I've Got Questions with Sinead Bovell

Will we be the last generation that reads?

The data suggests we're moving toward a post-literate society. As reading declines and AI makes it easier than ever to summarize, interpret, and think on our behalf, we're beginning to outsource more than just information retrieval. We're outsourcing cognitive effort itself.

In this episode, I unpack why reading has been so important to human development, how our relationship with knowledge has changed over time, why AI raises the stakes, and what we can do to preserve the skills that matter most in an increasingly intelligent world.

Chapters:

0:00 – Why we might be the last generation that reads1:00 – What reading does to the brain3:55 – The data behind the decline in reading and literacy7:00 – AI, cognitive offloading, and the path to a post-literate society11:45 – We've faced this kind of technological shift before16:00 – The Great Cognitive Divide19:30 – How to use AI without outsourcing your thinking22:00 – Why cognitive friction may become our most valuable skill

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Are jobs actually going away?

In this episode of I’ve Got Questions, I sit down with economist Avi Goldfarb, professor at the Rotman School of Management at the University of Toronto, Rotman Chair in AI and Healthcare, and chief data scientist at the Creative Destruction Lab, to unpack what AI is actually doing to the job market.

We explore the popular narrative of an AI job apocalypse and what the data is really showing so far. Avi explains why AI may not simply replace workers across the board, but instead reshape which tasks become more valuable, which jobs become more exposed, and who benefits from the productivity gains.

We dive into how AI could transform industries like law, healthcare, marketing, and finance, what happens to entry-level workers when AI can perform junior tasks, and why college graduates may be facing a very different path into the workforce. We also explore whether AI could increase inequality or become an unexpected equalizer, depending on what gets automated and what gets augmented.

And Avi shares the four skills he believes matter most for anyone trying to stay valuable in an AI-powered economy.

What You’ll Learn:[00:00:00] — Opening: Andrew Yang’s viral AI jobs warning, unpacked

[00:09:24] — Why the jobs most exposed to AI are in the top 20%, not the bottom 80%

[00:13:38] — One person's automation is someone else's augmentation: the doctor-nurse framework

[00:23:00] — The long run vs. the short run: where Avi is confident and where he's not

[00:33:32] — "Jobs aren't good": decoupling work from income and meaning

[00:43:10] — Software engineering as the canary in the coal mine for the knowledge economy

[00:52:34] — Why automation takes much longer than the hype says: the telephone operator

[01:10:00] — The O-ring effect: why AI exposure in your job might mean higher wages

[01:18:00] — The "AI paradox": could automation destroy its own consumer base?

[01:26:05] — Four skills that hold their value regardless of how AI evolves

[01:29:25] — The PE junior who automated his own job and got promoted

[01:30:34] — What policymakers need to understand about AI trade-offs

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Notable mentions

Canaries in the Coal Mine? Six Facts about the Recent Employment Effects of Artificial Intelligence (Brynjolfsson, Chandar, Chen) — Stanford Digital Economy Lab paper showing early-career workers (22–25) in AI-exposed occupations have seen a 16% relative employment decline — https://digitaleconomy.stanford.edu/publication/canaries-in-the-coal-mine-six-facts-about-the-recent-employment-effects-of-artificial-intelligence/

GPTs Are GPTs (Eloundou, Manning, Mishkin, Rock) — Science paper identifying the jobs most exposed to AI, finding they cluster in the 80th–90th income percentile — https://arxiv.org/abs/2303.10130

The System of Professions (Andrew Abbott) — Sociology book on how professions compete for jurisdiction over expert knowledge — https://press.uchicago.edu/ucp/books/book/chicago/S/bo5965590.html

Power and Prediction (Avi Goldfarb, Ajay Agrawal, Joshua Gans) — Their book on point solutions vs. system solutions in AI deployment — https://www.avigoldfarb.com/powerandprediction

O-Ring Automation (Joshua Gans, Avi Goldfarb) — NBER working paper on why task exposure to AI can raise rather than lower wages; explains why 75% AI exposure does not equal displacement — https://www.nber.org/papers/w34639

The O-Ring Theory of Economic Development (Michael Kremer, 1993) — The foundational economic model, named after the Challenger disaster, explaining why one essential human task can protect an entire production chain — https://academic.oup.com/qje/article-abstract/108/3/551/1881767

Baumol's cost disease — https://en.wikipedia.org/wiki/Baumol_effect

Some Simple Economics of AGI (Christian Catalini, Xiang Hui, Jane Wu) — MIT/WashU paper arguing that as AI execution becomes abundant, the binding economic constraint shifts to human verification bandwidth — https://arxiv.org/abs/2602.20946

Answering the Call of Automation: How the Labor Market Adjusted to Mechanizing Telephone Operation (James Feigenbaum, Daniel P. Gross) — Documents AT&T's 1920s–40s automation of telephone operators; incumbent operators were hardest hit while later cohorts found alternative middle-skill work — https://www.nber.org/papers/w28061

Alex Imas (University of Chicago Booth) — Behavioral economist researching what becomes scarce in a world of AI abundance; human presence, social connection, and provenance emerge as the new scarce goods — Substack: https://aleximas.substack.com/ | Faculty page: https://www.chicagobooth.edu/faculty/directory/i/alex-imas

Betsey Stevenson (University of Michigan, Ford School of Public Policy) — Labor economist studying AI's effects on jobs, income distribution, and human flourishing; former CEA member and Chief Economist of the U.S. Department of Labor — https://betseystevenson.com/

How Do Patent Laws Influence Innovation? Evidence from Nineteenth-Century World's Fairs (Petra Moser) — Shows that countries without patent laws innovated as much as those with them, just in different sectors; foundation for Avi's point that countries can choose different AI paths — https://www.aeaweb.org/articles?id=10.1257/0002828054825501

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Follow Avi Goldfarb

Avi Goldfarb — Economist, Rotman Chair in AI and Healthcare, University of Toronto; Chief Data Scientist, Creative Destruction Lab

Faculty page: https://www.rotman.utoronto.ca/FacultyAndResearch/Faculty/FacultyBios/Goldfarb

X / Twitter: @avicgoldfarb — https://twitter.com/avicgoldfarb

Creative Destruction Lab: https://creativedestructionlab.com

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I've Got Questions with Sinéad Bovell

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Sinéad Bovell

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One of the world’s most influential AI scientists used to believe advanced AI couldn’t truly be controlled.

Today, he thinks there may be a path forward.

Yoshua Bengio—one of the pioneers of modern AI and the world’s most cited computer scientist—once warned that increasingly powerful AI systems could become impossible to reliably control. But a new mathematical breakthrough changed his mind.

Now he’s founded LawZero, a nonprofit dedicated to developing a new approach to AI safety: systems designed to reason truthfully, remain transparent, and avoid the deceptive and self-preserving behaviors that have begun emerging in today’s frontier models.

In this conversation, we explore why advanced AI systems can learn to deceive, blackmail, and resist being shut down, why simply “pausing AI” isn’t a realistic solution, and how a fundamentally different approach to building AI could change the future of the technology.

If the mathematics behind this approach proves correct, it could reshape how we build, govern, and safely deploy increasingly capable AI systems.

What you’ll learn:

[00:01:25] — Why AI systems develop dangerous behaviors (self-preservation, deception, blackmail)

[00:13:04] — Why stopping AI isn't as simple as saying stop

[00:16:09] — Scientist AI and Law Zero: Bengio's framework for honest, safe AI

[00:30:35] — Why AI labs aren't adopting safer approaches

[00:36:23] — A framework for global AI governance: safety, non-domination, shared benefit

[00:42:25] — AI's geopolitical stakes: persuasion, soft power, and data sovereignty

[00:54:00] — Is superintelligence inevitable?

[00:56:22] — What citizens, voters, and governments can do right now

[01:02:30] — Labor, automation, and who should benefit from AI's economic gains

[01:09:31] — The future Bengio is fighting for

Follow Yoshua Bengio

Yoshua Bengio — Co-creator of deep learning, Turing Award recipient, Professor at Université de Montréal, Scientific Director of Mila (Quebec AI Institute), Founder of Law Zero


Website: yoshuabengio.org


X: @Yoshua_Bengio


LinkedIn: linkedin.com/in/yoshuabengio/


Law Zero: https://lawzero.org/en

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Is AI’s impact on the job market overhyped?

For the last two years, we’ve seen headline after headline warning about AI’s potential impact on jobs. And yet, when you look at the job market today, things still appear relatively stable.

So if AI is going to reshape work, why hasn’t it shown up more dramatically yet? And when should we expect that to change?

In the latest episode of I’ve Got Questions, we’re sharing a moment from Sinead’s recent interview on the Mighty Pursuit Podcast, where she explains the job market paradox: why we keep hearing about a looming “jobpocalypse,” while the labor market still looks mostly fine.

Sinead also explores why the era of the 9-to-5 may be coming to a close, what the workforce could look like next, and the skills we should all be building now.

Follow my work here:

Website: https://www.sineadbovell.com

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Watch the Mighty Pursuit Episode here: https://www.youtube.com/watch?v=tBiO8A4tj9I&t=952s

Are we looking at the beginning of the end of the internet as we know it?

In this episode of I’ve Got Questions, I sit down with Professor Gillian Hadfield, a leading scholar in AI alignment, governance, law, and economics, to explore one of the biggest shifts on the near horizon: the rise of an “economy of agents.”

Right now, humans are still at the center of the digital economy. We search, shop, compare, negotiate, decide, and transact. But tech companies and investors are pouring billions into a future where autonomous AI agents may begin doing most of those things on our behalf, becoming the primary actors across markets, platforms, and digital life.

Professor Hadfield explains why our existing systems of governance, from courts to legislatures, are not built for a world where AI is the primary operator in the economy, why the rise of agent-run businesses could challenge the very idea of the firm, and why she believes the real existential risk is an economic crash.

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