arXiv AI By Eun Jeong Kang (Xianpi), Peter (Xianpi), Duan, Swati Mishra

Novice Reliance Calibration in AI-Assisted Decision Making: The Role of Explanations and Self-Assessment

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arXiv AI
Aug 19

Supporting Calibrated Reliance in Human-AI Collaboration: Different Strategies for Different Tasks

The study investigates how different AI support formats influence human decision-making across two tasks: abstract visual reasoning with RAVEN matrices and deductive logical reasoning with LSAT problems. Findings reveal that in visual reasoning, predictions alone and predicted probabilities best support accuracy and error recovery, while in logical reasoning, LLM explanations outperform other supports. The results suggest that effective human–AI collaboration requires task‑specific support strategies rather than a one‑size‑fits‑all approach.

By Ruth Cohen, Lu Feng, Ayala Bloch, Sarit Kraus
arXiv AI
Aug 5

AI Assistance Reduces Persistence and Hurts Independent Performance

arXiv:2604. 04721v3 Announce Type: replace Abstract: People often optimize for long-term goals in collaboration: A mentor or companion doesn't just answer questions, but also scaffolds learning, tracks progress, and prioritizes the other person's growth over immediate results.

By Grace Liu, Brian Christian, Tsvetomira Dumbalska, Michiel A. Bakker, Rachit Dubey