AI-Curious with Jeff Wilser

What happens when an AI prediction does not just forecast the future, but helps create it?
In this episode of AI-Curious, we talk with philosopher and ethicist Carissa Véliz about AI ethics, AI privacy, predictive AI, and the hidden power of algorithmic decision-making. We explore how AI systems used in hiring, lending, insurance, and other high-stakes settings can become self-fulfilling prophecies, shaping outcomes rather than simply measuring them.
We also examine the growing privacy risks of large language models and AI agents, especially as they gain access to more personal data, communications, and systems. Along the way, we discuss automated decision-making, surveillance, human autonomy, and why predictions about people are far more ethically fraught than predictions about things like the weather.
This conversation also goes beyond policy and into philosophy: how narratives about AI shape public thinking, why humor can be a response to technological power, and how individuals and companies can use AI responsibly without giving up judgment, control, or resilience.
If you are interested in AI ethics, algorithmic bias, AI privacy, AI agents, responsible AI, predictive algorithms, self-fulfilling prophecy, and the future of AI, this episode offers a clear and thought-provoking framework for understanding what is at stake.
Guest
Carissa Véliz — Philosopher, Associate Professor at the Institute for Ethics in AI at the University of Oxford, and author of Prophecy, Prediction, Power, and the Fight for the Future: From Ancient Oracles to AI
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What if the job you have today will soon require a completely different set of skills? 
In this episode of AI-Curious, we talk with Dan Roth, Editor in Chief of LinkedIn, about what LinkedIn’s data reveals about the future of work, the rise of AI literacy, and why deeply human skills may matter more than ever. We dig into LinkedIn’s “Skills on the Rise” research, what employers are actually looking for now, and why the shift toward skills-based hiring is changing how people get hired, promoted, and evaluated.
We also explore the surprising rise of storytelling, public speaking, conflict resolution, and stakeholder communication in an AI-driven workplace. Along the way, we discuss why traditional resumes and polished cover letters may matter less in a world where anyone can use AI to sound impressive, and why some companies are moving toward live prototyping and real-time problem solving in interviews instead.
Later, we get into AI agents, what Dan is building himself, and how leaders can create stronger AI adoption inside their companies. We also talk about what it takes to stay competitive in a job market where AI is changing the stack of work, but not necessarily replacing the worker.
Guest
Dan Roth — Editor in Chief, LinkedIn
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For anyone interested in Jeff’s AI Workshops for their company:
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What does it actually look like to use AI tools in the real world, beyond the usual chatbot prompts and hype?
In this episode of AI-Curious, Jeff Wilser shares five AI tools and workflows that are shaping how he works right now, from Claude Code and personalized news briefings to NotebookLM, multi-model prompting, and using AI to write more closely in your own voice. The goal is not to offer a comprehensive list of every AI product on the market, but to show how these tools can be used in practical ways that expand capability, streamline research, and create new workflows.
We explore how vibe coding and AI agents can help non-coders build useful internal tools, why personalized AI news feeds may become increasingly common, and how NotebookLM can synthesize large amounts of information across transcripts, documents, and YouTube videos. We also look at the benefits of using multiple AI models together instead of relying on just one, and why feeding AI much richer context can dramatically improve writing outputs.
Throughout the episode, we return to a core idea: using AI to empower, not eliminate. Rather than treating AI only as a cost-cutting tool, we examine how it can help individuals and businesses do more, think more creatively, and build smarter systems around the work that matters most.

Key topics we cover
3:15 — Claude Code, vibe coding, and why non-coders should be paying attention
6:01 — Building a custom AI-powered conference outreach and research tool
11:05 — “AI to empower, not eliminate” as a guiding philosophy
16:16 — Personalized AI news briefings and the future of customized information
21:58 — How NotebookLM helps synthesize transcripts, documents, and YouTube content
27:04 — Why a “polymodel” approach can be better than relying on one chatbot
31:15 — Using AI to write more closely in your own voice through deeper context
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For anyone interested in Jeff’s AI Workshops for their company:
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What happens when AI stops being a productivity tool and starts reshaping the structure of work itself?
In this episode of AI-Curious, we talk with Kelly Monahan, a future of work and AI advisor, about what AI may actually do to the workplace over the next few years, and why the reality is likely to be messier than both the hype and the fear suggest. We dig into the tension between using AI for augmentation versus automation, why so many companies are still struggling to prove ROI, and how AI agents could transform business workflows while also creating major governance, accountability, and implementation challenges.
We also explore what this means for knowledge workers, middle managers, and enterprise leaders trying to adapt in real time. Along the way, we discuss why small businesses may have an advantage over large organizations, how workers can focus on higher-value contributions, and why the future of work may require not just new tools, but a new mindset.

Guest
Kelly Monahan — Future of Work and AI Advisor

Key topics we cover
2:49 — Kelly’s optimistic and pessimistic theses on the future of work
5:15 — Where AI is overhyped, and the disconnect between leaders and workers
6:35 — Why generative AI adds complexity inside organizations
10:05 — What the research says about AI ROI
12:54 — Where AI is delivering real wins today, especially for freelancers and small businesses
16:27 — Advice for leaders and middle managers inside large organizations
18:39 — Why curiosity, learning, and experimentation need to be rewarded
19:02 — AI agents, the hype cycle, and why the excitement may still be justified
22:25 — Why enterprises are struggling to keep pace with the speed of AI change
29:18 — What the future of work may look like over the next 3 to 5 years
30:02 — Why white-collar work could face major disruption
33:37 — The “elevator to skyscraper” analogy for how AI should reshape work
35:08 — Predictions for AI adoption, governance failures, and labor market shifts
39:00 — How Kelly uses AI in her own work and business

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For anyone interested in Jeff’s AI Workshops for their company:
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What happens when a business school decides AI isn’t a bolt-on elective, but the operating system for how students learn marketing, finance, entrepreneurship, and leadership?
In this episode of AI-Curious, we’re back with David Marchick, Dean of the Kogod School of Business, to see what changed after his earlier promise to become the country’s first AI-first business school. We dig into what “AI-first” actually means in practice, what worked (and what failed), and how a culture of experimentation turned AI adoption from a handful of pilots into a school-wide shift.
We also tackle the most unavoidable issue in education right now: cheating. David shares Kogod’s approach to disclosure, ethics, group work, oral exams, and why “blue books” may be making a comeback. From there, we zoom out to the bigger stakes: the existential threat AI poses to universities, how the higher ed business model may change, and what skills still matter when AI can generate content on demand.

Guest
David Marchick — Dean of Kogod School of Business
Key topics we cover
3:56 — The “tipping point”: how AI moved from experiments to 90% of faculty using it
7:16 — What “AI-first business school” really means: AI + fundamentals + “power skills”
10:32 — Cheating and assessment: disclosure statements, prompts, oral exams, blue books
16:51 — A prompts-only entrepreneurship course and what personalized learning could become
22:06 — Non-technical students building apps and graduating with an AI-driven portfolio
23:38 — Practicing negotiations against AI counterparts with different personalities
25:04 — Agentic workflows as a management tool, not just a technical novelty
29:13 — The university headwinds: demographic cliff, international enrollment, funding, AI
38:58 — Leadership lessons: top-down AI culture plus bottom-up workflow redesign
40:42 — How David uses AI personally, including Tour de France route training plans
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For anyone interested in Jeff’s AI Workshops for their company:
Reach out directly at [email protected]