Agency in sustained human-AI chatbot talks emerges as co-constructed turn-by-turn through boundary-setting and intention-steering, organized in a new 3-by-4 framework of actors and actions.
Mixed citations
Towards the Scalable Evaluation of Cooperativeness in Language Models, March 2023a
Mixed citation behavior. Most common role is background (67%).
12
Pith papers citing it
Background
67% of classified citations
citation-role summary
background 5
method 1
citation-polarity summary
representative citing papers
The paper defines five AI system categories for public administration and reports that 55% of 91 recent papers leave the system type underspecified while 31% study one type but motivate with another.
Exploratory interview study with 17 developers identifies four forms of emergent oversight work for software agents and documents situated challenges and heuristics.
The 2025 AI Agent Index catalogs technical and safety details for 30 deployed AI agents and finds low developer transparency on safety, evaluations, and societal impacts.
Trust calibration in agentic tool use is cast as preferential Bayesian optimization over a latent human risk-tolerance function observed through binary approve/deny feedback with a probit likelihood.
A new toolkit with cards and maps enables AI designers to juxtapose values and harms in early concept stages, shown valuable in designer surveys and interviews.
Designers using generative AI for concept envisioning engage in reciprocal reflection-in-action that surfaces multi-level value tensions and prioritizes harm recognition over positive value articulation.
Insider action research in an AI startup identifies three patterns of how practitioners view regulatory requirements and proposes internal expert collaboration as a way to turn external governance rules into shared, practical ownership.
A literature review concludes that pursuing consensus in data annotation creates biased AI by dismissing subjective disagreements and enforcing geographic hegemony, and proposes mapping diversity instead.
The paper maps LLM agent architectures onto a six-level continuum and argues that higher levels can enable simulation of emergent social phenomena while requiring attention to reproducibility and ethical issues.
The agentic web requires new normative infrastructure of laws, norms, and practices to allow user-delegated AI agents to access online properties without being blocked as malicious bots.
A survey that maps risks along the agent workflow and consolidates metrics and benchmarks for safety, robustness, privacy, and security in agentic AI.
citing papers explorer
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Does My Chatbot Have an Agenda? Understanding Human and AI Agency in Human-Human-like Chatbot Interaction
Agency in sustained human-AI chatbot talks emerges as co-constructed turn-by-turn through boundary-setting and intention-steering, organized in a new 3-by-4 framework of actors and actions.
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A Technical Typology of AI Systems in Public Administration
The paper defines five AI system categories for public administration and reports that 55% of 91 recent papers leave the system type underspecified while 31% study one type but motivate with another.
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Human oversight of agentic systems in practice: Examining the oversight work, challenges, and heuristics of developers using software agents
Exploratory interview study with 17 developers identifies four forms of emergent oversight work for software agents and documents situated challenges and heuristics.
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The 2025 AI Agent Index: Documenting Technical and Safety Features of Deployed Agentic AI Systems
The 2025 AI Agent Index catalogs technical and safety details for 30 deployed AI agents and finds low developer transparency on safety, evaluations, and societal impacts.
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Progressive Autonomy as Preference Learning: A Formalization of Trust Calibration for Agentic Tool Use
Trust calibration in agentic tool use is cast as preferential Bayesian optimization over a latent human risk-tolerance function observed through binary approve/deny feedback with a probit likelihood.
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Developing an AI Concept Envisioning Toolkit to Support Reflective Juxtaposition of Values and Harms
A new toolkit with cards and maps enables AI designers to juxtapose values and harms in early concept stages, shown valuable in designer surveys and interviews.
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How Designers Envision Value-Oriented AI Design Concepts with Generative AI
Designers using generative AI for concept envisioning engage in reciprocal reflection-in-action that surfaces multi-level value tensions and prioritizes harm recognition over positive value articulation.
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Engaged AI Governance: Addressing the Last Mile Challenge Through Internal Expert Collaboration
Insider action research in an AI startup identifies three patterns of how practitioners view regulatory requirements and proposes internal expert collaboration as a way to turn external governance rules into shared, practical ownership.
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The Consensus Trap: Dissecting Subjectivity and the "Ground Truth" Illusion in Data Annotation
A literature review concludes that pursuing consensus in data annotation creates biased AI by dismissing subjective disagreements and enforcing geographic hegemony, and proposes mapping diversity instead.
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Beyond Static Responses: Multi-Agent LLM Systems as a New Paradigm for Social Science Research
The paper maps LLM agent architectures onto a six-level continuum and argues that higher levels can enable simulation of emergent social phenomena while requiring attention to reproducibility and ethical issues.
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The Agentic Web Requires New Normative Infrastructure
The agentic web requires new normative infrastructure of laws, norms, and practices to allow user-delegated AI agents to access online properties without being blocked as malicious bots.
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Towards trustworthy agentic AI: a comprehensive survey of safety, robustness, privacy, and system security
A survey that maps risks along the agent workflow and consolidates metrics and benchmarks for safety, robustness, privacy, and security in agentic AI.