Towards Data Science

Meta-Cognitive Regulation Might Be the Most Important AI Skill Nobody Is Talking About

As AI gets smarter, the real differentiator may be how well humans regulate their own thinking. The post Meta-Cognitive Regulation Might Be the Most Important AI Skill Nobody Is Talking About appeared first on Towards Data Science .

Towards Data Science
Jul 10

The Big Con of Agentic AI

What our over-dependence on external consulting teaches us about delegating our minds to machines The post The Big Con of Agentic AI appeared first on Towards Data Science .

By Chinmay Kakatkar
Hugging Face Trending Papers
Jul 13

Bringing Back Rule Induction to Fluid Intelligence Research? An Initial Validation of the ARC-AGI Benchmark in Humans

Two competing perspectives on fluid intelligence (gf) measures propose that performance is primarily constrained either by working memory capacity or by the ability to induce novel relations. The first perspective is currently dominant in measurement, as evident from the use of a limited set of recurring rules, whereas the second perspective is reflected in many definitions but rarely present in measurement.

arXiv AI
Jul 9

Measuring the metacognition of AI

arXiv:2603. 29693v3 Announce Type: replace Abstract: A robust decision-making process must take into account uncertainty, especially when the choice involves inherent risks.

By Richard Servajean, Philippe Servajean
arXiv AI
Jun 16

Artificial Intelligence Index Report 2026

arXiv:2606. 15708v1 Announce Type: new Abstract: Welcome to the ninth edition of the AI Index report.

By Sha Sajadieh, Loredana Fattorini, Raymond Perrault, Yolanda Gil, Vanessa Parli, Lapo Santarlasci, Juan Pava, Nestor Maslej, Russ Altman, Erik Brynjolfsson, Carla Brodley, Jack Clark, Virginia Dignum, Vipin Kumar, James Landay, Terah Lyons, James Manyika, Juan Carlos Niebles, Yoav Shoham, Elham Tabassi, Russell Wald, Toby Walsh, Dan Weld
arXiv AI
Jun 3

A formal definition and meta-model for a machine theory of mind

arXiv:2606. 03471v1 Announce Type: new Abstract: This paper proposes, for the first time, a rigorous formal definition of the concept of Machine Theory of Mind, based on principles supported by evidence from cognitive psychology, neuroscience and artificial intelligence, and uses the above as a lens to examine state-of-the-art and current efforts in the field, driving a potential agenda for further research there able to "crack" the problem.

By Fabio Cuzzolin