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相关论文: AI-Induced Human Responsibility (AIHR) in AI-Human…

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How to attribute responsibility for autonomous artificial intelligence (AI) systems' actions has been widely debated across the humanities and social science disciplines. This work presents two experiments ($N$=200 each) that measure…

计算机与社会 · 计算机科学 2021-02-02 Gabriel Lima , Nina Grgić-Hlača , Meeyoung Cha

AI-related incidents are becoming increasingly frequent and severe, ranging from safety failures to misuse by malicious actors. In such complex situations, identifying which elements caused an adverse outcome, the problem of cause…

人工智能 · 计算机科学 2026-03-17 Maria Victoria Carro , David Lagnado

Human decision-making is strongly influenced by cognitive biases, particularly under conditions of uncertainty and risk. While prior work has examined bias in single-step decisions with immediate outcomes and in human interaction with a…

人机交互 · 计算机科学 2026-03-25 Teerthaa Parakh , Karen M. Feigh

AI systems are fallible, and humans can make mistakes in deciding whether to trust AI over their own judgment. Thus, improving human-AI collaboration requires understanding when, why, and how humans decide to rely on AI. We study two…

人工智能 · 计算机科学 2026-05-28 Maharshi Gor , Yoo Yeon Sung , Yu Hou , Eve Fleisig , Irene Ying , Tianyi Zhou , Jordan Boyd-Graber

In AI-assisted decision-making, effective hybrid (human-AI) teamwork is not solely dependent on AI performance alone, but also on its impact on human decision-making. While prior work studies the effects of model accuracy on humans, we…

人机交互 · 计算机科学 2022-02-25 Andi Peng , Besmira Nushi , Emre Kiciman , Kori Inkpen , Ece Kamar

The integration of artificial intelligence (AI) into human teams is widely expected to enhance performance and collaboration. However, our study reveals a striking and counterintuitive result: human-AI teams performed worse than human-only…

人机交互 · 计算机科学 2025-01-28 Yinuo Qin , Richard T. Lee , Paul Sajda

According to several empirical investigations, despite enhancing human capabilities, human-AI cooperation frequently falls short of expectations and fails to reach true synergy. We propose a task-driven framework that reverses prevalent…

计算机与社会 · 计算机科学 2026-05-26 Saleh Afroogh , Kush R. Varshney , Jason D'Cruz

Robots and other artificial intelligence (AI) systems are widely perceived as moral agents responsible for their actions. As AI proliferates, these perceptions may become entangled via the moral spillover of attitudes towards one AI to…

人工智能 · 计算机科学 2024-12-10 Aikaterina Manoli , Janet V. T. Pauketat , Jacy Reese Anthis

Collaboration with artificial intelligence (AI) has improved human decision-making across various domains by leveraging the complementary capabilities of humans and AI. Yet, humans systematically overrely on AI advice, even when their…

人机交互 · 计算机科学 2026-05-15 Joshua Holstein , Patrick Hemmer , Gerhard Satzger , Wei Sun

Given an increasing prevalence of intelligent systems capable of autonomous actions or augmenting human activities, it is important to consider scenarios in which the human, autonomous system, or both can exhibit failures as a result of one…

人工智能 · 计算机科学 2023-03-27 Andrew Fuchs , Andrea Passarella , Marco Conti

Artificial Intelligence (AI) is advancing at an unprecedented pace, with clear potential to enhance decision-making and productivity. Yet, the collaborative decision-making process between humans and AI remains underdeveloped, often falling…

人机交互 · 计算机科学 2025-04-10 Bowen Lou , Tian Lu , T. S. Raghu , Yingjie Zhang

Recent years have seen rapid growth in the market for HR technology and AI-driven HR solutions in particular. This popularity has also resulted in increased attention to the negative aspects of using AI to support hiring practices, such as…

计算机与社会 · 计算机科学 2026-03-09 Mesut Kaya , Toine Bogers

We anticipate increased instances of humans and AI systems working together in what we refer to as a hybrid team. The increase in collaboration is expected as AI systems gain proficiency and their adoption becomes more widespread. However,…

人工智能 · 计算机科学 2024-08-06 Andrew Fuchs , Andrea Passarella , Marco Conti

Scientists and philosophers have debated whether humans can trust advanced artificial intelligence (AI) agents to respect humanity's best interests. Yet what about the reverse? Will advanced AI agents trust humans? Gauging an AI agent's…

人工智能 · 计算机科学 2022-12-29 Tim Johnson , Nick Obradovich

This study examines the understudied role of algorithmic evaluation of human judgment in hybrid decision-making systems, a critical gap in management research. While extant literature focuses on human reluctance to follow algorithmic…

人机交互 · 计算机科学 2025-04-22 Yuanjun Feng , Vivek Chodhary , Yash Raj Shrestha

Since the first AI-HRI held at the 2014 AAAI Fall Symposium Series, a lot of the presented research and discussions have emphasized how artificial intelligence (AI) developments can benefit human-robot interaction (HRI). This portrays HRI…

人工智能 · 计算机科学 2022-10-24 Richard G. Freedman

As generative AI systems become increasingly embedded in collaborative work, they are evolving from visible tools into human-like communicative actors that participate socially rather than merely providing information. Yet little is known…

The integration of Artificial Intelligence (AI) necessitates determining whether systems function as tools or collaborative teammates. In this study, by synthesizing Human-AI Interaction (HAI) literature, we analyze this distinction across…

As artificial intelligence (AI) becomes deeply integrated into critical infrastructures and everyday life, ensuring its safe deployment is one of humanity's most urgent challenges. Current AI models prioritize task optimization over safety,…

人工智能 · 计算机科学 2024-11-08 Joshua T. S. Hewson

Despite the growing interest in collaborative AI, designing systems that seamlessly integrate human input remains a major challenge. In this study, we developed a task to systematically examine human preferences for collaborative agents. We…

人工智能 · 计算机科学 2025-10-28 Lukas William Mayer , Sheer Karny , Jackie Ayoub , Miao Song , Danyang Tian , Ehsan Moradi-Pari , Mark Steyvers
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