A Large Language Model (LLM) is an artificial intelligence system that has been trained on vast amounts of natural language data, enabling it to generate human-like responses to written or spoken language input. GPT-3.5 is an example of an LLM that supports a conversational agent called ChatGPT. In this work, we used a series of novel prompts to determine whether ChatGPT shows heuristics, biases, and other decision effects. We also tested the same prompts on human participants. Across four studies, we found that ChatGPT was influenced by random anchors in making estimates (Anchoring Heuristic, Study 1); it judged the likelihood of two events occurring together to be higher than the likelihood of either event occurring alone, and it was erroneously influenced by salient anecdotal information (Representativeness and Availability Heuristic, Study 2); it found an item to be more efficacious when its features were presented positively rather than negatively - even though both presentations contained identical information (Framing Effect, Study 3); and it valued an owned item more than a newly found item even though the two items were identical (Endowment Effect, Study 4). In each study, human participants showed similar effects. Heuristics and related decision effects in humans are thought to be driven by cognitive and affective processes such as loss aversion and effort reduction. The fact that an LLM - which lacks these processes - also shows such effects invites consideration of the possibility that language may play a role in generating these effects in humans.
Heuristics and Biases in AI Decision-Making: Implications for Responsible AGI
Golisano Institute for Sustainability Rochester Institute of Technology Rochester, The United States；Information Sciences \& Technology, CEHC University at Albany, SUNY Albany, The United States
Benchmarking and Adapting On-Device LLMs for Clinical Decision Support
AI Collaborative Centre, University Health Network（人工智能协同中心，健康大学网络）；Princess Margaret Cancer Centre, University Health Network（彭菲癌症中心，健康大学网络）；Department of Electrical and Computer Engineering, University of Toronto（电气与计算机工程系，多伦多大学）；Division of Urology, Department of Surgery, St. Michael’s Hospital, Unity Health Toronto and University of Toronto（泌尿科，外科部，圣米歇尔医院，统一健康多伦多及多伦多大学）；Peter Munk Cardiac Centre, University Health Network（彼得·默克心脏中心，健康大学网络）；Department of Laboratory Medicine and Pathobiology and Department of Computer Science, University of Toronto（实验室医学与病理学系及计算机科学系，多伦多大学）；Vector Institute, Toronto（向量研究所，多伦多）
Guiding Large Language Models with Genetic Programming-Evolved Heuristic Knowledge for Dynamic Multi-Mode Project Scheduling
Centre for Data Science and Artificial Intelligence（数据科学与人工智能中心）；School of Engineering and Computer Science（工程与计算机科学学院）；Victoria University of Wellington（惠灵顿维多利亚大学）
Large Language Newsvendor: Decision Biases and Cognitive Mechanisms
School of Business Administration, South China University of Technology（华南理工大学商学院）；Department of Decisions, Operations and Technology, The Chinese University of Hong Kong（香港中文大学决策、运营与技术系）
Do Persona-Infused LLMs Affect Performance in a Strategic Reasoning Game?
Bellini College of Artificial Intelligence, Cybersecurity and Computing（人工智能、网络安全与计算学院）；University of South Florida（佛罗里达州立大学）；Information Directorate（信息 Directorate）；Air Force Research Library（空军研究图书馆）
COMPARE: Clinical Optimization with Modular Planning and Assessment via RAG-Enhanced AI-OCT: Superior Decision Support for Percutaneous Coronary Intervention Compared to ChatGPT-5 and Junior Operators
Tangdu Hospital, The Fourth Military Medical University（空军军医大学唐都医院）；Research Institute of Tsinghua University in Shenzhen（深圳清华大学研究院）；The Second Affiliated Hospital, Air Force Medical University（空军军医大学第二附属医院）
Heuristic Classification of Thoughts Prompting (HCoT): Integrating Expert System Heuristics for Structured Reasoning into Large Language Models
Computer Network Information Center, Chinese Academy of Sciences（中国科学院计算机网络信息中心）；Shenyang Aerospace University（沈阳航空航天大学）；ZGC LAB, Beijing,China（北京ZGC实验室）；Institute for Network Sciences and Cyberspace, Tsinghua University（清华大学网络科学与网络空间研究院）
Medical Heuristic Learning: An LLM-Driven Framework for Interpretable and Auditable Clinical Decision Rules
Centre for Artificial Intelligence Driven Drug Discovery, Macao Polytechnic University（人工智能驱动药物发现中心，澳门理工学院）；Key Laboratory of Short-Range Radio Equipment Testing and Evaluation, Ministry of Industry and Information Technology Terahertz Science Application Center (TSAC), Beijing Institute of Technology（工业和信息化部短距离无线电设备测试与评估重点实验室，太赫兹科学应用中心（TSAC），北京理工大学）；Department of Critical Care Medicine, Yantai Yuhuangding Hospital, Qingdao University（重症医学科，烟台友谊医院，青岛大学）；Faculty of Education, The University of Hong Kong（教育学院，香港大学）；College of Information Engineering, Dalian University（信息工程学院，大连大学）
One Size Fits None: Heuristic Collapse in LLM Investment Advice
Computer Science and Artificial Intelligence Laboratory（计算机科学与人工智能实验室）；Massachusetts Institute of Technology（麻省理工学院）；Sloan School of Management（斯隆管理学院）
Evaluating Large Language Models for Multimodal Simulated Ophthalmic Decision-Making in Diabetic Retinopathy and Glaucoma Screening
Ophthalmology Department, São Paulo Federal University（圣保罗联邦大学眼科部）；Université Paris-Saclay, CentraleSupélec, Mathematics and Computer Science Laboratory（巴黎萨克莱大学、中央超导实验室数学与计算机科学实验室）；Laboratory for Computational Physiology, Massachusetts Institute of Technology（计算生理学实验室、麻省理工学院）
