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Humans learn from catastrophic mistakes not through numerical penalties, but through qualitative suffering that reshapes who they are. Current AI safety approaches replicate none of this. Reward shaping captures magnitude, not meaning.…

人工智能 · 计算机科学 2026-03-17 Pandurang Mopgar

Very soon, millions of AI agents will proliferate across the economy, autonomously taking billions of actions. Inevitably, things will go wrong. Humans will be defrauded, injured, even killed. Law will somehow have to govern the coming…

计算机与社会 · 计算机科学 2026-03-12 Yonathan Arbel , Peter Salib , Simon Goldstein

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

The current work addresses a virtual environment with self-replicating agents whose decisions are based on a form of "somatic computation" (soma - body) in which basic emotional responses, taken in parallelism to actual living organisms,…

人工智能 · 计算机科学 2014-01-10 Carlos Pedro Gonçalves

Regulating artificial intelligence (AI) has become necessary in light of its deployment in high-risk scenarios. This paper explores the proposal to extend legal personhood to AI and robots, which had not yet been examined through the lens…

计算机与社会 · 计算机科学 2021-11-12 Gabriel Lima , Meeyoung Cha , Chihyung Jeon , Kyungsin Park

As AI agents increasingly operate in multi-agent environments, understanding their collective behavior becomes critical for predicting the dynamics of artificial societies. This study examines conformity, the tendency to align with group…

人工智能 · 计算机科学 2026-01-12 Alessandro Bellina , Giordano De Marzo , David Garcia

AI systems often rely on two key components: a specified goal or reward function and an optimization algorithm to compute the optimal behavior for that goal. This approach is intended to provide value for a principal: the user on whose…

人工智能 · 计算机科学 2021-02-09 Simon Zhuang , Dylan Hadfield-Menell

As AI becomes more "agentic," it faces technical and socio-legal issues it must address if it is to fulfill its promise of increased economic productivity and efficiency. This paper uses technical and legal perspectives to explain how…

计算机与社会 · 计算机科学 2025-08-13 Mark O. Riedl , Deven R. Desai

Autonomous agents acting in the real-world often operate based on models that ignore certain aspects of the environment. The incompleteness of any given model -- handcrafted or machine acquired -- is inevitable due to practical limitations…

计算机与社会 · 计算机科学 2021-10-20 Sandhya Saisubramanian , Shlomo Zilberstein , Ece Kamar

As Artificial Intelligence (AI) systems are integrated into more aspects of society, they offer new capabilities but also cause a range of harms that are drawing increasing scrutiny. A large body of work in the Responsible AI community has…

人机交互 · 计算机科学 2025-12-16 Sijia Xiao , Haodi Zou , Alice Qian Zhang , Deepak Kumar , Hong Shen , Jason Hong , Motahhare Eslami

There are countless examples of how AI can cause harm, and increasing evidence that the public are willing to ascribe blame to the AI itself, regardless of how "illogical" this might seem. This raises the question of whether and how the…

人机交互 · 计算机科学 2025-03-06 Eddie L. Ungless , Zachary Horne , Björn Ross

Modern AI agents suffer from a fundamental identity problem: when context windows overflow and conversation histories are summarized, agents experience catastrophic forgetting -- losing not just information, but continuity of self. This…

人工智能 · 计算机科学 2026-04-14 Prahlad G. Menon

We investigate whether and why people might adjust compensation for workers who use AI tools. Across 13 studies (N = 4,956), participants consistently lowered compensation for workers who used AI compared to those who did not. This "AI…

综合经济学 · 经济学 2026-03-06 Jin Kim , Shane Schweitzer , David De Cremer , Christoph Riedl

As large language models are increasingly deployed as interacting agents in high-stakes decisions, the AI safety community assumes that safety properties of individual models will compose into safe multi-agent behavior. This position paper…

人工智能 · 计算机科学 2026-05-05 Tanav Singh Bajaj , Nikhil Singh , Karan Anand , Eishkaran Singh

As artificial intelligence (AI) systems rapidly gain autonomy, the need for robust responsible AI frameworks becomes paramount. This paper investigates how organizations perceive and adapt such frameworks amidst the emerging landscape of…

计算机与社会 · 计算机科学 2025-04-17 Lee Ackerman

As LLM-based systems increasingly operate as agents embedded within human social and technical systems, alignment can no longer be treated as a property of an isolated model, but must be understood in relation to the environments in which…

The AI alignment problem, which focusses on ensuring that artificial intelligence (AI), including AGI and ASI, systems act according to human values, presents profound challenges. With the progression from narrow AI to Artificial General…

人工智能 · 计算机科学 2025-07-25 Alberto Hernández-Espinosa , Felipe S. Abrahão , Olaf Witkowski , Hector Zenil

Agentic systems powered by large language models (LLMs) are becoming progressively more complex and capable. Their increasing agency and expanding deployment settings attract growing attention to effective governance policies, monitoring,…

计算机与社会 · 计算机科学 2025-08-06 Garry A. Gabison , R. Patrick Xian

The ubiquity of systems using artificial intelligence or "AI" has brought increasing attention to how those systems should be regulated. The choice of how to regulate AI systems will require care. AI systems have the potential to synthesize…

I am a person and so are you. Philosophically we sometimes grant personhood to non-human animals, and entities such as sovereign states or corporations can legally be considered persons. But when, if ever, should we ascribe personhood to AI…

人工智能 · 计算机科学 2025-01-24 Francis Rhys Ward
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