Machine learning (ML) is increasingly used in clinical oncology to diagnose cancers, predict
patient outcomes, and inform treatment planning. Here, we review recent applications of ML …

AI-chatbots as frontline agents promise innovative opportunities for sha** service offerings
that benefit customers and retailers. Examining current practice through the lens of agency …

Recent developments in deep learning have resulted in code-generation models that
produce source code from natural language and code-based prompts with high accuracy …

In AI-assisted decision-making, it is critical for human decision-makers to know when to trust
AI and when to trust themselves. However, prior studies calibrated human trust only based …

Artificial intelligence (AI)-generated clinical advice is becoming more prevalent in
healthcare. However, the impact of AI-generated advice on physicians' decision-making is …

Recent work has aimed to capture nuances of human behavior by using LLMs to simulate
responses from particular demographics in settings like social science experiments and …

This report synthesizes~ 60 research papers about overreliance on AI. The papers originate
from a variety of disciplines, including Human-Computer Interaction (HCI); Human Factors; …

In AI-assisted decision-making, it is crucial but challenging for humans to achieve
appropriate reliance on AI. This paper approaches this problem from a human-centered …

The development of diagnostic tools for skin cancer based on artificial intelligence (AI) is
increasing rapidly and will likely soon be widely implemented in clinical use. Even though …

Heightened AI expectations facilitate performance in human-AI interactions through placebo
effects. While lowering expectations to control for placebo effects is advisable, overly …