Jennifer Neville, who initially had no interest in computer science, found herself in the field and has since focused on uncovering the unexpected failures that challenge AI’s ability to manage complexity. In her article, she reflects on the career path that led her to this niche, highlighting the moments of both progress and setbacks that shaped her work. The piece emphasizes how these surprising failures reveal the limits of current AI systems.
By Chad Atalla, Jennifer Neville
Lab Director Chris White discusses his research on real‑world problems, including wartime data analysis and tools to fight human trafficking. He explains the influences that guided his work and shares insights with program manager Weishung Liu. The conversation highlights how technology and research can drive positive societal impact.
By Weishung Liu, Chris White
The article examines how AI policies implemented by software organisations affect developers, using insights from 19 interviews. It finds that while such policies aim to reduce risks like data leaks and unauthorized use, they can also impede developers if not properly engaged. The authors propose developer‑centric strategies to help managers and decision makers implement effective AI policies.
By Samuel Ferino, Rashina Hoda, John Grundy, Christoph Treude, Hashini Gunatilake
Microsoft Research Focus – Edition #97 features host Sowbhagya Suresh discussing recent developments across Microsoft. Topics include challenges faced by coding agents, insights into how people use AI at work, and advancements in extended‑range weather forecasting. The episode highlights cutting‑edge research and practical applications within the company.
By Sowbhagya Suresh
Because the alternative is much too dangerous The post We Should Train AI to Betray Its Users appeared first on Towards Data Science .
By Nathan Bos
How to set the rules that keep agents effective and out of trouble The post What AI Agents Should Never Do on Their Own appeared first on Towards Data Science .
By Sara Nobrega
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:2607. 19941v1 Announce Type: cross Abstract: As AI agents become integral to business workflows, establishing guiding user experience (UX) principles is crucial for ensuring user trust and successful adoption.
By Kathrin Paimann, Elizangela Valarini, Sebastian Juhl
arXiv:2607. 09954v1 Announce Type: cross Abstract: Hardening IT on-premises environments can be a daunting task for teams without access to adequate cybersecurity expertise.
By Carolina Fern\'andez-Mart\'inez, Shuaib Siddiqui, Vanesa Daza
arXiv:2604. 09998v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have recently emerged as promising tools for augmenting Security Operations Center (SOC) workflows, with vendors increasingly marketing autonomous AI solutions for SOCs.
By Souradip Nath, Chih-Yi Huang, Aditi Ganapathi, Kashyap Thimmaraju, Jaron Mink, Gail-Joon Ahn
arXiv:2608. 05656v1 Announce Type: cross Abstract: Safety risks of AI are becoming increasingly evident in human interactions with AI technologies.
By Jessica Y. Bo, Paula Akemi Aoyagui, Shalaleh Rismani, Dipto Das, Syed Ishtiaque Ahmed, Ashton Anderson
arXiv:2408. 02379v2 Announce Type: replace-cross Abstract: Developing and certifying safe - or so-called trustworthy - AI has become an increasingly salient issue, especially in light of upcoming regulation such as the EU AI Act.
By Benjamin Fresz, Vincent Philipp G\"obels, Safa Omri, Danilo Brajovic, Andreas Aichele, Janika Kutz, Jens Neuh\"uttler, Marco F. Huber