Artificial Intelligence and You

This and all episodes at: https://aiandyou.net/ .

I am talking with Rob May, Co-Founder and CEO of NeuroMetric AI, optimizing inference for multi-model AI systems, and returning to the show after 5 years. We're making sense of how rapid advances in AI—especially the shift from training to real-world inference—are reshaping work, business strategy, and the roles of humans. They accelerate productivity while increasing cognitive demands and redefining where human judgment still matters.

A serial entrepreneur, Rob has founded and scaled multiple successful companies including Backupify, Talla, Dianthus, and BrandGuard. He’s also an active angel investor with over 100 portfolio companies and brings firsthand insight into the evolution of AI entrepreneurship. His expertise lies at the intersection of AI research, applied inference, and startup strategy. He is also the co-host of the AI in NYC Show, where he discusses the latest breakthroughs in AI infrastructure and reasoning with top founders, investors, and researchers.

We conclude the interview by talking about AI processing on local devices, natural limits to automation, the shift in competitive advantage from execution to creativity, and restructuring of the economy and the workforce. 

All this plus our usual look at today's AI headlines!

Transcript and URLs referenced at HumanCusp Blog.

This and all episodes at: https://aiandyou.net/ .

Rapid advances in AI—especially the shift from training to real-world inference—are reshaping work, business strategy, and the roles of humans. They accelerate productivity while increasing cognitive demands and redefining where human judgment still matters. Here to help us get a handle on that and returning to the show after five years is Rob May, Co-Founder and CEO of NeuroMetric AI, a pioneering company optimizing inference for multi-model AI systems. A serial entrepreneur, Rob has founded and scaled multiple successful companies including Backupify, Talla, Dianthus, and BrandGuard. He’s also an active angel investor with over 100 portfolio companies and brings firsthand insight into the evolution of AI entrepreneurship. His expertise lies at the intersection of AI research, applied inference, and startup strategy. He is also the co-host of the AI in NYC Show, where he discusses the latest breakthroughs in AI infrastructure and reasoning with top founders, investors, and researchers.

We talk about how the bottleneck in business is shifting from labor to cognition, the paradoxical way AI is increasing workloads and cognitive strain, the rise of inference as the core AI economy, and how infrastructure constraints are pushing towards a more distributed AI ecosystem.

All this plus our usual look at today's AI headlines!

Transcript and URLs referenced at HumanCusp Blog.

This and all episodes at: https://aiandyou.net/ .

AI abounds with paradoxes.  I have been talking about those with Virginia Dignum, professor of responsible artificial intelligence at Umeå (OOMEO) university, about her new book, The AI Paradox: How to Make Sense of a Complex Future, just released, with links in the show notes and transcript. Virginia is an internationally recognized expert in AI ethics and policy who has led initiatives for the European Commission, the United Nations, the World Economic Forum, UNESCO, and UNICEF, among others, and is the author of the 2019 book Responsible Artificial Intelligence.

We conclude the interview by talking about some paradoxes in detail, like Moravec’s Paradox, questions about using AI in legal decisions, AI literacy, and the recent battle between Anthropic and the US Department of Defense, and OpenClaw.

All this plus our usual look at today's AI headlines!

Transcript and URLs referenced at HumanCusp Blog.

This and all episodes at: https://aiandyou.net/ .

AI runs not just broadly across human interest, but deeply. And at every level it seems to create paradoxes. How can it be useful without power; how can it be safe with power. We want it to take over jobs, but still leave us with meaning and purpose. We deny it the possibility of becoming sentient, but how can we trust something that lacks compassion? My guest today has written a whole book on these paradoxes. Calling from Sweden is Virginia Dignum, professor of responsible artificial intelligence at Umeå University, and the author of the 2019 book Responsible Artificial Intelligence. She’s an internationally recognized expert in AI ethics and policy who has led initiatives for the European Commission, the United Nations, the World Economic Forum, UNESCO, and UNICEF, among others. And we are talking about her new book, The AI Paradox: How to Make Sense of a Complex Future.

We talk about the issues of ethical choices and power that AI raises, where the difference between humans and LLMs matters, Viriginia’s path to the work she’s doing and her book, and our trend to techno-solutionism and what it means for us.

All this plus our usual look at today's AI headlines!

Transcript and URLs referenced at HumanCusp Blog.

This and all episodes at: https://aiandyou.net/ .

Have you ever thought about your thoughts? About what or how you’re thinking? It gets real meta real fast, doesn’t it? That’s called metacognition, and humans and certain other creatures do it. But what about AI? We’re coming back to the interview with Ricky Sethi, Professor of Computer Science at Fitchburg State University, and researcher into artificial metacognition, or whether and how machines can think about thinking. Ricky’s research spans fact-checking misinformation, virtual communities, and artificial metacognition, where he focuses on designing GenAI systems that can monitor, evaluate, and regulate their own reasoning. He is Director of Research for the Madsci Network, and an Adjunct Professor at Worcester Polytechnic Institute. He has over 50 scholarly publications, and his work has been covered in outlets such as the Chicago Tribune, The Conversation, and Communications of the ACM.

We conclude the interview by talking about his research into disinformation, measuring the emotions associated with it, how clusters of models in different roles could assess AIs for lying and implement AI safety, and how AI is impacting the job opportunities in research.

All this plus our usual look at today's AI headlines!

Transcript and URLs referenced at HumanCusp Blog.