arXiv:2606. 12587v1 Announce Type: new Abstract: Traditionally, decision support studies how humans use machine learning models to make better decisions.
By Shayan Kiyani, Sima Noorani, George Pappas, Hamed Hassani
arXiv:2607. 03025v1 Announce Type: new Abstract: The use of Large Language Models (LLMs) across diverse areas of human activity-ranging from everyday tasks to safety-critical applications-aims to enhance decision-making effectiveness with minimal human feedback.
By Andreas Kouridakis, Dimitrios Patiniotis Spyropoulos, George Vouros
arXiv:2608. 12372v1 Announce Type: new Abstract: AI systems are increasingly employed as decision aids, decision delegates, or autonomous decision-makers.
By Vijay Keswani, Breanna K. Nguyen, Cyrus Cousins, Vincent Conitzer, Walter Sinnott-Armstrong, Jana Schaich Borg
arXiv:2502. 20502v2 Announce Type: replace Abstract: Recent advances in Artificial Intelligence (AI) have yielded powerful computational models that, by learning from vast amounts of human-generated data, are increasingly posited as approximate models of human cognition.
By Lance Ying, Katherine M. Collins, Lionel Wong, Ilia Sucholutsky, Ryan Liu, Adrian Weller, Tianmin Shu, Thomas L. Griffiths, Joshua B. Tenenbaum
arXiv:2607. 06656v1 Announce Type: new Abstract: Machine learning models are often intended to augment rather than replace human decision makers, by providing information that is complementary to human judgement.
By Yewon Byun, Bryan Wilder
arXiv:2608. 05710v1 Announce Type: new Abstract: When an AI system is deployed, the individuals who use and or are evaluated by it form beliefs about how the system operates and use those beliefs to strategically present their preferences, behaviors, or attributes.
By Keziah Naggita