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Theory of Re/placement for Guiding Artificial Intelligence Integration in Real-World Operational Contexts
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Responsible Artificial Intelligence: Recommendations and Lessons Learned
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Reflections on the AI alignment problem
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Empirical research on requirements quality: a systematic mapping study
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Evaluation in artificial intelligence: from task-oriented to ability-oriented measurement
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AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations
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A matter of principle? AI alignment as the fair treatment of claims
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Normative conflicts and shallow AI alignment
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Multi-agent embodied AI: advances and future directions
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Social Integration of Artificial Intelligence: Functions, Automation Allocation Logic and Human-Autonomy Trust
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The value alignment problem in advisory AI: a systematic literature review
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Reframing the AI alignment problem: insights from business applications
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On the Characterization and Risk Assessment of AI-Powered Mobile Cloud Applications
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Activity theory for understanding and managing system innovations
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Evaluating and regulating agentic AI: A study of benchmarks, metrics, and regulation
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Responsible artificial intelligence governance: A review and research framework
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A Definition of Systems Thinking: A Systems Approach
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Ten steps for specifying saturation in qualitative research
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Drivers, barriers and social considerations for AI adoption in SCM
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The trust crisis in artificial intelligence: AI hallucinations and human-AI collaboration
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Risk it, if you dare: A quantitative analysis of the effects of perceived risk facets on the adoption of generative artificial intelligence in knowledge work
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Artificial intelligence tools expand scientists’ impact but contract science’s focus
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Temporal quality degradation in AI models
inferredcites →https://doi.org/10.1038/s42256-025-01113-8openalex-snapshot
Language models cannot reliably distinguish belief from knowledge and fact
inferredcites →https://doi.org/10.1038/s42256-025-01115-6openalex-snapshot
A psychometric framework for evaluating and shaping personality traits in large language models
inferredcites →https://doi.org/10.1080/001401300409143openalex-snapshot
Activity theory as a framework for analyzing and redesigning work
inferredcites →https://doi.org/10.1080/01449290410001673036openalex-snapshot
The cognitive task analysis methods for job and task design: review and reappraisal
inferredcites →https://doi.org/10.1080/0960085x.2022.2026621openalex-snapshot
Thinking responsibly about responsible AI and ‘the dark side’ of AI
inferredcites →https://doi.org/10.1080/10503300902897797openalex-snapshot
Developments in task analysis: New methods to study change
inferredcites →https://doi.org/10.1080/10749039.2020.1806328openalex-snapshot
From mediated actions to heterogenous coalitions: four generations of activity-theoretical studies of work and learning
inferredcites →https://doi.org/10.1086/711501openalex-snapshot
Why Simpler Computer Simulation Models Can Be Epistemically Better for Informing Decisions
inferredcites →https://doi.org/10.1093/mind/lix.236.433openalex-snapshot
I.—COMPUTING MACHINERY AND INTELLIGENCE
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Large Language Models are Not All You Need [President's Message]
inferredcites →https://doi.org/10.1109/sp.2017.49openalex-snapshot
Towards Evaluating the Robustness of Neural Networks
inferredcites →https://doi.org/10.1109/tbiom.2021.3132237openalex-snapshot
Towards Measuring Fairness in AI: The Casual Conversations Dataset
inferredcites →https://doi.org/10.1109/tetci.2022.3141105openalex-snapshot
A Survey of Embodied AI: From Simulators to Research Tasks
inferredcites →https://doi.org/10.1109/tpami.2024.3507000openalex-snapshot
LVLM-EHub: A Comprehensive Evaluation Benchmark for Large Vision-Language Models
inferredcites →https://doi.org/10.1109/tse.2019.2962027openalex-snapshot
Machine Learning Testing: Survey, Landscapes and Horizons
inferredcites →https://doi.org/10.1109/tts.2020.2974991openalex-snapshot
Responsible AI—Two Frameworks for Ethical Design Practice
inferredcites →https://doi.org/10.1126/science.adf6369openalex-snapshot
Rethink reporting of evaluation results in AI
inferredcites →https://doi.org/10.1145/3457607openalex-snapshot
A Survey on Bias and Fairness in Machine Learning
inferredcites →https://doi.org/10.1145/3531146.3533229openalex-snapshot
Predictability and Surprise in Large Generative Models
inferredcites →https://doi.org/10.1145/3545178openalex-snapshot
Trustworthy Autonomous System Development
inferredcites →https://doi.org/10.1162/qss_a_00267openalex-snapshot
A meso-scale cartography of the AI ecosystem
inferredcites →https://doi.org/10.1201/b12470openalex-snapshot
The Handbook of Task Analysis for Human-Computer Interaction
inferredcites →https://doi.org/10.1609/aaai.v35i17.17817openalex-snapshot
Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database
inferredcites →https://doi.org/10.2308/jfr-2020-024openalex-snapshot
How Do Individual Analyst Characteristics Affect Analyst Performance?
inferredcites →https://doi.org/10.52202/079017-0685openalex-snapshot
BetterBench: Assessing AI Benchmarks, Uncovering Issues, and Establishing Best Practices
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Science and Advanced Computing — runs a structured editorial panel for researchers
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