcast, host Alexandra Ebert, Chief Trust Officer at <a href='https://mostly.ai/'>MOSTLY AI</a>, is joined by Rania Wasir, co-founder and CTO of <a href='https://www.leiwand.ai/'>leiwand.ai</a>, to discuss AI transparency, the misconceptions surrounding AI transparency and fairness, and why having a standard for transparency is important. The episode also explores the concepts of fairness and explainability in AI, and how they differ from transparency. The challenges of detecting biases in large language models such as ChatGPT are also explored.</p>]]></content:encoded>
    <enclosure url="https://www.buzzsprout.com/1614655/episodes/12688627-39-what-you-didn-t-know-about-ai-transparency-with-rania-wazir-co-founder-and-ai-expert.mp3" length="38199472" type="audio/mpeg" />
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    <pubDate>Thu, 20 Apr 2023 11:00:00 +0200</pubDate>
    <itunes:duration>3177</itunes:duration>
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  <item>
    <itunes:title>38. Building trusted ML products with Karin Schöfegger (Ex-Google &amp; N26)</itunes:title>
    <title>38. Building trusted ML products with Karin Schöfegger (Ex-Google &amp; N26)</title>
    <itunes:summary><![CDATA[Karin Schöfegger is a seasoned ML product manager who knows how to create successful AI/ML products and mitigate the risks involved. In this episode, she shares her insights about challenges in building AI products. Tune in to learn about: How to align the business side and the data science side of product developmentWhat's the difference between traditional software development and machine learning developmentHow to bring customer understanding into data science and engineeringWhat are the m...]]></itunes:summary>
    <description><![CDATA[<p>Karin Schöfegger is a seasoned ML product manager who knows how to create successful AI/ML products and mitigate the risks involved. In this episode, she shares her insights about challenges in building AI products. Tune in to learn about:</p><ul><li>How to align the business side and the data science side of product development</li><li>What&apos;s the difference between traditional software development and machine learning development</li><li>How to bring customer understanding into data science and engineering</li><li>What are the most common traps in data science</li><li>Why it&apos;s essential to work with realistic data instead of picture-perfect datasets</li><li>How to get buy-in from stakeholders for ethical AI</li></ul>]]></description>
    <content:encoded><![CDATA[<p>Karin Schöfegger is a seasoned ML product manager who knows how to create successful AI/ML products and mitigate the risks involved. In this episode, she shares her insights about challenges in building AI products. Tune in to learn about:</p><ul><li>How to align the business side and the data science side of product development</li><li>What&apos;s the difference between traditional software development and machine learning development</li><li>How to bring customer understanding into data science and engineering</li><li>What are the most common traps in data science</li><li>Why it&apos;s essential to work with realistic data instead of picture-perfect datasets</li><li>How to get buy-in from stakeholders for ethical AI</li></ul>]]></content:encoded>
    <enclosure url="https://www.buzzsprout.com/1614655/episodes/12459144-38-building-trusted-ml-products-with-karin-schofegger-ex-google-n26.mp3" length="39447472" type="audio/mpeg" />
    <itunes:image href="https://storage.buzzsprout.com/20sgr5z95vcip2a0jyogrp2dwzpz?.jpg" />
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    <pubDate>Fri, 17 Mar 2023 11:00:00 +0100</pubDate>
    <itunes:duration>3282</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:season>3</itunes:season>
    <itunes:episode>38</itunes:episode>
    <itunes:episodeType>full</itunes:episodeType>
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  </item>
  <item>
    <itunes:title>37. How to effectively audit AI (and what to do today to get a head start on AI Act compliance)</itunes:title>
    <title>37. How to effectively audit AI (and what to do today to get a head start on AI Act compliance)</title>
    <itunes:summary><![CDATA[Kicking off season three of the Data Democratization podcast, our host, Alexandra Ebert, MOSTLY AI's Chief Trust Officer, talks to Ryan Carrier, Founder and Executive Director of the NGO For Humanity. Ryan's mission at For Humanity is to translate emerging AI regulation into auditable criteria, helping to build an AI ecosystem that people can trust.   If you want to learn more about For Humanity's work, join their Slack community or take one of their classes online. ]]></itunes:summary>
    <description><![CDATA[<p>Kicking off season three of the Data Democratization podcast, our host, Alexandra Ebert, MOSTLY AI&apos;s Chief Trust Officer, talks to Ryan Carrier, Founder and Executive Director of the NGO For Humanity. Ryan&apos;s mission at For Humanity is to translate emerging AI regulation into auditable criteria, helping to build an AI ecosystem that people can trust. <br/><br/>If you want to learn more about For Humanity&apos;s work, join <a href='https://forhumanity.center/get-involved/'>their Slack community</a> or take <a href='https://forhumanity.center/forhumanity-university/'>one of their classes online</a>.</p>]]></description>
    <content:encoded><![CDATA[<p>Kicking off season three of the Data Democratization podcast, our host, Alexandra Ebert, MOSTLY AI&apos;s Chief Trust Officer, talks to Ryan Carrier, Founder and Executive Director of the NGO For Humanity. Ryan&apos;s mission at For Humanity is to translate emerging AI regulation into auditable criteria, helping to build an AI ecosystem that people can trust. <br/><br/>If you want to learn more about For Humanity&apos;s work, join <a href='https://forhumanity.center/get-involved/'>their Slack community</a> or take <a href='https://forhumanity.center/forhumanity-university/'>one of their classes online</a>.</p>]]></content:encoded>
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    <pubDate>Thu, 23 Feb 2023 11:00:00 +0100</pubDate>
    <itunes:duration>3124</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:season>3</itunes:season>
    <itunes:episode>37</itunes:episode>
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  </item>
  <item>
    <itunes:title>36. The secrets of building an AI-ready culture with Noelle</itunes:title>
    <title>36. The secrets of building an AI-ready culture with Noelle</title>
    <itunes:summary><![CDATA[Noelle knows her stuff when it comes to implementing and scaling AI while, at the same time, keeping everyone content and on board. With experience leading teams at Microsoft, NPR and Amazon, she is well-versed in the day-to-day challenges of building an AI-ready culture and knows how to overcome them. She specializes in conversational AI, voice technology, intelligent apps, and responsible AI, working on creating innovative tech education programs. Tune in to learn her tips and tricks for bu...]]></itunes:summary>
    <description><![CDATA[<p><a href='https://noelle.ai/'>Noelle</a> knows her stuff when it comes to implementing and scaling AI while, at the same time, keeping everyone content and on board. With experience leading teams at Microsoft, NPR and Amazon, she is well-versed in the day-to-day challenges of building an AI-ready culture and knows how to overcome them. She specializes in conversational AI, voice technology, intelligent apps, and responsible AI, working on creating innovative tech education programs. Tune in to learn her tips and tricks for building AI teams and AI models with success! </p>]]></description>
    <content:encoded><![CDATA[<p><a href='https://noelle.ai/'>Noelle</a> knows her stuff when it comes to implementing and scaling AI while, at the same time, keeping everyone content and on board. With experience leading teams at Microsoft, NPR and Amazon, she is well-versed in the day-to-day challenges of building an AI-ready culture and knows how to overcome them. She specializes in conversational AI, voice technology, intelligent apps, and responsible AI, working on creating innovative tech education programs. Tune in to learn her tips and tricks for building AI teams and AI models with success! </p>]]></content:encoded>
    <enclosure url="https://www.buzzsprout.com/1614655/episodes/11535019-36-the-secrets-of-building-an-ai-ready-culture-with-noelle.mp3" length="36087494" type="audio/mpeg" />
    <itunes:image href="https://storage.buzzsprout.com/dj49t4fd3r8ilh3e5f44kh9xqmp6?.jpg" />
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    <pubDate>Thu, 20 Oct 2022 10:00:00 +0200</pubDate>
    <podcast:soundbite startTime="900.0" duration="41.5" />
    <itunes:duration>3004</itunes:duration>
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    <itunes:season>1</itunes:season>
    <itunes:episode>36</itunes:episode>
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  </item>
  <item>
    <itunes:title>35. Striking a balance - a conversation about privacy with Meta&#39;s Pedro Pavón</itunes:title>
    <title>35. Striking a balance - a conversation about privacy with Meta&#39;s Pedro Pavón</title>
    <itunes:summary><![CDATA[Pedro Pavón is the Global Policy Director responsible for monetization, privacy, and fairness at Meta. Pedro is a professor of law and a certified privacy professional who talked to us about the state of privacy and fairness. Meta has been the focus of attention for its role in society and the public discourse. Pedro sheds light on some of the challenges and solutions social media companies need to tackle to preserve privacy, facilitate research and mitigate impacts on democracy. ]]></itunes:summary>
    <description><![CDATA[<p>Pedro Pavón is the Global Policy Director responsible for monetization, privacy, and fairness at Meta. Pedro is a professor of law and a certified privacy professional who talked to us about the state of privacy and fairness. Meta has been the focus of attention for its role in society and the public discourse. Pedro sheds light on some of the challenges and solutions social media companies need to tackle to preserve privacy, facilitate research and mitigate impacts on democracy.</p>]]></description>
    <content:encoded><![CDATA[<p>Pedro Pavón is the Global Policy Director responsible for monetization, privacy, and fairness at Meta. Pedro is a professor of law and a certified privacy professional who talked to us about the state of privacy and fairness. Meta has been the focus of attention for its role in society and the public discourse. Pedro sheds light on some of the challenges and solutions social media companies need to tackle to preserve privacy, facilitate research and mitigate impacts on democracy.</p>]]></content:encoded>
    <enclosure url="https://www.buzzsprout.com/1614655/episodes/11365032-35-striking-a-balance-a-conversation-about-privacy-with-meta-s-pedro-pavon.mp3" length="37621799" type="audio/mpeg" />
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    <pubDate>Thu, 22 Sep 2022 10:00:00 +0200</pubDate>
    <itunes:duration>3128</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:season>1</itunes:season>
    <itunes:episode>35</itunes:episode>
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  <item>
    <itunes:title>34. AI ethics is science, not just philosophy - a practical guide with Reid Blackman</itunes:title>
    <title>34. AI ethics is science, not just philosophy - a practical guide with Reid Blackman</title>
    <itunes:summary><![CDATA[Author of a best-seller book for AI ethics, Ethical machines, Reid's mission is to educate business leaders about the practical reality of AI ethics. Business leaders need to understand ethics if they care about their brands. As Reid says, you can't math your way out of AI bias. Issues of ethics need to be addressed head-on, and those at the top must understand the nuances of operationalizing AI ethics and running AI systems to do so. Tune in to this episode of the Data Democratization Podcas...]]></itunes:summary>
    <description><![CDATA[<p>Author of a best-seller book for AI ethics, <a href='https://www.amazon.com/Ethical-Machines-Unbiased-Transparent-Respectful-ebook/dp/B09KNXTVLP'>Ethical machines</a>, Reid&apos;s mission is to educate business leaders about the practical reality of AI ethics. Business leaders need to understand ethics if they care about their brands. As Reid says, you can&apos;t math your way out of AI bias. Issues of ethics need to be addressed head-on, and those at the top must understand the nuances of operationalizing AI ethics and running AI systems to do so. Tune in to this episode of the Data Democratization Podcast to learn:</p><ul><li>why ethics is not a fuzzy topic and how to properly operationalize it,</li><li>why businesses should hire AI ethicists and why lawyers can&apos;t do the job of an ethicist,</li><li>how to think about AI ethics,</li><li>how to build an AI risk mitigation program,</li><li>what are the pitfalls and best practices for implementing AI ethics,</li><li>how to buy AI solutions and prepare procurement for the challenges of purchasing responsible AI products,</li><li>the difference between responsible AI, ethical AI, and trustworthy AI,</li><li>how to write an AI ethics statement that actually does its job,</li><li>what&apos;s the difference between global explainable AI (XAI) and local XAI</li></ul><p>Reid is a regularly published author at Harvard Business Review. If you would like to learn more about his work, read his article entitled <a href='https://hbr.org/2021/07/everyone-in-your-organization-needs-to-understand-ai-ethics'>Everyone in Your Organization Needs to Understand AI Ethics</a>.</p>]]></description>
    <content:encoded><![CDATA[<p>Author of a best-seller book for AI ethics, <a href='https://www.amazon.com/Ethical-Machines-Unbiased-Transparent-Respectful-ebook/dp/B09KNXTVLP'>Ethical machines</a>, Reid&apos;s mission is to educate business leaders about the practical reality of AI ethics. Business leaders need to understand ethics if they care about their brands. As Reid says, you can&apos;t math your way out of AI bias. Issues of ethics need to be addressed head-on, and those at the top must understand the nuances of operationalizing AI ethics and running AI systems to do so. Tune in to this episode of the Data Democratization Podcast to learn:</p><ul><li>why ethics is not a fuzzy topic and how to properly operationalize it,</li><li>why businesses should hire AI ethicists and why lawyers can&apos;t do the job of an ethicist,</li><li>how to think about AI ethics,</li><li>how to build an AI risk mitigation program,</li><li>what are the pitfalls and best practices for implementing AI ethics,</li><li>how to buy AI solutions and prepare procurement for the challenges of purchasing responsible AI products,</li><li>the difference between responsible AI, ethical AI, and trustworthy AI,</li><li>how to write an AI ethics statement that actually does its job,</li><li>what&apos;s the difference between global explainable AI (XAI) and local XAI</li></ul><p>Reid is a regularly published author at Harvard Business Review. If you would like to learn more about his work, read his article entitled <a href='https://hbr.org/2021/07/everyone-in-your-organization-needs-to-understand-ai-ethics'>Everyone in Your Organization Needs to Understand AI Ethics</a>.</p>]]></content:encoded>
    <enclosure url="https://www.buzzsprout.com/1614655/episodes/11041430-34-ai-ethics-is-science-not-just-philosophy-a-practical-guide-with-reid-blackman.mp3" length="63068641" type="audio/mpeg" />
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    <pubDate>Thu, 28 Jul 2022 10:00:00 +0200</pubDate>
    <itunes:duration>5251</itunes:duration>
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    <itunes:season>1</itunes:season>
    <itunes:episode>34</itunes:episode>
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  <item>
    <itunes:title>33. Fair synthetic data and ethical AI in healthcare with Humana</itunes:title>
    <title>33. Fair synthetic data and ethical AI in healthcare with Humana</title>
    <itunes:summary><![CDATA[The Data Democratization Podcast is back with an intriguing episode giving us a glimpse into the future of healthcare. Just like with any industry, AI is set to revolutionize how health insurers and healthcare service providers work. Improving patient outcomes is a great way to maximize the positive impact. However, the risks, as well as the opportunities are even greater when it comes to the health of millions of humans. Laura and Brent, two AI Ethics experts working at Humana, a large US he...]]></itunes:summary>
    <description><![CDATA[<p>The Data Democratization Podcast is back with an intriguing episode giving us a glimpse into the future of healthcare. Just like with any industry, AI is set to revolutionize how health insurers and healthcare service providers work. Improving patient outcomes is a great way to maximize the positive impact. However, the risks, as well as the opportunities are even greater when it comes to the health of millions of humans. Laura and Brent, two AI Ethics experts working at Humana, a large US health insurance company, are pioneers of their fields. For them, ethical AI, fairness and explainability are not just far-away buzz words, but everyday todo items with hands-on solutions. If you would like to learn more about how ethical AI gets done, listen to this episode and find out:</p><ul><li>How will AI revolutionize healthcare?</li><li>How to build AI ethics programs?</li><li>What is fairness in AI and what does synthetic data have to do with it?</li><li>How is fair synthetic data used to promote AI fairness?</li></ul><p>Meet Laura Mariano, Lead Ethical AI Data Scientist and Brent Sundheimer, Principal AI Architect from Humana and your host, Alexandra Ebert, Chief Trust Officer at MOSTLY AI,<a href='https://mostly.ai'> the world’s leading synthetic data company</a>! </p>]]></description>
    <content:encoded><![CDATA[<p>The Data Democratization Podcast is back with an intriguing episode giving us a glimpse into the future of healthcare. Just like with any industry, AI is set to revolutionize how health insurers and healthcare service providers work. Improving patient outcomes is a great way to maximize the positive impact. However, the risks, as well as the opportunities are even greater when it comes to the health of millions of humans. Laura and Brent, two AI Ethics experts working at Humana, a large US health insurance company, are pioneers of their fields. For them, ethical AI, fairness and explainability are not just far-away buzz words, but everyday todo items with hands-on solutions. If you would like to learn more about how ethical AI gets done, listen to this episode and find out:</p><ul><li>How will AI revolutionize healthcare?</li><li>How to build AI ethics programs?</li><li>What is fairness in AI and what does synthetic data have to do with it?</li><li>How is fair synthetic data used to promote AI fairness?</li></ul><p>Meet Laura Mariano, Lead Ethical AI Data Scientist and Brent Sundheimer, Principal AI Architect from Humana and your host, Alexandra Ebert, Chief Trust Officer at MOSTLY AI,<a href='https://mostly.ai'> the world’s leading synthetic data company</a>! </p>]]></content:encoded>
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    <pubDate>Thu, 07 Jul 2022 08:00:00 +0200</pubDate>
    <itunes:duration>3613</itunes:duration>
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    <itunes:season>1</itunes:season>
    <itunes:episode>33</itunes:episode>
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  <item>
    <itunes:title>32. A journey through the global data privacy landscape with Omer Tene</itunes:title>
    <title>32. A journey through the global data privacy landscape with Omer Tene</title>
    <itunes:summary><![CDATA[Omer Tene is a well-known data privacy expert, who led the International Association of Privacy Professionals for years. He has a deep and global understanding of data privacy legilsations as they stand in 2022 and has a pretty good grasp on the trends and about the way things are likely to evolve globally. Tune in to learn about the latest news on data privacy legislations and the hot topics of the day, including crypto, NFTs and the metaverse.  ]]></itunes:summary>
    <description><![CDATA[<p>Omer Tene is a well-known data privacy expert, who led the International Association of Privacy Professionals for years. He has a deep and global understanding of data privacy legilsations as they stand in 2022 and has a pretty good grasp on the trends and about the way things are likely to evolve globally. Tune in to learn about the latest news on data privacy legislations and the hot topics of the day, including crypto, NFTs and the metaverse. </p>]]></description>
    <content:encoded><![CDATA[<p>Omer Tene is a well-known data privacy expert, who led the International Association of Privacy Professionals for years. He has a deep and global understanding of data privacy legilsations as they stand in 2022 and has a pretty good grasp on the trends and about the way things are likely to evolve globally. Tune in to learn about the latest news on data privacy legislations and the hot topics of the day, including crypto, NFTs and the metaverse. </p>]]></content:encoded>
    <enclosure url="https://www.buzzsprout.com/1614655/episodes/10591371-32-a-journey-through-the-global-data-privacy-landscape-with-omer-tene.mp3" length="41101631" type="audio/mpeg" />
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    <pubDate>Tue, 10 May 2022 11:00:00 +0200</pubDate>
    <itunes:duration>3420</itunes:duration>
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    <itunes:season>1</itunes:season>
    <itunes:episode>32</itunes:episode>
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  <item>
    <itunes:title>31. How to get value out of PETs in banking with Ville Sointu</itunes:title>
    <title>31. How to get value out of PETs in banking with Ville Sointu</title>
    <itunes:summary><![CDATA[Ville Sointu is leading the Emerging Technologies team at one of Europe's biggest banks, Nordea. In this episode, he shares his advice and insights about adopting new technologies in famously conservative financial environments. Ville is also a host of the podcast entitled Fintech Daydreaming where he covers fintech topics with his guests from the financial sector.  ]]></itunes:summary>
    <description><![CDATA[<p>Ville Sointu is leading the Emerging Technologies team at one of Europe&apos;s biggest banks, Nordea. In this episode, he shares his advice and insights about adopting new technologies in famously conservative financial environments. Ville is also a host of the podcast entitled <a href='https://podcasts.apple.com/us/podcast/fintech-daydreaming/id1512431105'>Fintech Daydreaming</a> where he covers fintech topics with his guests from the financial sector. </p>]]></description>
    <content:encoded><![CDATA[<p>Ville Sointu is leading the Emerging Technologies team at one of Europe&apos;s biggest banks, Nordea. In this episode, he shares his advice and insights about adopting new technologies in famously conservative financial environments. Ville is also a host of the podcast entitled <a href='https://podcasts.apple.com/us/podcast/fintech-daydreaming/id1512431105'>Fintech Daydreaming</a> where he covers fintech topics with his guests from the financial sector. </p>]]></content:encoded>
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    <pubDate>Wed, 27 Apr 2022 16:00:00 +0200</pubDate>
    <itunes:duration>2958</itunes:duration>
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  <item>
    <itunes:title>30. From meaningless guarantees to strong data privacy with Yves-Alexandre de Montjoye</itunes:title>
    <title>30. From meaningless guarantees to strong data privacy with Yves-Alexandre de Montjoye</title>
    <itunes:summary><![CDATA[In this episode we talked to a prominent scientist from the data privacy field, Yves-Alexandre de Montjoye. He is an assistant professor at the Imperial College London, leading the Computational Privacy Group. A lot of fascinating privacy questions came up about behavioral data, k-anonymity, differential privacy and meaningless privacy guarantees that mask true risks. We talked about the way forward and how true data privacy can be created in practical terms. Tune in for an enlightening conve...]]></itunes:summary>
    <description><![CDATA[<p>In this episode we talked to a prominent scientist from the data privacy field, Yves-Alexandre de Montjoye. He is an assistant professor at the Imperial College London, leading the Computational Privacy Group. A lot of fascinating privacy questions came up about behavioral data, k-anonymity, differential privacy and meaningless privacy guarantees that mask true risks. We talked about the way forward and how true data privacy can be created in practical terms. Tune in for an enlightening conversation that puts a lot of greys into the seemingly black and white world of data privacy!   </p>]]></description>
    <content:encoded><![CDATA[<p>In this episode we talked to a prominent scientist from the data privacy field, Yves-Alexandre de Montjoye. He is an assistant professor at the Imperial College London, leading the Computational Privacy Group. A lot of fascinating privacy questions came up about behavioral data, k-anonymity, differential privacy and meaningless privacy guarantees that mask true risks. We talked about the way forward and how true data privacy can be created in practical terms. Tune in for an enlightening conversation that puts a lot of greys into the seemingly black and white world of data privacy!   </p>]]></content:encoded>
    <enclosure url="https://www.buzzsprout.com/1614655/episodes/10436814-30-from-meaningless-guarantees-to-strong-data-privacy-with-yves-alexandre-de-montjoye.mp3" length="47959464" type="audio/mpeg" />
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    <pubDate>Thu, 14 Apr 2022 09:00:00 +0200</pubDate>
    <itunes:duration>3991</itunes:duration>
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  <item>
    <itunes:title>29. Unpacking the Transatlantic Data Privacy Framework with Scott Marcus, Bruegel</itunes:title>
    <title>29. Unpacking the Transatlantic Data Privacy Framework with Scott Marcus, Bruegel</title>
    <itunes:summary><![CDATA[The recently announced Transatlantic Data Privacy Framework will foster data flows between the US and the EU, addressing the concerns raised by the Schrems II. decision. The US-made an unprecedented commitment to strengthen the privacy protection applicable to US signals intelligence activities within the new framework. New safeguards will be implemented to protect citizens' rights while advancing cross-border data flows. The next step is to translate this framework agreement into legal docum...]]></itunes:summary>
    <description><![CDATA[<p>The recently announced Transatlantic Data Privacy Framework will foster data flows between the US and the EU, addressing the concerns raised by the Schrems II. decision. The US-made an unprecedented commitment to strengthen the privacy protection applicable to US signals intelligence activities within the new framework. New safeguards will be implemented to protect citizens&apos; rights while advancing cross-border data flows. The next step is to translate this framework agreement into legal documents that will be put into practice on both sides of the Atlantic. But what does this mean for data privacy in practice? What are the major challenges, and what can we expect in the long run? We spoke to J. Scott Marcus, Senior Fellow at the EU&apos;s economic think tank, Bruegel, about the history and future of transatlantic data flows. <br/>Read on to learn <a href='https://mostly.ai/use-case/synthetic-data-sharing/'>how synthetic data can solve cross-border data sharing!</a></p>]]></description>
    <content:encoded><![CDATA[<p>The recently announced Transatlantic Data Privacy Framework will foster data flows between the US and the EU, addressing the concerns raised by the Schrems II. decision. The US-made an unprecedented commitment to strengthen the privacy protection applicable to US signals intelligence activities within the new framework. New safeguards will be implemented to protect citizens&apos; rights while advancing cross-border data flows. The next step is to translate this framework agreement into legal documents that will be put into practice on both sides of the Atlantic. But what does this mean for data privacy in practice? What are the major challenges, and what can we expect in the long run? We spoke to J. Scott Marcus, Senior Fellow at the EU&apos;s economic think tank, Bruegel, about the history and future of transatlantic data flows. <br/>Read on to learn <a href='https://mostly.ai/use-case/synthetic-data-sharing/'>how synthetic data can solve cross-border data sharing!</a></p>]]></content:encoded>
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    <pubDate>Tue, 29 Mar 2022 07:00:00 +0200</pubDate>
    <itunes:duration>3003</itunes:duration>
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    <itunes:episode>29</itunes:episode>
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  <item>
    <itunes:title>28. Data challenges in software testing with Maaret Pyhäjärvi</itunes:title>
    <title>28. Data challenges in software testing with Maaret Pyhäjärvi</title>
    <itunes:summary><![CDATA[We talked to an amazingly experienced and visionary test engineer to find out all about her challenges and inspirations. Alexandra and Maaret covered a lot of ground in the testing landscape, from everyday testing challenges to best practices and to visions of the future. According to Maaret, testing is about breaking illusions and we couldn't agree with her more. Testing is also like singing. Why? Tune in to find out!  ]]></itunes:summary>
    <description><![CDATA[<p>We talked to an amazingly experienced and visionary test engineer to find out all about her challenges and inspirations. Alexandra and Maaret covered a lot of ground in the testing landscape, from everyday testing challenges to best practices and to visions of the future. According to Maaret, testing is about breaking illusions and we couldn&apos;t agree with her more. Testing is also like singing. Why? Tune in to find out! </p>]]></description>
    <content:encoded><![CDATA[<p>We talked to an amazingly experienced and visionary test engineer to find out all about her challenges and inspirations. Alexandra and Maaret covered a lot of ground in the testing landscape, from everyday testing challenges to best practices and to visions of the future. According to Maaret, testing is about breaking illusions and we couldn&apos;t agree with her more. Testing is also like singing. Why? Tune in to find out! </p>]]></content:encoded>
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    <itunes:image href="https://storage.buzzsprout.com/7oacd6shwgt3yh90uy8ihijed3o9?.jpg" />
    <itunes:author>MOSTLY AI</itunes:author>
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    <pubDate>Wed, 09 Mar 2022 13:00:00 +0100</pubDate>
    <itunes:duration>2294</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:season>1</itunes:season>
    <itunes:episode>28</itunes:episode>
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  <item>
    <itunes:title>27. Stop relying on the Brussels Effect: On effective digital policymaking and negotiating transatlantic data flows with Andrea Renda, CEPS</itunes:title>
    <title>27. Stop relying on the Brussels Effect: On effective digital policymaking and negotiating transatlantic data flows with Andrea Renda, CEPS</title>
    <itunes:summary><![CDATA[What does it take to create effective digital policies? Why does the AI Act only go half-way - and what else needs to happen to ensure meaningful regulation of AI? How could the EU and the US overcome the challenges of negotiating transatlantic dataflows? And why should the EU might consider to stop relying on the Brussels Effect and instead get down on the negotiation table? Tune in to this conversation with Andrea Renda, a Senior Research Fellow at the Center for European Policy Studies (CE...]]></itunes:summary>
    <description><![CDATA[<p>What does it take to create effective digital policies? Why does the AI Act only go half-way - and what else needs to happen to ensure meaningful regulation of AI? How could the EU and the US overcome the challenges of negotiating transatlantic dataflows? And why should the EU might consider to stop relying on the Brussels Effect and instead get down on the negotiation table? Tune in to this conversation with Andrea Renda, a Senior Research Fellow at the Center for European Policy Studies (CEPS) and Advisor to the European Parliament, to learn more about the geopolitical battle on data, AI and digital policies.</p><p><br/></p>]]></description>
    <content:encoded><![CDATA[<p>What does it take to create effective digital policies? Why does the AI Act only go half-way - and what else needs to happen to ensure meaningful regulation of AI? How could the EU and the US overcome the challenges of negotiating transatlantic dataflows? And why should the EU might consider to stop relying on the Brussels Effect and instead get down on the negotiation table? Tune in to this conversation with Andrea Renda, a Senior Research Fellow at the Center for European Policy Studies (CEPS) and Advisor to the European Parliament, to learn more about the geopolitical battle on data, AI and digital policies.</p><p><br/></p>]]></content:encoded>
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    <pubDate>Thu, 24 Feb 2022 09:00:00 +0100</pubDate>
    <itunes:duration>3535</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:season>1</itunes:season>
    <itunes:episode>27</itunes:episode>
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  <item>
    <itunes:title>26. The synthetic data future with Tobi Hann, CEO of MOSTLY AI</itunes:title>
    <title>26. The synthetic data future with Tobi Hann, CEO of MOSTLY AI</title>
    <itunes:summary><![CDATA[What's synthetic data's future, and what's behind the synthetic data hype? This episode is all about synthetic data. We spoke to Tobi Hann, CEO of MOSTLY AI, the world's leading synthetic data company about the opportunities and challenges surrounding this important data tool. MOSTLY AI's recent Series B funding round is the biggest investment for synthetic data in Europe to date. What is synthetic data? It's an emerging privacy enhancing technology that enables privacy-preserving data usage,...]]></itunes:summary>
    <description><![CDATA[<p>What&apos;s synthetic data&apos;s future, and what&apos;s behind the synthetic data hype? This episode is all about synthetic data. We spoke to Tobi Hann, CEO of MOSTLY AI, the world&apos;s leading synthetic data company about the opportunities and challenges surrounding this important data tool. MOSTLY AI&apos;s recent Series B funding round is the biggest investment for synthetic data in Europe to date. <a href='https://mostly.ai/synthetic-data/'>What is synthetic data?</a> It&apos;s an emerging privacy enhancing technology that enables privacy-preserving data usage, improves machine learning models and allows realistic testing. In short: a data democratization tool. Listen in to find out all about why the future is synthetic. </p>]]></description>
    <content:encoded><![CDATA[<p>What&apos;s synthetic data&apos;s future, and what&apos;s behind the synthetic data hype? This episode is all about synthetic data. We spoke to Tobi Hann, CEO of MOSTLY AI, the world&apos;s leading synthetic data company about the opportunities and challenges surrounding this important data tool. MOSTLY AI&apos;s recent Series B funding round is the biggest investment for synthetic data in Europe to date. <a href='https://mostly.ai/synthetic-data/'>What is synthetic data?</a> It&apos;s an emerging privacy enhancing technology that enables privacy-preserving data usage, improves machine learning models and allows realistic testing. In short: a data democratization tool. Listen in to find out all about why the future is synthetic. </p>]]></content:encoded>
    <enclosure url="https://www.buzzsprout.com/1614655/episodes/10043088-26-the-synthetic-data-future-with-tobi-hann-ceo-of-mostly-ai.mp3" length="18978013" type="audio/mpeg" />
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    <pubDate>Wed, 09 Feb 2022 17:00:00 +0100</pubDate>
    <itunes:duration>1576</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:season>1</itunes:season>
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    <itunes:title>25. The end of AI ethics - a conversation about the EU&#39;s AI Act with Paul Nemitz, the godfather of GDPR</itunes:title>
    <title>25. The end of AI ethics - a conversation about the EU&#39;s AI Act with Paul Nemitz, the godfather of GDPR</title>
    <itunes:summary><![CDATA[To celebrate Data Privacy Day 2022, we talked to the godfather of GDPR, Paul Nemitz, about how bigtech threatens democracy, the role law can play in protecting people and societies from adverse effects of technology and why it's time to regulate AI. Tune in to learn more about the upcoming European AI act and find out what role synthetic data is likely to play in this regulated future!  ]]></itunes:summary>
    <description><![CDATA[<p>To celebrate Data Privacy Day 2022, we talked to the godfather of GDPR, Paul Nemitz, about how bigtech threatens democracy, the role law can play in protecting people and societies from adverse effects of technology and why it&apos;s time to regulate AI. Tune in to learn more about the upcoming European AI act and find out what role synthetic data is likely to play in this regulated future! </p>]]></description>
    <content:encoded><![CDATA[<p>To celebrate Data Privacy Day 2022, we talked to the godfather of GDPR, Paul Nemitz, about how bigtech threatens democracy, the role law can play in protecting people and societies from adverse effects of technology and why it&apos;s time to regulate AI. Tune in to learn more about the upcoming European AI act and find out what role synthetic data is likely to play in this regulated future! </p>]]></content:encoded>
    <enclosure url="https://www.buzzsprout.com/1614655/episodes/9955212-25-the-end-of-ai-ethics-a-conversation-about-the-eu-s-ai-act-with-paul-nemitz-the-godfather-of-gdpr.mp3" length="59445430" type="audio/mpeg" />
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    <pubDate>Wed, 26 Jan 2022 13:00:00 +0100</pubDate>
    <itunes:duration>4948</itunes:duration>
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    <itunes:season>1</itunes:season>
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    <itunes:title>24. The EU roadmap for AI with Axel Voss, MEP</itunes:title>
    <title>24. The EU roadmap for AI with Axel Voss, MEP</title>
    <itunes:summary><![CDATA[Axel Voss is  leading the Special Committee on Artificial Intelligence in the European Parliament. He's been working on a report outlining important policy recommendations for the upcoming European AI regulations. Among other things, Axel talked to us about: why the GDPR is due for an updatewhat the future of data protection holdshow the EU should compete globally in AI and digital innovationwhy access to high-quality data is so important how synthetic data can help bridge the gap b...]]></itunes:summary>
    <description><![CDATA[<p>Axel Voss is  leading the Special Committee on Artificial Intelligence in the European Parliament. He&apos;s been working on a report outlining important policy recommendations for the upcoming European AI regulations. Among other things, Axel talked to us about:</p><ul><li>why the GDPR is due for an update</li><li>what the future of data protection holds</li><li>how the EU should compete globally in AI and digital innovation</li><li>why access to high-quality data is so important </li><li>how synthetic data can help bridge the gap between data protection and data-driven innovations</li><li>what the upcoming European AI-regulation will look like</li></ul><p>If you would like to learn more about the legislative privacy landscape around GDPR and the upcoming AI regulations, listen to one of our previous conversations with Axel von dem Bussche, <a href='https://mostly.ai/data-democratization-podcast/gdpr-the-european-ai-regulation-and-the-privacy-landscape/'>GDPR, the new European AI regulation, and the privacy landscape. </a></p>]]></description>
    <content:encoded><![CDATA[<p>Axel Voss is  leading the Special Committee on Artificial Intelligence in the European Parliament. He&apos;s been working on a report outlining important policy recommendations for the upcoming European AI regulations. Among other things, Axel talked to us about:</p><ul><li>why the GDPR is due for an update</li><li>what the future of data protection holds</li><li>how the EU should compete globally in AI and digital innovation</li><li>why access to high-quality data is so important </li><li>how synthetic data can help bridge the gap between data protection and data-driven innovations</li><li>what the upcoming European AI-regulation will look like</li></ul><p>If you would like to learn more about the legislative privacy landscape around GDPR and the upcoming AI regulations, listen to one of our previous conversations with Axel von dem Bussche, <a href='https://mostly.ai/data-democratization-podcast/gdpr-the-european-ai-regulation-and-the-privacy-landscape/'>GDPR, the new European AI regulation, and the privacy landscape. </a></p>]]></content:encoded>
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    <pubDate>Thu, 13 Jan 2022 09:00:00 +0100</pubDate>
    <itunes:duration>3691</itunes:duration>
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    <itunes:title>23. Explainable AI with Denis Rothman, AI expert</itunes:title>
    <title>23. Explainable AI with Denis Rothman, AI expert</title>
    <itunes:summary><![CDATA[Denis Rothman has been an AI practitioner since the dawn of this technology. Denis shares his ideas on the origins of explainable AI, its necessity, the way forward for model agnostic explainable AI and the challenges of natural language processing.  ]]></itunes:summary>
    <description><![CDATA[<p>Denis Rothman has been an AI practitioner since the dawn of this technology. Denis shares his ideas on the origins of explainable AI, its necessity, the way forward for model agnostic explainable AI and the challenges of natural language processing. </p>]]></description>
    <content:encoded><![CDATA[<p>Denis Rothman has been an AI practitioner since the dawn of this technology. Denis shares his ideas on the origins of explainable AI, its necessity, the way forward for model agnostic explainable AI and the challenges of natural language processing. </p>]]></content:encoded>
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    <pubDate>Thu, 16 Dec 2021 16:00:00 +0100</pubDate>
    <itunes:duration>5101</itunes:duration>
    <itunes:keywords></itunes:keywords>
    <itunes:season>1</itunes:season>
    <itunes:episode>23</itunes:episode>
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    <itunes:title>22. The future of insurance with David Marock, insurtech and fintech expert</itunes:title>
    <title>22. The future of insurance with David Marock, insurtech and fintech expert</title>
    <itunes:summary><![CDATA[What does the future hold for the insurance industry? In the latest episode of the Data Democratization Podcast, our host, Alexandra Ebert talked to David Marock, a seasoned insurtech, fintech and proptech expert from London. David shared his insights on the state of AI in the insurance industry and what are the current trends developing in the insurtech space. In this episode you will hear about AI opportunities in insurance, why traditional insurance companies are tech hesitant, how to over...]]></itunes:summary>
    <description><![CDATA[<p><b>What does the future hold for the insurance industry? In the latest episode of the Data Democratization Podcast, our host, Alexandra Ebert talked to David Marock, a seasoned insurtech, fintech and proptech expert from London. David shared his insights on the state of AI in the insurance industry and what are the current trends developing in the insurtech space. In this episode you will hear about AI opportunities in insurance, why traditional insurance companies are tech hesitant, how to overcome the tech inertia in insurance organizations, how regulatory pressure is changing minds about digital transformation, why fairness is critical for insurance companies, how synthetic data solves data access and privacy issues, what to do about less tech-savvy business leaders and why the future of insurance will be driven by new technologies. </b></p><p><br/></p>]]></description>
    <content:encoded><![CDATA[<p><b>What does the future hold for the insurance industry? In the latest episode of the Data Democratization Podcast, our host, Alexandra Ebert talked to David Marock, a seasoned insurtech, fintech and proptech expert from London. David shared his insights on the state of AI in the insurance industry and what are the current trends developing in the insurtech space. In this episode you will hear about AI opportunities in insurance, why traditional insurance companies are tech hesitant, how to overcome the tech inertia in insurance organizations, how regulatory pressure is changing minds about digital transformation, why fairness is critical for insurance companies, how synthetic data solves data access and privacy issues, what to do about less tech-savvy business leaders and why the future of insurance will be driven by new technologies. </b></p><p><br/></p>]]></content:encoded>
    <enclosure url="https://www.buzzsprout.com/1614655/episodes/9730308-22-the-future-of-insurance-with-david-marock-insurtech-and-fintech-expert.mp3" length="56107501" type="audio/mpeg" />
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    <pubDate>Thu, 16 Dec 2021 09:00:00 +0100</pubDate>
    <itunes:duration>4670</itunes:duration>
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    <itunes:season>1</itunes:season>
    <itunes:episode>22</itunes:episode>
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    <itunes:title>21. Responsible AI by design with Maria Axente, PwC UK</itunes:title>
    <title>21. Responsible AI by design with Maria Axente, PwC UK</title>
    <itunes:summary><![CDATA[Take an organizational deep-dive into the topic of responsible AI with Maria Axente, PwC's Responsible AI lead! You'll hear lots of hands-on advice for decision makers looking to make their company's AI adoption a success from hiring decisions, organizational structures and the new AI mindset of pause and reflect.  ]]></itunes:summary>
    <description><![CDATA[<p>Take an organizational deep-dive into the topic of responsible AI with Maria Axente, PwC&apos;s Responsible AI lead! You&apos;ll hear lots of hands-on advice for decision makers looking to make their company&apos;s AI adoption a success from hiring decisions, organizational structures and the new AI mindset of pause and reflect. </p>]]></description>
    <content:encoded><![CDATA[<p>Take an organizational deep-dive into the topic of responsible AI with Maria Axente, PwC&apos;s Responsible AI lead! You&apos;ll hear lots of hands-on advice for decision makers looking to make their company&apos;s AI adoption a success from hiring decisions, organizational structures and the new AI mindset of pause and reflect. </p>]]></content:encoded>
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    <pubDate>Thu, 02 Dec 2021 09:00:00 +0100</pubDate>
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    <itunes:title>20. Ethically aligned design in AI with IEEE&#39;s Dr. Clara Neppel</itunes:title>
    <title>20. Ethically aligned design in AI with IEEE&#39;s Dr. Clara Neppel</title>
    <itunes:summary><![CDATA[Clara is a director at IEEE, the world's largest technical organization  founded by Tesla and Edison more than 100 years ago. Today, she is working on developing an ethically aligned design framework to help companies develop safe and effective AI systems. Listen to the 20th episode of the Data Democratization Podcast to find out what the difference is between standards and certifications, what the role of values is in ethically aligned design and what synthetic data and fresh Alpine spr...]]></itunes:summary>
    <description><![CDATA[<p>Clara is a director at IEEE, the world&apos;s largest technical organization  founded by Tesla and Edison more than 100 years ago. Today, she is working on developing an ethically aligned design framework to help companies develop safe and effective AI systems. Listen to the 20th episode of the Data Democratization Podcast to find out what the difference is between standards and certifications, what the role of values is in ethically aligned design and what synthetic data and fresh Alpine spring water have in common! </p>]]></description>
    <content:encoded><![CDATA[<p>Clara is a director at IEEE, the world&apos;s largest technical organization  founded by Tesla and Edison more than 100 years ago. Today, she is working on developing an ethically aligned design framework to help companies develop safe and effective AI systems. Listen to the 20th episode of the Data Democratization Podcast to find out what the difference is between standards and certifications, what the role of values is in ethically aligned design and what synthetic data and fresh Alpine spring water have in common! </p>]]></content:encoded>
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    <pubDate>Thu, 18 Nov 2021 08:00:00 +0100</pubDate>
    <itunes:duration>4097</itunes:duration>
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    <itunes:title>19. How to implement data privacy? A conversation with Klaudius Kalcher, cofounder and chief data scientist of MOSTLY AI</itunes:title>
    <title>19. How to implement data privacy? A conversation with Klaudius Kalcher, cofounder and chief data scientist of MOSTLY AI</title>
    <itunes:summary><![CDATA[In this episode, Alexandra Ebert, MOSTLY AI's chief trust officer will be talking to one of the founders and the chief data scientist of MOSTLY AI. If you are looking to get a behind-the-scenes view of how data privacy is implemented in practice, you are in the right place! You won't need a math Ph.D. to finally understand how privacy is measured and what is takes to protect personal data. Klaudius is also a huge fan of the concept of open data and talks about how synthetic data is the way fo...]]></itunes:summary>
    <description><![CDATA[<p>In this episode, Alexandra Ebert, MOSTLY AI&apos;s chief trust officer will be talking to one of the founders and the chief data scientist of MOSTLY AI. If you are looking to get a behind-the-scenes view of how data privacy is implemented in practice, you are in the right place! You won&apos;t need a math Ph.D. to finally understand how privacy is measured and what is takes to protect personal data. Klaudius is also a huge fan of the concept of open data and talks about how synthetic data is the way forward for realizing the potential of open data sharing for research and innovation. </p>]]></description>
    <content:encoded><![CDATA[<p>In this episode, Alexandra Ebert, MOSTLY AI&apos;s chief trust officer will be talking to one of the founders and the chief data scientist of MOSTLY AI. If you are looking to get a behind-the-scenes view of how data privacy is implemented in practice, you are in the right place! You won&apos;t need a math Ph.D. to finally understand how privacy is measured and what is takes to protect personal data. Klaudius is also a huge fan of the concept of open data and talks about how synthetic data is the way forward for realizing the potential of open data sharing for research and innovation. </p>]]></content:encoded>
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    <pubDate>Thu, 04 Nov 2021 09:00:00 +0100</pubDate>
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    <itunes:title>18. Data in action with Lisa Palmer from Splunk</itunes:title>
    <title>18. Data in action with Lisa Palmer from Splunk</title>
    <itunes:summary><![CDATA[Lisa Palmer is the chief technical advisor of Splunk, the popular data platform designed to remove barriers between data and action. Besides working for Splunk, she is a university professor, a podcast host, and an author. She spent years at Microsoft, Gartner, and Teradata, building up her unique perspective on data and technology-related business opportunities. In this episode, Lisa shares her most exciting insights and data stories around tackling real-life problems with data, including wi...]]></itunes:summary>
    <description><![CDATA[<p>Lisa Palmer is the chief technical advisor of Splunk, the popular data platform designed to remove barriers between data and action. Besides working for Splunk, she is a university professor, a podcast host, and an author. She spent years at Microsoft, Gartner, and Teradata, building up her unique perspective on data and technology-related business opportunities. In this episode, Lisa shares her most exciting insights and data stories around tackling real-life problems with data, including wildfires and F1 racing, how privacy-enhancing technologies like homomorphic encryption and synthetic data can be used for social good, why we need truly complete datasets to address biases, the role synthetic data plays in ethical AI and bias mitigation, how to increase diversity, especially in tech and how to think about data opportunities in times of disruption and opportunity. <br/>Check out the transcript for this episode and all previous episodes of the Data Democratization Podcast at <a href='https://mostly.ai/data-democratization-podcasts/'>our website! </a></p>]]></description>
    <content:encoded><![CDATA[<p>Lisa Palmer is the chief technical advisor of Splunk, the popular data platform designed to remove barriers between data and action. Besides working for Splunk, she is a university professor, a podcast host, and an author. She spent years at Microsoft, Gartner, and Teradata, building up her unique perspective on data and technology-related business opportunities. In this episode, Lisa shares her most exciting insights and data stories around tackling real-life problems with data, including wildfires and F1 racing, how privacy-enhancing technologies like homomorphic encryption and synthetic data can be used for social good, why we need truly complete datasets to address biases, the role synthetic data plays in ethical AI and bias mitigation, how to increase diversity, especially in tech and how to think about data opportunities in times of disruption and opportunity. <br/>Check out the transcript for this episode and all previous episodes of the Data Democratization Podcast at <a href='https://mostly.ai/data-democratization-podcasts/'>our website! </a></p>]]></content:encoded>
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    <pubDate>Wed, 13 Oct 2021 09:00:00 +0200</pubDate>
    <itunes:duration>3220</itunes:duration>
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  <item>
    <itunes:title>17. Synthetic data engineering in insurance and banking</itunes:title>
    <title>17. Synthetic data engineering in insurance and banking</title>
    <itunes:summary><![CDATA[In the latest episode of the Data Democratization Podcast, Jim Hu, MOSTLY AI's Data Engineer, talks about the most exciting synthetic data engineering he has been busy doing. Synthetic data is quickly becoming a must-have engineering tool across industries, with new use cases emerging every day. If you want to learn how to leverage synthetic data in insurance and banking, listen to the episode! Learn to maximize synthetic data's business impact: how to increase profit margins in insurance usi...]]></itunes:summary>
    <description><![CDATA[<p>In the latest episode of the Data Democratization Podcast, Jim Hu, MOSTLY AI&apos;s Data Engineer, talks about the most exciting synthetic data engineering he has been busy doing. Synthetic data is quickly becoming a must-have engineering tool across industries, with new use cases emerging every day. If you want to learn how to leverage synthetic data in insurance and banking, listen to the episode! Learn to maximize synthetic data&apos;s business impact:</p><ul><li>how to increase profit margins in insurance using synthetic data</li><li>how to maximize the lifetime revenue of a loan</li><li>how to detect suspicious transactions and prevent fraud</li><li>how to estimate credit risk using machine learning</li><li>how to unlock transaction data for AI training</li><li>why synthetic data is superior to legacy data anonymization techniques</li><li>optimize software testing processes</li><li>create personalized banking experiences</li></ul>]]></description>
    <content:encoded><![CDATA[<p>In the latest episode of the Data Democratization Podcast, Jim Hu, MOSTLY AI&apos;s Data Engineer, talks about the most exciting synthetic data engineering he has been busy doing. Synthetic data is quickly becoming a must-have engineering tool across industries, with new use cases emerging every day. If you want to learn how to leverage synthetic data in insurance and banking, listen to the episode! Learn to maximize synthetic data&apos;s business impact:</p><ul><li>how to increase profit margins in insurance using synthetic data</li><li>how to maximize the lifetime revenue of a loan</li><li>how to detect suspicious transactions and prevent fraud</li><li>how to estimate credit risk using machine learning</li><li>how to unlock transaction data for AI training</li><li>why synthetic data is superior to legacy data anonymization techniques</li><li>optimize software testing processes</li><li>create personalized banking experiences</li></ul>]]></content:encoded>
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    <pubDate>Wed, 29 Sep 2021 16:00:00 +0200</pubDate>
    <itunes:duration>2768</itunes:duration>
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    <itunes:title>16. The cybersecurity perspective: TD Bank&#39;s Claudette McGowan</itunes:title>
    <title>16. The cybersecurity perspective: TD Bank&#39;s Claudette McGowan</title>
    <itunes:summary><![CDATA[Claudette McGowan is an award-winning technology leader with a real passion for cybersecurity. In this episode of the Data Democratization Podcast, she shares her personal journey to the cybersecurity field as well as her perspective on the current state of cybersecurity. Listen to the episode to learn more about how the pandemic changed the threat landscape, how companies should prepare for cyberattacks, how data should be managed for maximum security, what is a zero-trust approach, the impo...]]></itunes:summary>
    <description><![CDATA[<p>Claudette McGowan is an award-winning technology leader with a real passion for cybersecurity. In this episode of the Data Democratization Podcast, she shares her personal journey to the cybersecurity field as well as her perspective on the current state of cybersecurity. Listen to the episode to learn more about how the pandemic changed the threat landscape, how companies should prepare for cyberattacks, how data should be managed for maximum security, what is a zero-trust approach, the importance of privacy-safe data sharing, why data literacy is important, why cybersecurity is an amazing career option and where you can learn about cybersecurity. Also, don&apos;t forget to check out Claudette&apos;s podcast, the <a href='https://www.youtube.com/globalcsuite'>Cyber Suite</a>, to elevate your everyday cyber literacy!  </p>]]></description>
    <content:encoded><![CDATA[<p>Claudette McGowan is an award-winning technology leader with a real passion for cybersecurity. In this episode of the Data Democratization Podcast, she shares her personal journey to the cybersecurity field as well as her perspective on the current state of cybersecurity. Listen to the episode to learn more about how the pandemic changed the threat landscape, how companies should prepare for cyberattacks, how data should be managed for maximum security, what is a zero-trust approach, the importance of privacy-safe data sharing, why data literacy is important, why cybersecurity is an amazing career option and where you can learn about cybersecurity. Also, don&apos;t forget to check out Claudette&apos;s podcast, the <a href='https://www.youtube.com/globalcsuite'>Cyber Suite</a>, to elevate your everyday cyber literacy!  </p>]]></content:encoded>
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    <pubDate>Mon, 13 Sep 2021 10:00:00 +0200</pubDate>
    <itunes:duration>1882</itunes:duration>
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    <itunes:title>15. Data best practices with Scott Taylor, the Data Whisperer</itunes:title>
    <title>15. Data best practices with Scott Taylor, the Data Whisperer</title>
    <itunes:summary><![CDATA[Scott, the Data Whisperer, knows a thing or two about proper data management. If you are in the business of making large scale data projects happen, make sure you listen to this episode and learn about creating visibility and getting executive buy-in for your data projects. Find out how to set your data projects up for success from the beginning through master data, metadata, data governance and data stewardship and get great tips on how to tell great data stories.  ]]></itunes:summary>
    <description><![CDATA[<p>Scott, the Data Whisperer, knows a thing or two about proper data management. If you are in the business of making large scale data projects happen, make sure you listen to this episode and learn about creating visibility and getting executive buy-in for your data projects. Find out how to set your data projects up for success from the beginning through master data, metadata, data governance and data stewardship and get great tips on how to tell great data stories. </p>]]></description>
    <content:encoded><![CDATA[<p>Scott, the Data Whisperer, knows a thing or two about proper data management. If you are in the business of making large scale data projects happen, make sure you listen to this episode and learn about creating visibility and getting executive buy-in for your data projects. Find out how to set your data projects up for success from the beginning through master data, metadata, data governance and data stewardship and get great tips on how to tell great data stories. </p>]]></content:encoded>
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    <pubDate>Mon, 23 Aug 2021 13:00:00 +0200</pubDate>
    <itunes:duration>2936</itunes:duration>
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    <itunes:title>14. Privacy blindspots in banking with Amir Tabakovic, Mobey Forum</itunes:title>
    <title>14. Privacy blindspots in banking with Amir Tabakovic, Mobey Forum</title>
    <itunes:summary><![CDATA[Amir Tabakovic has lots of experience in developing banking products, and as a chairman of the AI and Data Privacy Experts Group at Mobey Forum, he has a very good overview of privacy best practices and the most common mistakes in the banking industry. Listen to this episode to learn about how to develop customer-centric banking products and take them to market? How can traditional banks compete with neobanks?  What is privacy-enhancing technology? How should banks leverage privacy tech ...]]></itunes:summary>
    <description><![CDATA[<p>Amir Tabakovic has lots of experience in developing banking products, and as a chairman of the AI and Data Privacy Experts Group at Mobey Forum, he has a very good overview of privacy best practices and the most common mistakes in the banking industry. Listen to this episode to learn about how to develop customer-centric banking products and take them to market? How can traditional banks compete with neobanks?  What is privacy-enhancing technology? How should banks leverage privacy tech for success? Which privacy technology to choose when? How to make privacy-by-design happen from an organizational point of view? What is the difference between pseudonymization and anonymization? What&apos;s the problem with legacy anonymization technologies? <br/><br/>Amir and his team at Mobey Forum recently published a report entitled The Digital Banking Blindspot: Emerging Privacy Enhancing Technologies. <a href='https://mobeyforum.org/the-digital-banking-blindspot/'>Download the report</a> if you would like to get a detailed overview of how privacy tech is changing the banking industry!<br/><br/>To learn more about synthetic data, visit MOSTLY AI&apos;s <a href='https://mostly.ai/synthetic-data-blog/'>Synthetic Data Blog</a>! <br/><br/></p>]]></description>
    <content:encoded><![CDATA[<p>Amir Tabakovic has lots of experience in developing banking products, and as a chairman of the AI and Data Privacy Experts Group at Mobey Forum, he has a very good overview of privacy best practices and the most common mistakes in the banking industry. Listen to this episode to learn about how to develop customer-centric banking products and take them to market? How can traditional banks compete with neobanks?  What is privacy-enhancing technology? How should banks leverage privacy tech for success? Which privacy technology to choose when? How to make privacy-by-design happen from an organizational point of view? What is the difference between pseudonymization and anonymization? What&apos;s the problem with legacy anonymization technologies? <br/><br/>Amir and his team at Mobey Forum recently published a report entitled The Digital Banking Blindspot: Emerging Privacy Enhancing Technologies. <a href='https://mobeyforum.org/the-digital-banking-blindspot/'>Download the report</a> if you would like to get a detailed overview of how privacy tech is changing the banking industry!<br/><br/>To learn more about synthetic data, visit MOSTLY AI&apos;s <a href='https://mostly.ai/synthetic-data-blog/'>Synthetic Data Blog</a>! <br/><br/></p>]]></content:encoded>
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    <pubDate>Wed, 11 Aug 2021 17:00:00 +0200</pubDate>
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    <itunes:title>13. Behrang Raji on the regulatory challenges of ethical AI, fairness and data anonymization</itunes:title>
    <title>13. Behrang Raji on the regulatory challenges of ethical AI, fairness and data anonymization</title>
    <itunes:summary><![CDATA[Behrang Raji is a data privacy officer for the Hamburg Commissioner for Data Protection and Freedom of Information. He is right where legislation happens, knows what drives regulators and has a pretty good understanding of trends and the larger regulatory landscape. Listen to this episode if you are curious about the upcoming European AI regulations, fairness in law and how synthetic data helps fix biases and test AI systems, the most common data anonymization mistakes, data anonymization sta...]]></itunes:summary>
    <description><![CDATA[<p>Behrang Raji is a data privacy officer for the Hamburg Commissioner for Data Protection and Freedom of Information. He is right where legislation happens, knows what drives regulators and has a pretty good understanding of trends and the larger regulatory landscape. Listen to this episode if you are curious about the upcoming European AI regulations, fairness in law and how synthetic data helps fix biases and test AI systems, the most common data anonymization mistakes, data anonymization standards and compliance strategies that really work. </p>]]></description>
    <content:encoded><![CDATA[<p>Behrang Raji is a data privacy officer for the Hamburg Commissioner for Data Protection and Freedom of Information. He is right where legislation happens, knows what drives regulators and has a pretty good understanding of trends and the larger regulatory landscape. Listen to this episode if you are curious about the upcoming European AI regulations, fairness in law and how synthetic data helps fix biases and test AI systems, the most common data anonymization mistakes, data anonymization standards and compliance strategies that really work. </p>]]></content:encoded>
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    <pubDate>Wed, 28 Jul 2021 09:00:00 +0200</pubDate>
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    <itunes:duration>3311</itunes:duration>
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    <itunes:title>12. Accelerating data science in finance and insurance with Jochen Papenbrock, NVIDIA</itunes:title>
    <title>12. Accelerating data science in finance and insurance with Jochen Papenbrock, NVIDIA</title>
    <itunes:summary><![CDATA[NVIDIA is famous for its graphics cards, but NVIDIA's story is so much bigger than this. Their graphics cards have been used to accelerate AI and data science, and now they offer a whole ecosystem of services and tools for companies ready to make AI happen. Listen to the episode to learn about the top AI use cases in finance and insurance and how to make those happen. Questions you will get answers for in this episode: How to implement AI successfully? How does NVIDIA help democratize AI? How...]]></itunes:summary>
    <description><![CDATA[<p>NVIDIA is famous for its graphics cards, but NVIDIA&apos;s story is so much bigger than this. Their graphics cards have been used to accelerate AI and data science, and now they offer a whole ecosystem of services and tools for companies ready to make AI happen. Listen to the episode to learn about the top AI use cases in finance and insurance and how to make those happen. Questions you will get answers for in this episode: How to implement AI successfully? How does NVIDIA help democratize AI? How to automate explainability? How is synthetic data used for evaluating and supervising AI models? What does the future of AI hold for financial institutions? </p>]]></description>
    <content:encoded><![CDATA[<p>NVIDIA is famous for its graphics cards, but NVIDIA&apos;s story is so much bigger than this. Their graphics cards have been used to accelerate AI and data science, and now they offer a whole ecosystem of services and tools for companies ready to make AI happen. Listen to the episode to learn about the top AI use cases in finance and insurance and how to make those happen. Questions you will get answers for in this episode: How to implement AI successfully? How does NVIDIA help democratize AI? How to automate explainability? How is synthetic data used for evaluating and supervising AI models? What does the future of AI hold for financial institutions? </p>]]></content:encoded>
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    <pubDate>Tue, 13 Jul 2021 12:00:00 +0200</pubDate>
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    <itunes:duration>3346</itunes:duration>
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    <itunes:title>11. Hands-on ethical AI with Nancy Nemes, former global leader at Microsoft and Google, the founder of HumanAIze</itunes:title>
    <title>11. Hands-on ethical AI with Nancy Nemes, former global leader at Microsoft and Google, the founder of HumanAIze</title>
    <itunes:summary><![CDATA[Nancy Nemes is an AI expert with 20 years of hand-on experience in implementing frameworks as a leader at Microsoft and Google. She is the founder of HumanAIze, an organization that aims to make AI more inclusive. If you are looking for some practical advice on how to implement responsible AI at the moment, then look no more – In this episode you will learn about all the necessary steps to perform ethical AI. What are the most important ethical AI best practices? What does the regulation aspe...]]></itunes:summary>
    <description><![CDATA[<p>Nancy Nemes is an AI expert with 20 years of hand-on experience in implementing frameworks as a leader at Microsoft and Google. She is the founder of HumanAIze, an organization that aims to make AI more inclusive. If you are looking for some practical advice on how to implement responsible AI at the moment, then look no more – In this episode you will learn about all the necessary steps to perform ethical AI. What are the most important ethical AI best practices? What does the regulation aspect mean for the financial sector? What kind of skills are necessary to adapt to this AI-driven environment? How to identify the right metrics for understanding privacy and fairness when developing AI systems? Which kind of privacy enhancing technologies should you implement? Who are the experts that you should gather? Learn the answers to these by following the best, expert, practices!</p>]]></description>
    <content:encoded><![CDATA[<p>Nancy Nemes is an AI expert with 20 years of hand-on experience in implementing frameworks as a leader at Microsoft and Google. She is the founder of HumanAIze, an organization that aims to make AI more inclusive. If you are looking for some practical advice on how to implement responsible AI at the moment, then look no more – In this episode you will learn about all the necessary steps to perform ethical AI. What are the most important ethical AI best practices? What does the regulation aspect mean for the financial sector? What kind of skills are necessary to adapt to this AI-driven environment? How to identify the right metrics for understanding privacy and fairness when developing AI systems? Which kind of privacy enhancing technologies should you implement? Who are the experts that you should gather? Learn the answers to these by following the best, expert, practices!</p>]]></content:encoded>
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    <itunes:author>MOSTLY AI</itunes:author>
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    <pubDate>Wed, 30 Jun 2021 15:00:00 +0200</pubDate>
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    <itunes:duration>2759</itunes:duration>
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  <item>
    <itunes:title>10. Data ethics best practices from Nicolas Passadelis, Head of Data Governance at Swisscom</itunes:title>
    <title>10. Data ethics best practices from Nicolas Passadelis, Head of Data Governance at Swisscom</title>
    <itunes:summary><![CDATA[Nicolas Passadelis is a lawyer and privacy expert who has been leading the Data Governance team at Swisscom for over four years. In this episode of the Data Democratization Podcast, Nicolas shares his best practices of data governance and provides real-life examples of how Swisscom's data ethics board works. The episode contains an amazing collection of actionable takeaways and great answers to the big questions of data governance. For example, how to implement data governance in an enterpris...]]></itunes:summary>
    <description><![CDATA[<p>Nicolas Passadelis is a lawyer and privacy expert who has been leading the Data Governance team at Swisscom for over four years. In this episode of the Data Democratization Podcast, Nicolas shares his best practices of data governance and provides real-life examples of how Swisscom&apos;s data ethics board works. The episode contains an amazing collection of actionable takeaways and great answers to the big questions of data governance. For example, how to implement data governance in an enterprise setting successfully? How to automate and scale compliance? How to self-assess your data protection practices? What is data ethics? How to create a data ethics framework? How to create a data ethics board? What are the six ethics principles for assessment at Swisscom? Listen to the episode and reach out to us with your own solutions to these questions by sending a voice recording to podcast@mostly.ai! <br/><a href='https://mostly.ai/2021/06/18/data-ethics-nicolas-passadelis-swisscom/'>Read the transcript! </a></p>]]></description>
    <content:encoded><![CDATA[<p>Nicolas Passadelis is a lawyer and privacy expert who has been leading the Data Governance team at Swisscom for over four years. In this episode of the Data Democratization Podcast, Nicolas shares his best practices of data governance and provides real-life examples of how Swisscom&apos;s data ethics board works. The episode contains an amazing collection of actionable takeaways and great answers to the big questions of data governance. For example, how to implement data governance in an enterprise setting successfully? How to automate and scale compliance? How to self-assess your data protection practices? What is data ethics? How to create a data ethics framework? How to create a data ethics board? What are the six ethics principles for assessment at Swisscom? Listen to the episode and reach out to us with your own solutions to these questions by sending a voice recording to podcast@mostly.ai! <br/><a href='https://mostly.ai/2021/06/18/data-ethics-nicolas-passadelis-swisscom/'>Read the transcript! </a></p>]]></content:encoded>
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    <itunes:author>MOSTLY AI</itunes:author>
    <guid isPermaLink="false">Buzzsprout-8712981</guid>
    <pubDate>Wed, 16 Jun 2021 16:00:00 +0200</pubDate>
    <podcast:transcript url="https://www.buzzsprout.com/1614655/8712981/transcript" type="text/html" />
    <itunes:duration>4165</itunes:duration>
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  <item>
    <itunes:title>9. Fair synthetic data and ethical algorithms: the fairness conversation with Paul Tiwald, Head of Data Science at MOSTLY AI</itunes:title>
    <title>9. Fair synthetic data and ethical algorithms: the fairness conversation with Paul Tiwald, Head of Data Science at MOSTLY AI</title>
    <itunes:summary><![CDATA[Paul Tiwald has been part of the MOSTLY AI team since the beginning. He is the mastermind behind the team's research into fairness and the idea of fair synthetic data.  In this episode, you will hear about:  what it's like to work in the field of artificial intelligence (spoiler: it's really fun!)how the idea of fair synthetic data came uphow to create machine learning models that are private and fair by designwhy is it so challenging to remove bias from an algorithmwhat are proxy v...]]></itunes:summary>
    <description><![CDATA[<p>Paul Tiwald has been part of the MOSTLY AI team since the beginning. He is the mastermind behind the team&apos;s research into fairness and the idea of fair synthetic data. </p><p>In this episode, you will hear about: </p><ul><li>what it&apos;s like to work in the field of artificial intelligence (spoiler: it&apos;s really fun!)</li><li>how the idea of fair synthetic data came up</li><li>how to create machine learning models that are private and fair by design</li><li>why is it so challenging to remove bias from an algorithm</li><li>what are proxy variables, and why are they dangerous</li><li>what is the definition of fairness, and why do we need one in the first place</li><li>how should companies start implementing fairness and ethical approaches into their AI development</li><li>why it&apos;s impossible to fix bias without fair synthetic data and algorithmic fairness</li></ul>]]></description>
    <content:encoded><![CDATA[<p>Paul Tiwald has been part of the MOSTLY AI team since the beginning. He is the mastermind behind the team&apos;s research into fairness and the idea of fair synthetic data. </p><p>In this episode, you will hear about: </p><ul><li>what it&apos;s like to work in the field of artificial intelligence (spoiler: it&apos;s really fun!)</li><li>how the idea of fair synthetic data came up</li><li>how to create machine learning models that are private and fair by design</li><li>why is it so challenging to remove bias from an algorithm</li><li>what are proxy variables, and why are they dangerous</li><li>what is the definition of fairness, and why do we need one in the first place</li><li>how should companies start implementing fairness and ethical approaches into their AI development</li><li>why it&apos;s impossible to fix bias without fair synthetic data and algorithmic fairness</li></ul>]]></content:encoded>
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    <itunes:author>MOSTLY AI</itunes:author>
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    <pubDate>Wed, 02 Jun 2021 12:00:00 +0200</pubDate>
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    <itunes:duration>1606</itunes:duration>
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    <itunes:title>8. GDPR, the new European AI regulation, and the privacy landscape: Axel von dem Bussche data lawyer from Taylor Wessing</itunes:title>
    <title>8. GDPR, the new European AI regulation, and the privacy landscape: Axel von dem Bussche data lawyer from Taylor Wessing</title>
    <itunes:summary><![CDATA[We talked to one of Europe's most renowned GDPR and data experts, who shared his insights about the regulatory landscape in Europe and elsewhere and gave excellent advice for lawmakers and companies.  In this episode, you will hear more about: recent regulatory developments, including Schrems II, GDPR, and the new AI-regulation proposal from the European Court of Justicewhy regulation is necessary and timely for AIwhat companies should do in light of these recent developmentshow, accordi...]]></itunes:summary>
    <description><![CDATA[<p>We talked to one of Europe&apos;s most renowned GDPR and data experts, who shared his insights about the regulatory landscape in Europe and elsewhere and gave excellent advice for lawmakers and companies. </p><p>In this episode, you will hear more about:</p><ul><li>recent regulatory developments, including Schrems II, GDPR, and the new AI-regulation proposal from the European Court of Justice</li><li>why regulation is necessary and timely for AI</li><li>what companies should do in light of these recent developments</li><li>how, according to Axel&apos;s prediction, we&apos;ll end up with 20 GDPR-like laws</li><li>how to make regulation less complex and easier to comply with</li><li>how to develop a successful data strategy and to turn data privacy into a competitive edge through know-how, proactivity, and risk assessments </li><li>why 95% of data transfers became illegal after Schrems II and that companies need to map all of their cross-border data transfers to comply with regulations</li><li>how synthetic data can help, since it&apos;s exempt from GDPR and Schrems II</li></ul>]]></description>
    <content:encoded><![CDATA[<p>We talked to one of Europe&apos;s most renowned GDPR and data experts, who shared his insights about the regulatory landscape in Europe and elsewhere and gave excellent advice for lawmakers and companies. </p><p>In this episode, you will hear more about:</p><ul><li>recent regulatory developments, including Schrems II, GDPR, and the new AI-regulation proposal from the European Court of Justice</li><li>why regulation is necessary and timely for AI</li><li>what companies should do in light of these recent developments</li><li>how, according to Axel&apos;s prediction, we&apos;ll end up with 20 GDPR-like laws</li><li>how to make regulation less complex and easier to comply with</li><li>how to develop a successful data strategy and to turn data privacy into a competitive edge through know-how, proactivity, and risk assessments </li><li>why 95% of data transfers became illegal after Schrems II and that companies need to map all of their cross-border data transfers to comply with regulations</li><li>how synthetic data can help, since it&apos;s exempt from GDPR and Schrems II</li></ul>]]></content:encoded>
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    <itunes:author>MOSTLY AI</itunes:author>
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    <pubDate>Wed, 19 May 2021 18:00:00 +0200</pubDate>
    <itunes:duration>3828</itunes:duration>
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    <itunes:title>The frontline CISO&#39;s perspective on the opioid crisis, the pandemic and the ICU: John Frushour from the New York-Presbyterian Hospital  </itunes:title>
    <title>The frontline CISO&#39;s perspective on the opioid crisis, the pandemic and the ICU: John Frushour from the New York-Presbyterian Hospital  </title>
    <itunes:summary><![CDATA[In this action-packed episode, John Frushour, Deputy Chief Information Security Officer at New York-Presbyterian Hospital, shares his best frontline data stories. And data stories don't get any more frontline than his. From fighting the opioid crisis to the COVID-19 emergency in New York, John and his team accomplished superhuman achievements with data.    In this episode, you will hear more about: the most useful leadership, data, and technical skills for CISOshow DevOps teams operate a...]]></itunes:summary>
    <description><![CDATA[<p>In this action-packed episode, John Frushour, Deputy Chief Information Security Officer at New York-Presbyterian Hospital, shares his best frontline data stories. And data stories don&apos;t get any more frontline than his. From fighting the opioid crisis to the COVID-19 emergency in New York, John and his team accomplished superhuman achievements with data. </p><p><br/></p><p>In this episode, you will hear more about:</p><ul><li>the most useful leadership, data, and technical skills for CISOs</li><li>how DevOps teams operate and how they mature with data science and automation</li><li>balancing data protection with data access in a healthcare setting</li><li>advanced analytics use cases: tracking opioids and sensor data in the ICU</li><li>the COVID-19 challenge in New York 2020 from a CISOs perspective</li><li>using synthetic data for AI/ML</li><li>AI and data regulations from a CISO&apos;s perspective in 2021</li><li>how to increase diversity in cybersecurity teams</li><li>tips for keeping your data safe and secure and for finding the best tequila in town</li></ul>]]></description>
    <content:encoded><![CDATA[<p>In this action-packed episode, John Frushour, Deputy Chief Information Security Officer at New York-Presbyterian Hospital, shares his best frontline data stories. And data stories don&apos;t get any more frontline than his. From fighting the opioid crisis to the COVID-19 emergency in New York, John and his team accomplished superhuman achievements with data. </p><p><br/></p><p>In this episode, you will hear more about:</p><ul><li>the most useful leadership, data, and technical skills for CISOs</li><li>how DevOps teams operate and how they mature with data science and automation</li><li>balancing data protection with data access in a healthcare setting</li><li>advanced analytics use cases: tracking opioids and sensor data in the ICU</li><li>the COVID-19 challenge in New York 2020 from a CISOs perspective</li><li>using synthetic data for AI/ML</li><li>AI and data regulations from a CISO&apos;s perspective in 2021</li><li>how to increase diversity in cybersecurity teams</li><li>tips for keeping your data safe and secure and for finding the best tequila in town</li></ul>]]></content:encoded>
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    <itunes:author>MOSTLY AI</itunes:author>
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    <pubDate>Wed, 05 May 2021 11:00:00 +0200</pubDate>
    <itunes:duration>5057</itunes:duration>
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    <itunes:title>6. Data-driven product development with Ryan McCabe, Senior Data Scientist at Spotify, Stockholm</itunes:title>
    <title>6. Data-driven product development with Ryan McCabe, Senior Data Scientist at Spotify, Stockholm</title>
    <itunes:summary><![CDATA[Ryan is a Senior Data Scientist at Spotify with extensive experience in developing great customer-centric products with the power of data. He is a data consultant and university lecturer, passionate about data science and understanding the business side of things. In this episode you will hear about: How to start building data infrastructure in your organization, no matter the size.How to embed data best practices in your team and how to get the most value out of data science.Actionable advic...]]></itunes:summary>
    <description><![CDATA[<p>Ryan is a Senior Data Scientist at Spotify with extensive experience in developing great<br/>customer-centric products with the power of data. He is a data consultant and university<br/>lecturer, passionate about data science and understanding the business side of things.<br/>In this episode you will hear about:</p><ul><li>How to start building data infrastructure in your organization, no matter the size.</li><li>How to embed data best practices in your team and how to get the most value out of data science.</li><li>Actionable advice on how to scale machine learning in your organization through making data accessible and automating data access processes.</li><li>Data protection is a true differentiator in today’s market. You don’t need to use<br/>personal data for data science and fake users are better than real ones for testing your<br/>ideas.</li></ul>]]></description>
    <content:encoded><![CDATA[<p>Ryan is a Senior Data Scientist at Spotify with extensive experience in developing great<br/>customer-centric products with the power of data. He is a data consultant and university<br/>lecturer, passionate about data science and understanding the business side of things.<br/>In this episode you will hear about:</p><ul><li>How to start building data infrastructure in your organization, no matter the size.</li><li>How to embed data best practices in your team and how to get the most value out of data science.</li><li>Actionable advice on how to scale machine learning in your organization through making data accessible and automating data access processes.</li><li>Data protection is a true differentiator in today’s market. You don’t need to use<br/>personal data for data science and fake users are better than real ones for testing your<br/>ideas.</li></ul>]]></content:encoded>
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    <itunes:author>MOSTLY AI</itunes:author>
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    <pubDate>Mon, 19 Apr 2021 08:00:00 +0200</pubDate>
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    <itunes:duration>2651</itunes:duration>
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    <itunes:title>5. Enterprise strategies for privacy and AI with Punit Bhatia</itunes:title>
    <title>5. Enterprise strategies for privacy and AI with Punit Bhatia</title>
    <itunes:summary><![CDATA[Punit Bhatia was the Privacy and Protection Officer at ING and has tons of experience in managing privacy and data protection in large international environments. In this episode, Punit shares his best strategic advice for those looking to strategize privacy in their organization.  You will hear about: the three biggest privacy challenges for enterprises and their solutionswhose responsibility should privacy be in an organization for best results why synthetic data is the way forwar...]]></itunes:summary>
    <description><![CDATA[<p>Punit Bhatia was the Privacy and Protection Officer at ING and has tons of experience in managing privacy and data protection in large international environments. In this episode, Punit shares his best strategic advice for those looking to strategize privacy in their organization. </p><p>You will hear about:</p><ul><li>the three biggest privacy challenges for enterprises and their solutions</li><li>whose responsibility should privacy be in an organization for best results</li><li> why synthetic data is the way forward in data-sharing</li><li>how to approach AI from a privacy and data protection standpoint</li><li>what should companies expect in the privacy space in 2021 and beyond</li></ul>]]></description>
    <content:encoded><![CDATA[<p>Punit Bhatia was the Privacy and Protection Officer at ING and has tons of experience in managing privacy and data protection in large international environments. In this episode, Punit shares his best strategic advice for those looking to strategize privacy in their organization. </p><p>You will hear about:</p><ul><li>the three biggest privacy challenges for enterprises and their solutions</li><li>whose responsibility should privacy be in an organization for best results</li><li> why synthetic data is the way forward in data-sharing</li><li>how to approach AI from a privacy and data protection standpoint</li><li>what should companies expect in the privacy space in 2021 and beyond</li></ul>]]></content:encoded>
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    <itunes:author>MOSTLY AI</itunes:author>
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    <pubDate>Thu, 01 Apr 2021 08:00:00 +0200</pubDate>
    <itunes:duration>2826</itunes:duration>
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    <itunes:title>4. Lessons of privacy and innovation with Sang Shin, Digital Innovation Director of Temasek</itunes:title>
    <title>4. Lessons of privacy and innovation with Sang Shin, Digital Innovation Director of Temasek</title>
    <itunes:summary><![CDATA[In the fourth episode of the Data Democratization pod, we are talking to Sang Shin, serial entrepreneur, investment expert about his adventures in data monetization and he'll share his vision for the future of the data and privacy space.  Topics discussed in the episode: How Been Choice, a privacy protection and data monetization app was banned by AppleWhat is the data privacy landscape like in Southeast Asia in 2021What are some notable privacy tech innovationsHow synthetic data made a ...]]></itunes:summary>
    <description><![CDATA[<p>In the fourth episode of the Data Democratization pod, we are talking to Sang Shin, serial entrepreneur, investment expert about his adventures in data monetization and he&apos;ll share his vision for the future of the data and privacy space. <br/>Topics discussed in the episode:</p><ul><li>How Been Choice, a privacy protection and data monetization app was banned by Apple</li><li>What is the data privacy landscape like in Southeast Asia in 2021</li><li>What are some notable privacy tech innovations</li><li>How synthetic data made a datathon possible with data from both the private and public sector</li><li>What the future holds for tech innovations and why the open data movement is gaining momentum</li></ul>]]></description>
    <content:encoded><![CDATA[<p>In the fourth episode of the Data Democratization pod, we are talking to Sang Shin, serial entrepreneur, investment expert about his adventures in data monetization and he&apos;ll share his vision for the future of the data and privacy space. <br/>Topics discussed in the episode:</p><ul><li>How Been Choice, a privacy protection and data monetization app was banned by Apple</li><li>What is the data privacy landscape like in Southeast Asia in 2021</li><li>What are some notable privacy tech innovations</li><li>How synthetic data made a datathon possible with data from both the private and public sector</li><li>What the future holds for tech innovations and why the open data movement is gaining momentum</li></ul>]]></content:encoded>
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    <itunes:author>MOSTLY AI</itunes:author>
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    <pubDate>Thu, 11 Mar 2021 15:00:00 +0100</pubDate>
    <itunes:duration>2316</itunes:duration>
    <itunes:keywords></itunes:keywords>
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    <itunes:episode>4</itunes:episode>
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  <item>
    <itunes:title>3. The digital transformation talk with Rebecca Macieira-Kaufmann, ex-Citi, ex-Well Fargo executive, Revolut board member, and author</itunes:title>
    <title>3. The digital transformation talk with Rebecca Macieira-Kaufmann, ex-Citi, ex-Well Fargo executive, Revolut board member, and author</title>
    <itunes:summary><![CDATA[In this episode, we will be exploring best practices around digital transformations in banking. Rebecca has decades of experience in leading financial institutions and led major transformations during her career. She has a unique, executive-level perspective to share with us about processes, data management, and how AI can be used for fairness. You can find Rebecca through her website. ]]></itunes:summary>
    <description><![CDATA[<p>In this episode, we will be exploring best practices around digital transformations in banking. Rebecca has decades of experience in leading financial institutions and led major transformations during her career. She has a unique, executive-level perspective to share with us about processes, data management, and how AI can be used for fairness. You can find Rebecca <a href=' https://rmkgroupllc.com/'>through her website.</a></p>]]></description>
    <content:encoded><![CDATA[<p>In this episode, we will be exploring best practices around digital transformations in banking. Rebecca has decades of experience in leading financial institutions and led major transformations during her career. She has a unique, executive-level perspective to share with us about processes, data management, and how AI can be used for fairness. You can find Rebecca <a href=' https://rmkgroupllc.com/'>through her website.</a></p>]]></content:encoded>
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    <pubDate>Wed, 03 Mar 2021 08:00:00 +0100</pubDate>
    <itunes:duration>1930</itunes:duration>
    <itunes:keywords>digital transformation</itunes:keywords>
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    <itunes:title>2. Privacy tips and tricks from Nada Bseikri, VP and Privacy Officer of Apple Bank, New York</itunes:title>
    <title>2. Privacy tips and tricks from Nada Bseikri, VP and Privacy Officer of Apple Bank, New York</title>
    <itunes:summary><![CDATA[Our second guest on the show is Nada Bseikri, a privacy pro from Apple Bank, New York. Nada has a unique perspective: she has both a legal and a software engineering background. Thanks to this double role, she can share unique insights into the field of data privacy. Nada shares her best tips for making privacy go beyond compliance, and we'll find out why privacy carrots are important.  ]]></itunes:summary>
    <description><![CDATA[<p>Our second guest on the show is Nada Bseikri, a privacy pro from Apple Bank, New York. Nada has a unique perspective: she has both a legal and a software engineering background. Thanks to this double role, she can share unique insights into the field of data privacy. Nada shares her best tips for making privacy go beyond compliance, and we&apos;ll find out why privacy carrots are important. </p>]]></description>
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    <itunes:author>MOSTLY AI</itunes:author>
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    <pubDate>Thu, 11 Feb 2021 07:00:00 +0100</pubDate>
    <itunes:duration>2047</itunes:duration>
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    <itunes:title>1. Celebrating Data Privacy Day with Shampa Chatterjee, Director of Data Privacy at Silicon Valley Bank</itunes:title>
    <title>1. Celebrating Data Privacy Day with Shampa Chatterjee, Director of Data Privacy at Silicon Valley Bank</title>
    <itunes:summary><![CDATA[What better way to celebrate Data Privacy Day than to have an awesome chat with a seasoned privacy professional who has been in the frontlines of privacy since the dawn of days? Shampa Chatterjee shares her great adventures around the world and in the service of others, as well as her best advice to those looking to create success stories in the field of data privacy. We discussed customer-centricity, privacy tech, automation, synthetic data, and more.  ]]></itunes:summary>
    <description><![CDATA[<p>What better way to celebrate Data Privacy Day than to have an awesome chat with a seasoned privacy professional who has been in the frontlines of privacy since the dawn of days? Shampa Chatterjee shares her great adventures around the world and in the service of others, as well as her best advice to those looking to create success stories in the field of data privacy. We discussed customer-centricity, privacy tech, automation, synthetic data, and more. </p>]]></description>
    <content:encoded><![CDATA[<p>What better way to celebrate Data Privacy Day than to have an awesome chat with a seasoned privacy professional who has been in the frontlines of privacy since the dawn of days? Shampa Chatterjee shares her great adventures around the world and in the service of others, as well as her best advice to those looking to create success stories in the field of data privacy. We discussed customer-centricity, privacy tech, automation, synthetic data, and more. </p>]]></content:encoded>
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    <itunes:author>MOSTLY AI</itunes:author>
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    <pubDate>Thu, 21 Jan 2021 20:00:00 +0100</pubDate>
    <itunes:duration>2459</itunes:duration>
    <itunes:keywords>data, privacy, tech, synthetic data, interview</itunes:keywords>
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