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
Sep 25

10 Things I’m Learning Beyond AI to Become More Technologically Fluent

The article titled "10 Things I’m Learning Beyond AI to Become More Technologically Fluent" discusses the author's exploration of various technologies that are shaping the future, beyond just artificial intelligence. It is presented as part one of a series, focusing on understanding these emerging technologies and their impact.

By Rashi Desai
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
arXiv AI
6d ago

Cognitive Skills in the Age of AI: Computing Students and Experts Perceptions

The study examines how AI’s growing presence in computing affects the perceived importance of cognitive skills among students and experts. Findings suggest that most cognitive skills will become less critical in an AI‑rich future, while critical thinking remains essential. Interviews provide reasons for these shifts and offer guidance for preparing future computing students.

By Neha Rani, Vu Minh Anh Le, Austin M. Spangler, Erta Cenko
Towards Data Science
Sep 1

5 AI Skills That Will Keep Data Scientists Relevant in 2027

The article titled "5 AI Skills That Will Keep Data Scientists Relevant in 2027" outlines five specific AI competencies, explaining what each skill addresses and providing runnable code snippets that readers can directly paste into a notebook. It serves as a practical guide for data scientists aiming to stay current with emerging AI technologies.

By Sara Nobrega
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
Towards Data Science
Sep 22

4 Ways to Use AI on a PhD Thesis

The article outlines four practical applications of AI for PhD students: locating relevant citations, consolidating code snippets, fact‑checking research claims, and preparing for the thesis defence. It highlights how AI tools can streamline the research process and improve the quality of academic work.

By Conor O'Sullivan
Towards Data Science
Aug 27

Agentic AI Is Rewriting The Analytics Stack But There's One Skill It Still Can't Touch

The article discusses how agentic AI is reshaping the analytics stack by taking over more execution tasks. It raises the question of which responsibilities should remain with human analysts versus AI agents and explores the importance of this distinction. The piece highlights the evolving role of AI in analytics and the need to define clear boundaries between human and machine work.

By Rashi Desai