Ayush Prakash Podcast

Hosted by Ayush Prakash

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171

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Oct 2026

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About the show

The Ayush Prakash Podcast is the public channel of the Center for Innovating the Future, a strategy innovation lab based in Toronto. Across 150+ episodes since 2021, I've sat down with neuroscientists, philosophers, astrophysicists, psychologists and builders to work out what these technologies are actually doing to us, and which claims are being made without evidence. innovatingfuture.com

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October 6, 2026Episode 17138 min

Tristan Glatard: Can AI Help With Mental Health?

AI could expand access to mental-health support, but a convincing conversation doesn’t establish that a chatbot is safe. Tristan Glatard explains why mental-health AI needs evidence, evaluation and human supervision, and how its potential extends from conversational tools to predicting treatment responses and identifying crises. Tristan is Scientific Director of the Krembil Centre for Neuroinformatics at the Centre for Addiction and Mental Health (CAMH) in Toronto. His background is in computer science. In this conversation, he examines where AI could help patients, where general-purpose chatbots need limits, and why privacy, patient perspectives and clinical oversight matter. In this conversation: What mental health means across the lifespan How AI could help match patients with treatments Why mental-health AI includes wearables and predictive tools The difference between healthcare chatbots, wellbeing apps and general-purpose AI The case for support when a human therapist isn’t available Whether people disclose more to chatbots, and what remains uncertain Why wellbeing tools need evaluation How hospital researchers balance opportunity, safety and health equity Why crisis detection and data privacy matter How patients should shape the use of AI in their care Who evaluates and supervises AI support conversations A surprising finding from Tristan’s ongoing image-analysis research What discovery, collaboration and good work mean to him Chapters: 00:00 AI and Mental Health at CAMH 01:29 What Do We Mean by Mental Health? 03:41 How Technology Can Help Personalize Treatment 05:48 AI Beyond Chatbots: Wearables and Prediction 08:58 The Case for an AI Companion 13:15 Do People Open Up More to Chatbots? 15:03 Where AI Mental-Health Support Breaks Down 16:56 Balancing Opportunity, Safety and Health Equity 20:00 Crisis Detection and Data Privacy 22:12 The AI Healthcare Conversation We Need 26:28 Who Supervises AI Support? 30:19 A Surprising Research Discovery 33:03 What Keeps a Researcher Going 35:40 What Gives Tristan Hope 37:30 Where to Follow Tristan’s Work Connect with Tristan: Website: https://www.camh.ca/en/science-and-research/science-and-research-staff-directory/tristanglatard LinkedIn: https://www.linkedin.com/in/tristanglatard/ Podcast: Spotify: https://open.spotify.com/show/1ILhje5HSua1FEOlTyFAhG Apple Podcasts: https://apple.co/3qXL37W Connect: Website: https://ayushprakash.com LinkedIn: https://www.linkedin.com/in/prakash-ayush/ Instagram: https://instagram.com/ayushprakashofficial Book: https://www.amazon.com/dp/0981182135

October 1, 2026Episode 17034 min

Anna Jahn: Why Canada Can’t Build AI Sovereignty Alone

A Canadian frontier model alone won’t give Canada control over its AI future. Anna Jahn explains why AI sovereignty also depends on data, energy, compute, talent, and governance, and why countries may need to combine their strengths to reduce dependence on the biggest AI powers. Anna is Executive Director of the Centre for Media, Technology and Democracy at McGill University. She previously led public policy and inclusion work at Mila. In this conversation, she examines who holds power over AI now, why Canadian research strength hasn’t produced the same economic strength, and what a credible Canadian approach could look like. In this conversation: Why researchers, the public, government, and industry talk past one another Whether democratic policymaking needs to match the pace of AI Why voluntary company safeguards aren’t enough The tension between promoting AI adoption and protecting the public Why a domestic frontier model is only one part of AI sovereignty How Canada could work with other middle powers Why Canadian AI talent often builds companies elsewhere What Anna wants to hear from Mark Carney about AI Montreal’s opportunity to offer a different vision for AI What it would take for Canadians to trust and benefit from the technology Chapters: 00:00 Who Gets a Say in AI Policy? 02:19 Can Governments Keep Up With AI? 05:17 Who Is Responsible for AI Safety? 08:03 AI Adoption vs. Public Protection 11:15 Why One Model Won’t Deliver AI Sovereignty 14:07 Why Canada Struggles to Commercialize AI Research 16:49 What a Middle-Power AI Alliance Could Look Like 21:55 What Canada Needs to Do First 24:44 Is Montreal Still a Leading AI Hub? 27:38 Should Montreal Try to Become Another Silicon Valley? 29:34 What AI Success Would Look Like for Canadians 32:28 What Gives Anna Hope 33:32 Where to Find Anna’s Work Connect with Anna: Website: https://mediatechdemocracy.com/en/team/anna-jahn/ LinkedIn: https://www.linkedin.com/in/anna-jahn-8a318241/ Podcast: Spotify: https://open.spotify.com/show/1ILhje5HSua1FEOlTyFAhG Apple Podcasts: https://apple.co/3qXL37W Connect: Website: https://ayushprakash.com LinkedIn: https://www.linkedin.com/in/prakash-ayush/ Instagram: https://instagram.com/ayushprakashofficial Book: https://www.amazon.com/dp/0981182135

August 28, 2026Episode 16951 min

Nick Nadeau: The AI You’re Talking To Is a Bootleg of Human Expertise

Nicholas Nadeau argues that the AI most people use is a bootleg of human expertise: a confident statistical average built from scraped public data, without the judgment, consent, or unpublished knowledge that makes an expert worth consulting. Nicholas is the CTO and Co-Founder of Onix. He holds a PhD in human-robot interaction and previously served as CTO of humanoid-robotics company 1X and data company SmartOne.ai. Onix is building private AI systems grounded in the approved work and judgment of individual experts. In this conversation: ■ Whose answer you receive when you ask AI a question ■ Why frontier models blend textbooks, social media, and internet noise ■ What gets lost when AI attempts to imitate a human expert ■ Why an expert's most important knowledge may never have been published ■ How privacy and on-device AI can improve personal usefulness ■ Whether expert AI will replace professionals or increase their capacity ■ What young founders should understand about risk, stamina, and relationships ■ Why smart investors must contribute more than capital ■ How personal AI could eventually connect with robotics ■ The question Nicholas asks himself every day: should Onix exist? CHAPTERS 00:00 Whose Answer Is AI Giving You? 04:02 Transactional AI vs. Wicked Problems 06:03 What AI Misses About Expert Judgment 11:51 Dark Data and the Knowledge Experts Never Publish 17:28 How Onix Began 22:42 Advice for Young Founders 28:45 Smart Money and Choosing Investors 32:45 Onix Beyond Health: Robots and Human Expertise 36:59 Will Expert AI Replace Humans? 41:20 Would Nicholas Let His Children Use AI? 46:45 The Question That Keeps Him Up at Night 48:49 What Gives Him Hope 50:45 Where to Find Nicholas and Onix CONNECT WITH NICHOLAS Website: https://nicholasnadeau.com Onix: https://onix.life LISTEN TO THE PODCAST Spotify: https://open.spotify.com/show/1ILhje5HSua1FEOlTyFAhG Apple Podcasts: https://apple.co/3qXL37W CONNECT WITH AYUSH Website: https://ayushprakash.com LinkedIn: https://www.linkedin.com/in/prakash-ayush/ Instagram: https://instagram.com/ayushprakashofficial AI FOR GEN Z https://www.amazon.com/dp/0981182135

July 28, 2026Episode 16844 min

Renée Sieber: We’re Forcing AI Into Schools Before We Know What It Does to Students

Renée Sieber explains why schools and public institutions are adopting generative AI before confronting its effects on learning, judgment, privacy, and civic life. Her central warning: when AI substitutes for the struggle involved in thinking and writing, students may become dependent on systems they were never given a meaningful choice to refuse.Renée is an associate professor at McGill University whose work spans AI, natural language processing, public policy, and civic engagement. We discuss what AI literacy should include, why transparency means little when people cannot act on it, how communities can contest unwanted systems, the history of Luddism, and what a genuinely humanizing technology could look like.In this episode:- Why Renée has gained respect for controlled-corpus deep learning- How social justice separates signal from noise in AI policy- Why individual “choice” fails as a frame for structural AI harms- What governments and communities can do when AI becomes embedded- How generative AI can remove productive struggle from education- Why Renée embraces the original meaning of Luddism- Where local, bounded AI systems may serve real human needs- Why Gen Z’s resistance gives her hopeChapters:00:00 What Renée changed her mind about00:46 Where she gets information about AI01:50 Social justice as the signal in AI policy06:31 Why these harms are difficult to discuss09:33 What AI literacy should actually mean14:54 Can communities reject embedded AI?20:28 Rebuilding civic engagement in Canada23:10 What generative AI is doing to students34:38 Why Renée embraces Luddism35:29 What humanizing technology could look like37:26 Thinking, writing, and the value of struggle39:50 The technology Renée would eliminate41:15 What gives her hope43:30 Where to follow Renée’s workConnect with Renée:Website: https://aifortherestofus.ca/McGill profile: https://www.mcgill.ca/geography/sieberPodcast:Spotify: https://open.spotify.com/show/1ILhje5HSua1FEOlTyFAhGApple Podcasts: https://apple.co/3qXL37WConnect with Ayush:Website: https://ayushprakash.comLinkedIn: https://www.linkedin.com/in/prakash-ayush/Instagram: https://instagram.com/ayushprakashofficialBook:AI for Gen Z: https://www.amazon.com/dp/0981182135

July 21, 2026Episode 16744 min

Nidhi Hegde: AI Isn’t Democratized If You Have Access but No Agency

Nidhi Hegde explains why giving the public access to chatbots does not make AI democratic when users have no control over how the systems are built, trained, or deployed. Her central argument is that agency, representation, privacy, fairness, and technical robustness must be treated as connected design and governance problems. Nidhi is an associate professor of computing science at the University of Alberta, a Fellow at the Alberta Machine Intelligence Institute, and a Canada CIFAR AI Chair. We discuss what trustworthy AI means technically, the unavoidable trade-offs between privacy, fairness, accuracy, and cost, why broad AI regulation targets the wrong unit, and what public participation in AI decisions could actually require. In this episode: - How model robustness may produce fairer outcomes - What privacy, fairness, robustness, and trust mean in practice - Who currently decides the trade-offs built into AI systems - Why AI governance should focus on products, sectors, and consequences - How the post-ChatGPT boom changed AI research and graduate training - Why access to a chatbot is not the same as democratic control - What agency and representation would add to AI governance - Why government and education are struggling to match AI’s pace - How community-led action could fill the institutional gap Chapters: 00:00 The one research idea Nidhi would keep 01:50 Privacy, fairness, robustness, and trust 04:54 The unavoidable trade-offs in trustworthy AI 07:54 What Canada gets wrong about AI policy 10:19 Why AI governance should regulate products and sectors 15:11 How the ChatGPT boom changed AI research 22:51 Why Nidhi rejects “democratized AI” 24:39 What democratic AI would actually require 26:18 Should AI become a national political question? 31:34 Building national AI literacy 35:32 Why institutions cannot match AI’s pace 38:54 Community action when government falls behind 41:09 The missing intervention 42:07 What gives Nidhi hope 43:29 Where to follow Nidhi’s work Connect with Nidhi: Amii profile: https://www.amii.ca/people/nidhi-hegde University of Alberta: https://apps.ualberta.ca/directory/person/nidhih Research website: https://sites.google.com/view/nidhihegde Podcast: Spotify: https://open.spotify.com/show/1ILhje5HSua1FEOlTyFAhG Apple Podcasts: https://apple.co/3qXL37W Connect with Ayush: Website: https://ayushprakash.com LinkedIn: https://www.linkedin.com/in/prakash-ayush/ Instagram: https://instagram.com/ayushprakashofficial Book: AI for Gen Z: https://www.amazon.com/dp/0981182135

July 13, 2026Episode 16635 min

Fenwick McKelvey: Canada Helped Build Modern AI. Why Can’t It Control What Comes Next?

Fenwick McKelvey joins the podcast to explain why Canada’s AI problem runs deeper than research funding or regulation. Canada helped sustain the ideas behind modern AI and launched an early national strategy, yet it still struggles to turn that history into independent industry, enforceable public accountability, and a clear position between the United States, China, and the European Union. Fenwick breaks down the difference between regulation, policy, and governance; how hype shapes investment and news coverage; why a small number of companies already make rules for the public; and why strengthening existing institutions may matter more than building another AI regulator. We also discuss ChatGPT in higher education, open models, proactive regulation, political privacy, and the technology he is watching after AI. Fenwick McKelvey is an associate professor in Communication Studies at Concordia University. His research covers digital politics, internet policy, algorithmic media, and AI governance. His book *SimPolitics: America’s Quest to Solve Politics with Computers* was published by the MIT Press in 2026. Chapters: 00:00 Why Parliament testimony rarely becomes policy 01:28 Regulation, policy, and governance explained 04:38 Governing AI when nobody knows its real impact 08:04 Should governments regulate AI hype? 11:06 Did Canada build AI and lose the industry? 14:14 Regulation is not Canada’s innovation problem 17:00 Where Canada fits between the US, China, and EU 20:31 Fenwick’s AI governance wish list 25:01 Is ChatGPT ruining higher education? 27:07 How students actually use AI 30:10 Can regulation get ahead of technology? 32:35 The next disruption after AI: quantum 34:44 SimPolitics and where to follow Fenwick Connect with Fenwick: Website: https://www.fenwickmckelvey.com/ Concordia profile: https://www.concordia.ca/faculty/fenwick-mckelvey.html SimPolitics: https://mitpress.mit.edu/9780262053198/simpolitics/ Podcast Info: Spotify: https://open.spotify.com/show/1ILhje5HSua1FEOlTyFAhG Apple Podcasts: https://apple.co/3qXL37W Connect: Website: https://ayushprakash.com LinkedIn: https://www.linkedin.com/in/prakash-ayush/ Instagram: https://instagram.com/ayushprakashofficial Books: AI for Gen Z: https://www.amazon.com/dp/0981182135

June 17, 2026Episode 16537 min

Matthew Guzdial: What Happens When Cheap AI Disappears?

What happens when the AI tools you rely on stop being cheap? Matthew Guzdial argues that becoming dependent on today’s generative AI could leave people and businesses exposed if prices rise or providers disappear. Matthew is an associate professor of Computing Science at the University of Alberta. We discuss AI’s role in game design, why players object to generative AI, and why synthetic data can’t supply missing ground truth in his research. He explains his prediction of an AI bubble and what he thinks could survive it. The conversation also covers VR’s adoption problems, Roblox and child safety, platform accountability, and how to talk to children about screens. We finish with his advice for young people trying to decide what to do with their lives. His market forecasts and parenting observations are his views, not established outcomes or clinical guidance. Chapters: 00:00 Introduction: what makes a good game? 02:12 AI in games before ChatGPT 03:42 Concept art, coding and generative AI 05:48 Why players push back against AI 08:27 The risk of relying on cheap AI 11:41 What could follow an AI bubble? 16:10 Small datasets and synthetic data 17:28 AI winters and the road to AGI 19:08 Escapism, Roblox and child safety 21:04 Why VR struggles with adoption 23:17 How marketing shapes technology expectations 24:53 Should children be banned from games? 28:53 Parenting, screens and autonomy 34:24 Advice for young people 35:47 What gives Matthew hope 36:35 Where to follow Matthew and his games Connect with Matthew: Website: https://guzdial.com/ University profile: https://apps.ualberta.ca/directory/person/guzdial Bluesky: https://bsky.app/profile/matthewguz.bsky.social Google Scholar: https://scholar.google.com/citations?user=jKqmTbIAAAAJ Podcast Info: Spotify: https://open.spotify.com/show/1ILhje5HSua1FEOlTyFAhG Apple Podcasts: https://podcasts.apple.com/ca/podcast/ayush-prakash-podcast/id1557703631 Connect: Website: https://ayushprakash.com LinkedIn: https://www.linkedin.com/in/prakash-ayush/ Instagram: https://instagram.com/ayushprakashofficial Books: AI for Gen Z: https://www.amazon.com/dp/0981182135

June 7, 2026Episode 16440 min

Nick Hunt: The Stories We Tell Ourselves Are Killing Us

What if the first honest response to ecological collapse is admitting that we may not know how to fix it? Writer and Dark Mountain Project co-director Nick Hunt explains why climate change, mass extinction and cultural alienation cannot be reduced to engineering problems, and why accepting loss does not have to mean giving up. We discuss the disappearance of the Aral Sea, the surprising life emerging from its exposed seabed and the difficulty of forcing every story into hope or despair. Nick reflects on humanity’s capacity for destruction, the possibility of leaving good traces and why he turns to art to create meaning in a damaged world. The conversation then turns to writing, artificial intelligence, travel and the value of getting lost. Nick explains why human-made art still matters, why he writes to think instead of delivering a final truth and what different cultures can teach us about purpose, time and simply being. We finish with speculative fiction, hope beyond hope and the message he would give his future self. Chapters: 00:00 What is the Dark Mountain Project? 03:55 Why technology cannot solve every crisis 08:09 What remains after the Aral Sea disappears 14:04 Hope, despair and humanity’s destructive side 18:03 Why Nick turns to art instead of destruction 19:50 What is the point of writing if we are doomed? 24:36 Writing what the world may not be ready for 26:06 Travel, writing and the value of getting lost 27:52 Why modern life cannot tolerate aimlessness 31:43 Presence, creativity and the pressure to succeed 33:21 Hope beyond hope 36:26 Why there is no magic-wand solution 38:02 What Nick would tell his future self 39:14 Where to follow Nick Hunt Connect with Nick: Website: https://nickhuntscrutiny.com Dark Mountain: https://dark-mountain.net Podcast Info: Spotify: https://open.spotify.com/show/1ILhje5HSua1FEOlTyFAhG Apple Podcasts: https://apple.co/3qXL37W Connect: Website: https://ayushprakash.com LinkedIn: https://www.linkedin.com/in/prakash-ayush/ Instagram: instagram.com/ayushprakashofficial Books: AI for Gen Z: https://www.amazon.com/dp/0981182135

May 22, 2026Episode 16349 min

The Source Intelligence Beyond Your Mind - Adam Dickinson

Adam Dickinson joins the podcast to break down what intuition actually is, why logic alone is one of the most limiting and overlooked barriers to human potential, and what it means that most of us are operating from only a fraction of our true consciousness. We also get into the spiritual frameworks that can expand the way you think and feel, and what Adam believes it will take for humanity to evolve beyond the mind and into a deeper intelligence. Connect with Adam: LinkedIn: https://www.linkedin.com/in/adam-r-dickinson/ Podcast Info: Spotify: https://open.spotify.com/show/1ILhje5HSua1FEOlTyFAhG Apple Podcasts: https://apple.co/3qXL37W Connect: Website: https://ayushprakash.com LinkedIn: https://www.linkedin.com/in/prakash-ayush/ Instagram: instagram.com/ayushprakashofficial Books: AI for Gen Z: https://www.amazon.com/dp/0981182135

April 27, 2026Episode 1621 hr 3 min

We Have Microplastics in Our Brains (And How We Remove Them) - David Roberts

David Roberts of Mara Labs joins the podcast to break down what microplastics are, why air is one of the biggest and most overlooked sources of exposure, and what it means that most of us are consuming the equivalent of a credit card's worth of plastic every week. We also get into concrete lifestyle changes you can make right now to reduce your intake, and what Mara Labs is building to tackle the problem at scale. Connect with David: LinkedIn: https://www.linkedin.com/in/david-roberts-7170416/ Website: https://mara-labs.com Podcast Info: Spotify: https://open.spotify.com/show/1ILhje5HSua1FEOlTyFAhG Apple Podcasts: https://apple.co/3qXL37W Connect: Website: https://ayushprakash.com LinkedIn: https://www.linkedin.com/in/prakash-ayush/ Instagram: instagram.com/ayushprakashofficial Books: AI for Gen Z: https://www.amazon.com/dp/0981182135