arXiv AI
Jul 2
Constructive Alignment: Governing Preference Dynamics in Human-AI Interaction
arXiv:2607. 00001v1 Announce Type: new Abstract: Most approaches to AI alignment treat human preferences as fixed targets to be inferred and optimized.
Align AI to Dynamic Human-AI Workflows
arXiv:2607. 14240v1 Announce Type: new Abstract: Current alignment approaches typically focus on emulating human behavior using static representations of human preferences, failing to capture the dynamic, context-dependent nature of real-world human-AI interactions.
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arXiv AI
Jul 9
Learning social norms enhances compatibility in dynamic human-AI coordination
arXiv:2607. 07021v1 Announce Type: new Abstract: Humans continuously coordinate with others in dynamic interactions, often through implicit, hard-to-quantify social norms that act as shared tacit expectations among interacting agents.
arXiv AI
5d ago
Position: We Need Practical AI Alignment Methods to Mirror Human Reasoning
arXiv:2608. 12372v1 Announce Type: new Abstract: AI systems are increasingly employed as decision aids, decision delegates, or autonomous decision-makers.
arXiv AI
Aug 5
Socially Grounded Agentic AI: Coordinating Plural Perspectives through Social Theory
arXiv:2608. 03910v1 Announce Type: new Abstract: As AI systems are deployed across increasingly diverse social contexts, alignment can no longer be framed as the optimization of a single, unified set of values.
arXiv AI
Aug 10
Social World Models
arXiv:2509. 00559v3 Announce Type: replace Abstract: Humans intuitively navigate social interactions by simulating unspoken dynamics and reasoning about others' perspectives, even with limited information.
arXiv AI
6d ago
On Benchmarking Human-Like Intelligence in Machines
arXiv:2502. 20502v2 Announce Type: replace Abstract: Recent advances in Artificial Intelligence (AI) have yielded powerful computational models that, by learning from vast amounts of human-generated data, are increasingly posited as approximate models of human cognition.
arXiv AI
Jun 30
Modelling Human Values for Value-Aware Multi-Agent Systems
arXiv:2402. 06359v2 Announce Type: replace Abstract: One of today's most pressing societal challenges is building AI systems whose behaviour, or the behaviour it enables within communities of interacting human and artificial agents, aligns with relevant human values.
arXiv AI
Aug 12
Toward a Theory of Value in AI Alignment
arXiv:2608. 10327v1 Announce Type: new Abstract: Can AI systems be aligned to human values?
arXiv AI
Jun 16
Synthetic Counteradaptation: A Principle of Human-AI Co-evolution
arXiv:2606. 15503v1 Announce Type: new Abstract: In this paper, we introduce the concept of synthetic counteradaptation, a process where human and AI systems co-evolve by adapting to each other's strategies and behaviors.
arXiv AI
Aug 7
Shaping Human-AI Interactions to Provide Improvement Pathways and Balance Competing Objectives
arXiv:2608. 05710v1 Announce Type: new Abstract: When an AI system is deployed, the individuals who use and or are evaluated by it form beliefs about how the system operates and use those beliefs to strategically present their preferences, behaviors, or attributes.
arXiv AI
Jul 7
Human-Centric Reflective Architecture for Human-AI Collaborative Decision-Making
arXiv:2607. 03025v1 Announce Type: new Abstract: The use of Large Language Models (LLMs) across diverse areas of human activity-ranging from everyday tasks to safety-critical applications-aims to enhance decision-making effectiveness with minimal human feedback.
arXiv AI
Jul 3
Structuring the Space of Sociotechnical Alignment
arXiv:2607. 01250v1 Announce Type: cross Abstract: Sociotechnical alignment concerns the social desirability of AI behavior and is thus inherently normative, not merely technical.