Every time you open TikTok or YouTube, a system you didn't choose has already decided what you're going to believe today.

And the people who built it? They're not thinking about you.

In this episode, we continue our AI, Power, Law, and Civic Life miniseries with Dr. Ramesh Srinivasan, Professor at UCLA and founder of the Digital Cultures Lab, whose research on algorithms, power, and democracy has taken him to nearly 80 countries and into conversations with the White House, the European Union, and governments across four continents.

Together, we explore:

• Why no algorithm is neutral — and what it actually means when a platform claims to just show you "what you like"
• How the same platform can present two students sitting next to each other with completely different versions of reality
• What people in Afghanistan, Egypt, and rural India told him they actually want from technology — and why Silicon Valley isn't listening
• The bait and switch at the heart of the data economy: why these platforms would be worth nothing without your data, and why you've never been paid a cent for it
• How algorithmic fragmentation is fueling nativism and authoritarianism across the globe
• What transparency, accountability, and democratic governance of AI would actually look like — and why social media proves what happens when we skip that step

Dr. Srinivasan also shares his own non-linear path from college radio DJ to Stanford engineer to globally recognized scholar and activist, and why the most important thing he ever learned was to stay true to who he is as a human being first.

This conversation will change how you think about every feed, every recommendation, and every platform that claims to know you.

Because in a world where algorithms decide what's real, the question isn't just what you're being shown — it's who decided you should see it, and why.

Paths of Curiosity in an AI World Exploring tomorrow's careers through the lens of AI

Paths of Curiosity in an AI World
Exploring tomorrow’s careers through the lens of AI
Follow us: @pathsofcuriosity

Website: https://pathsofcuriosity.com/
Youtube: youtube.com/@PathsofCuriosity
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What if the video used to convict someone never actually happened?

That's not science fiction. With today's deepfake technology, it could happen in any courtroom - and soon!

In this episode, we continue our AI, Power, Law, and Civic Life miniseries with Dr. Maura Grossman, Research Professor of Computer Science at the University of Waterloo and Adjunct Professor at Osgoode Hall Law School, whose work at the intersection of AI, law, and evidence has made her one of the most sought-after experts in courtrooms on both sides of the border.

Together, we explore:

• Why deepfakes have changed evidence manipulation from a skilled crime to something anyone can do in five minutes for free
• The nightmare scenario: what happens when fabricated audio or video shows up in family court, and no one can tell it's fake
• How Dr. Grossman is building a deepfake detection tool specifically designed for the justice system — and why explainability is non-negotiable
• Why "black box" AI has no place in a courtroom where someone's freedom is on the line
• What metadata, physics, and shadows can reveal about whether a video is real
• Whether juries will ever be able to trust video evidence again — and how soon that moment of no return might arrive

Dr. Grossman also shares her remarkable non-linear path from clinical psychologist to elite litigator to computer science professor, and why the best career advice she ever received was to stop being a generalist.

This conversation will change how you look at every video you've ever trusted.

Because in a world where anyone can fabricate a confession, a threat, or a crime — the real question isn't just whether the evidence is real. It's whether we'll ever be able to know.

Paths of Curiosity in an AI World
Exploring tomorrow’s careers through the lens of AI
Follow us: @pathsofcuriosity

Website: https://pathsofcuriosity.com/
Youtube: youtube.com/@PathsofCuriosity
X: https://x.com/PathsCuriosity
LinkedIn: https://www.linkedin.com/in/paths-of-curiosity-in-an-ai-world-2117803aa/

Paths of Curiosity in an AI World

What if the app deciding how much to pay you already knows how little you're willing to accept?

For millions of gig workers, that's not a hypothetical. That is your typical day. 

In this episode, we continue our AI, Power, Law, and Civic Life miniseries with Dr. Veena Dubal, Professor of Law and Anthropology at UC Irvine, whose research on algorithmic labor control has been cited by the California Supreme Court and covered by the New York Times, NPR, and CNN. TechCrunch called her an unlikely star in the tech world — and once you hear what she's uncovered, you'll understand why.

Together, we explore:

• How gig companies legally stripped millions of workers of basic protections by classifying them as independent contractors
• What algorithmic wage discrimination actually means — and why two drivers doing the same ride can be paid completely different amounts
• The desperation score: what it is, why workers believe it exists, and why there's nothing stopping companies from using one
• How gamification and intentional psychological design keep workers accepting bad offers
• Why the "supply and demand" defense doesn't hold up — and what these platforms are really doing
• What it will take for algorithmic wage discrimination to finally become illegal

Dr. Dubal also shares her journey from public interest law to becoming one of the most recognized critics of Silicon Valley's labor practices, and why writing — real, effortful writing — may be the most important skill you can build in an AI-shaped world.

This conversation will change how you look at every app that pays people on the other side.

Because in a world where algorithms set your wages behind a black box, the real question isn't just whether the system is fair — it's whether anyone is allowed to ask.

Paths of Curiosity in an AI World
Exploring tomorrow’s careers through the lens of AI
Follow us: @pathsofcuriosity

Website: https://pathsofcuriosity.com/
Youtube: youtube.com/@PathsofCuriosity
X: https://x.com/PathsCuriosity
LinkedIn: https://www.linkedin.com/in/paths-of-curiosity-in-an-ai-world-2117803aa/

What if the government could track everywhere you’ve been, everyone you’ve contacted, and everything you’ve searched, without ever asking permission?

For years, that was dangerously close to reality.

In this episode, we launch our AI, Power, Law, and Civic Life miniseries with Nathan Freed Wessler, Deputy Director of the ACLU’s Speech, Privacy, and Technology Project, who took this question all the way to the Supreme Court and won.

He argued Carpenter v. United States, a landmark case that established a critical rule for the digital age: law enforcement must get a warrant before accessing your cell phone location history. But that victory is just one piece of a much larger story.

Together, we explore:

•  How AI-powered surveillance is transforming what governments can know about you 
•  Why your phone is one of the most powerful tracking devices ever created 
•  The hidden world of data brokers buying and selling your location information 
•  How facial recognition can lead to wrongful arrests, especially for people of color 
•  Why “I have nothing to hide” misses the point entirely 
•  What’s at stake for your future if privacy laws don’t keep up with technology 

Nathan also shares his journey from political organizing to arguing before the Supreme Court, and why the most important career decisions often can’t be planned.

This conversation will change how you think about your phone, your data, and your rights.

Because in a world where surveillance is becoming effortless, the real question is not just who is watching — but when they’re allowed to.

Paths of Curiosity in an AI World
Exploring tomorrow’s careers through the lens of AI
Follow us: @pathsofcuriosity

Website: https://pathsofcuriosity.com/
Youtube: youtube.com/@PathsofCuriosity
X: https://x.com/PathsCuriosity
LinkedIn: https://www.linkedin.com/in/paths-of-curiosity-in-an-ai-world-2117803aa/

What does AI in healthcare actually look like right now and who is building it?

In this recap episode, Acadia and Alora step back from six conversations across medicine, engineering, and policy to connect the bigger picture. From an emergency room algorithm saving lives in real time, to AI systems that reshape how doctors work, to the hidden risks of trusting machines too much, this episode brings together what’s real, what’s working, and what’s still unresolved.

You’ll hear how:

•  AI is already changing patient outcomes today, not just in theory 
•  The biggest risks aren’t always the technology, but how it’s used 
•  The same data can either widen or close gaps in care 
•  Entire career paths in this space didn’t exist a decade ago 
•  The most valuable skills might not be what you expect 

This episode is also a guide for students, parents, and educators: how to think about careers that don’t fully exist yet, what skills actually matter, and what you can do now to get started.

Because the future of healthcare isn’t finished and the people who will shape it are still in school.

Paths of Curiosity in an AI World
Exploring tomorrow’s careers through the lens of AI
Follow us: @pathsofcuriosity

Website: https://pathsofcuriosity.com/
Youtube: youtube.com/@PathsofCuriosity
X: https://x.com/PathsCuriosity
LinkedIn: https://www.linkedin.com/in/paths-of-curiosity-in-an-ai-world-2117803aa/

What if your earbuds could measure your blood pressure? Or your smartwatch could detect illness days before you feel sick?

In this episode of Paths of Curiosity in an AI World, host Acadia explores the future of wearable health technology with Dr. Mayank Goel, assistant professor at the Carnegie Mellon University. His lab is developing new ways to turn everyday consumer devices into powerful health monitoring tools.

Dr. Goel’s team is building wearable sensors that can continuously track signals from the human body, from earbuds that estimate blood pressure to algorithms that analyze movement patterns and behavior using devices people already wear every day. The goal is simple but ambitious: detect health issues earlier and give doctors better data to help patients.

But the story behind these technologies is just as interesting as the devices themselves. Dr. Goel shares how interdisciplinary collaboration between engineers, doctors, and students turns impossible-sounding ideas into real research projects, and why many breakthroughs begin simply by “doing more with less.”

In this conversation, we explore:

• How everyday devices like earbuds and smartwatches are becoming medical sensors
 • Why AI is essential for turning raw sensor data into meaningful health insights
 • The biggest challenges in building wearable health technology, including privacy and data access
 • Why physics and foundational science may be the most valuable skills for future innovators
 • How the future of healthcare could shift toward personalized medical devices designed for each individual

For students interested in engineering, AI, or healthcare innovation, this episode offers a behind-the-scenes look at how researchers turn creative ideas into technologies that could change how millions of people monitor their health.

If you’re curious about careers at the intersection of AI, hardware, and medicine, this conversation will open your eyes to possibilities you might not have imagined.

Paths of Curiosity in an AI World
Exploring tomorrow’s careers through the lens of AI
Follow us: @pathsofcuriosity

Website: https://pathsofcuriosity.com/
Youtube: youtube.com/@PathsofCuriosity
X: https://x.com/PathsCuriosity
LinkedIn: https://www.linkedin.com/in/paths-of-curiosity-in-an-ai-world-2117803aa/

Your health data is being used to build the future of medicine. Dr. Erin Holve helped write the rules to make sure that future still belongs to you.

In this episode of Paths of Curiosity in an AI World, we continue our AI and Healthcare mini-series with Dr. Erin Holve, a health services researcher, methodologist, and policy architect who has spent over two decades turning raw health data into evidence that actually improves care. From helping draft the original HIPAA privacy notice practices to shaping the data quality standards that make AI research trustworthy, Dr. Holve has been quietly building the infrastructure that makes modern healthcare AI possible.

Dr. Holve pulls back the curtain on what health services research actually is — and why its messy, multi-disciplinary nature makes it one of the most dynamic fields you've never heard of. She explains the promise and the tension at the heart of the "learning health system" — the idea that every doctor's visit you've ever had could, in theory, contribute to better care for millions — and why commercial interests and fragmented data systems keep that vision just out of reach.

She also gets candid about something few guests address directly: when you type your symptoms into a chatbot, that information may not be protected the way your doctor's records are. And as AI tools go mainstream in healthcare, that gap is becoming one of the most important policy questions of our time.

In this episode, we explore:

• What health services research is and why it sits at the intersection of biology, economics, policy, and public health
• How AI is — and isn't — changing day-to-day research work (and why fundamentals still matter most)
• What a "learning health system" means, and the data privacy tensions standing in its way
• Why the language we use to talk about patient rights changed real-world decisions — and continues to today
• What blockchain, open science, and content ownership have to do with your generation's career in AI
• The three human skills — plus one book recommendation — Dr. Holve says will matter most by 2035

This episode is a reminder that behind every AI model in healthcare, there are researchers, policymakers, and advocates making sure the data is clean, the questions are right, and the people those decisions affect actually have a voice.

Resources:
1. Future Jobs Map: 
https://pathsofcuriosity.com/Future_Jobs_Map_-_AI_in_Healthcare.htm

2. Student Self-Discovery - What's Your Spark :
https://pathsofcuriosity.com/whats_your_spark_quiz.html

Paths of Curiosity in an AI World
Exploring tomorrow’s careers through the lens of AI
Follow us: @pathsofcuriosity

Website: https://pathsofcuriosity.com/
Youtube: youtube.com/@PathsofCuriosity
X: https://x.com/PathsCuriosity
LinkedIn: https://www.linkedin.com/in/paths-of-curiosity-in-an-ai-world-2117803aa/

with Dr. Natalie Pageler, MD

The choices we make for kids today echo for a lifetime. Dr. Natalie Pageler uses AI to help doctors notice the moments that could change a child's life — for better or worse.

In this episode of *Paths of Curiosity in an AI World*, we continue our AI and Healthcare mini-series with Dr. Natalie Pageler, a board-certified pediatrician, pediatric intensivist, and clinical informaticist at Stanford Medicine. As the inaugural Division Chief of Clinical Informatics, Clinical Professor of Pediatrics, and Associate Dean for Maternal and Child Health, Dr. Pageler has spent more than a decade designing safe, ethical, and meaningful uses of AI for children and families — a challenge that looks very different when your patients are growing, changing, and often unable to speak for themselves.

Dr. Pageler shares what drew her from the bedside to the system level, and why the transition from caring for one patient at a time to shaping how all pediatricians practice felt like the natural extension of the same mission. She walks us through the unique challenges of deploying AI in pediatric care — from smaller and more fragmented data, to models never tested on children, to the ethical stakes of interventions whose effects can ripple across an entire lifetime.

We also explore the invisible work behind any successful health technology: the people, process, and workflow decisions that determine whether a tool helps or harms. And we dig into one of the clearest ethical tensions in AI healthcare today — how the same predictive model can either overbook clinics at the expense of vulnerable families, or proactively remove the barriers keeping those same families from getting care.

In this episode, we explore:
- Why AI in pediatrics requires different data, different models, and different stakeholders
- How automation bias and automation neglect show up in clinical practice — and how to teach around them
- What clinical informatics is and why it's one of medicine's newest — and most important — subspecialties
- How a predictive model for missed appointments can either deepen or reduce health inequity depending on how it's used
- What future pediatricians will need to know that wasn't taught a generation ago

This episode is a reminder that in healthcare, the most powerful uses of AI aren't about replacing clinical judgment. They're about giving every child — regardless of circumstance — a better shot at a healthier life.

Resources:
1. Future Jobs Map: 
https://pathsofcuriosity.com/Future_Jobs_Map_-_AI_in_Healthcare.htm

2. Student Self-Discovery - What's Your Spark :
https://pathsofcuriosity.com/whats_your_spark_quiz.html

Paths of Curiosity in an AI World
Exploring tomorrow’s careers through the lens of AI
Follow us: @pathsofcuriosity

Website: https://pathsofcuriosity.com/
Youtube: youtube.com/@PathsofCuriosity
X: https://x.com/PathsCuriosity
LinkedIn: https://www.linkedin.com/in/paths-of-curiosity-in-an-ai-world-2117803aa/

with Dr. Gabriel Wardi

In emergency medicine, minutes matter, and some of the most dangerous conditions do not announce themselves clearly.

In this episode of Paths of Curiosity in an AI World, we continue our AI and Healthcare mini-series with Dr. Gabriel Wardi, an emergency and critical care physician at UC San Diego Health and a leader in applying machine learning to high-stakes clinical care. Dr. Wardi works at the front lines of medicine, where chaos, speed, and uncertainty are part of everyday life, and where AI has the potential to save lives when used thoughtfully.

Dr. Wardi shares how working in the emergency department reshaped the way he thinks about healthcare problems beyond individual patients, and why sepsis, a condition that affects millions worldwide but often goes unrecognized, became a focus of his work. He walks us through the real-world implementation of a deep learning sepsis prediction model that gave clinicians hours of lead time and contributed to a 17% reduction in sepsis-related mortality at UC San Diego Health.

We also explore where AI truly helps clinicians today, where it can be risky, and why AI must remain a tool rather than a replacement for clinical reasoning. From early diagnosis and patient flow to ambient AI scribes and future triage systems, this conversation shows what it actually takes to bring AI into real emergency care.

In this episode, we explore:

• Why sepsis is so hard to catch and how AI can help identify it earlier
• How machine learning models work inside a real emergency department
• What makes clinicians trust or ignore AI alerts
• Where AI improves efficiency and where it can be dangerous
• How students can explore careers at the intersection of AI, medicine, and patient impact

This episode is a reminder that AI’s biggest promise in healthcare is not flashy technology. It is giving clinicians the right information at the right moment, so fewer patients slip through the cracks.

Resources:
1. Future Jobs Map:
https://pathsofcuriosity.com/Future_Jobs_Map_-_AI_in_Healthcare.htm

2. Student Self-Discovery - What's Your Spark :
https://pathsofcuriosity.com/whats_your_spark_quiz.html

Paths of Curiosity in an AI World
Exploring tomorrow’s careers through the lens of AI
Follow us: @pathsofcuriosity

Website: https://pathsofcuriosity.com/
Youtube: youtube.com/@PathsofCuriosity
X: https://x.com/PathsCuriosity
LinkedIn: https://www.linkedin.com/in/paths-of-curiosity-in-an-ai-world-2117803aa/

What if we’re asking doctors to do something humans are actually bad at?

In this episode of Paths of Curiosity in an AI World, we continue our AI and Healthcare mini-series with Dr. Julia Adler-Milstein, founding chief of UCSF’s Division of Clinical Informatics and Digital Transformation and a national leader in health policy and AI governance. Dr. Adler-Milstein studies a critical question facing modern healthcare: when AI systems make mistakes, who is responsible for catching them?

From her early career path through consulting to pioneering research at the intersection of data, policy, and medicine, Dr. Adler-Milstein explains why AI vigilance is harder than it sounds, why relying on individual clinicians to catch rare AI errors may be unrealistic, and how better system design can make AI safer in practice.

We explore how research shapes real policy decisions, how data sharing laws changed because of evidence, and why writing, systems thinking, and curiosity matter just as much as technical skills. This conversation offers a behind-the-scenes look at how AI is monitored, governed, and improved in real healthcare settings, and where students might fit into that future.

In this episode, we explore:

• Why humans struggle to catch AI mistakes—and what to do instead
• How AI governance and monitoring systems are emerging in healthcare
• How research influences federal and state health policy
• Where AI can reduce clinician burden—and where it might add to it
• Career paths for students interested in data, policy, and healthcare without clinical practice

Let’s follow that curiosity and see where it leads!

Resources:
1. Future Jobs Map:
https://pathsofcuriosity.com/Future_Jobs_Map_-_AI_in_Healthcare.htm

2. Student Self-Discovery - What's Your Spark :
https://pathsofcuriosity.com/whats_your_spark_quiz.html

Paths of Curiosity in an AI World
Exploring tomorrow’s careers through the lens of AI
Follow us: @pathsofcuriosity

Website: https://pathsofcuriosity.com/
Youtube: youtube.com/@PathsofCuriosity
X: https://x.com/PathsCuriosity
LinkedIn: https://www.linkedin.com/in/paths-of-curiosity-in-an-ai-world-2117803aa/

What does it actually look like when artificial intelligence shows up in a real hospital, not as hype, but as a tool people rely on every day?

In our first episode of Paths of Curiosity in an AI World, we sit down with Dr. Chris Longhurst, CEO of Seattle Children’s Hospital, to explore how AI is changing healthcare at the level where it matters most: people, data, and decisions. From mission-control-style hospital operations to the human judgment behind AI systems, Dr. Longhurst shares how technology can support, not replace, clinicians, nurses, and care teams.

We talk about what AI is already doing behind the scenes, what surprised him most as a healthcare leader, and why curiosity, systems thinking, and ethics matter just as much as coding skills. Whether you’re curious about medicine, data science, leadership, or the future of healthcare, this conversation opens a window into how AI-driven careers work in practice.

In this episode, we explore:

• How AI helps hospitals make faster, safer decisions
• Why healthcare is as much about people as it is about data
• What students should understand about careers at the intersection of AI and medicine

Let’s follow that curiosity and see where it leads!

Resources:
1. Future Jobs Map:
https://pathsofcuriosity.com/Future_Jobs_Map_-_AI_in_Healthcare.htm

2. Student Self-Discovery - What's Your Spark :
https://pathsofcuriosity.com/whats_your_spark_quiz.html

Paths of Curiosity in an AI World
Exploring tomorrow’s careers through the lens of AI
Follow us: @pathsofcuriosity

Website: https://pathsofcuriosity.com/
Youtube: youtube.com/@PathsofCuriosity
X: https://x.com/PathsCuriosity
LinkedIn: https://www.linkedin.com/in/paths-of-curiosity-in-an-ai-world-2117803aa/