mlsanityData to 7 Oct 2026

The Rise of the AI Co-Pilot: Lessons for Design from Aviation and Beyond

arXiv 2311.14713 ↗First posted 16 Nov 2023cs.HC cs.AIcited by 15

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Abstract (arXiv)

The fast pace of advances in AI promises to revolutionize various aspects of knowledge work, extending its influence to daily life and professional fields alike. We advocate for a paradigm where AI is seen as a collaborative co-pilot, working under human guidance rather than as a mere tool. Drawing from relevant research and literature in the disciplines of Human-Computer Interaction and Human Factors Engineering, we highlight the criticality of maintaining human oversight in AI interactions. Reflecting on lessons from aviation, we address the dangers of over-relying on automation, such as diminished human vigilance and skill erosion. Our paper proposes a design approach that emphasizes active human engagement, control, and skill enhancement in the AI partnership, aiming to foster a harmonious, effective, and empowering human-AI relationship. We particularly call out the critical need to design AI interaction capabilities and software applications to enable and celebrate the primacy of human agency. This calls for designs for human-AI partnership that cede ultimate control and responsibility to the human user as pilot, with the AI co-pilot acting in a well-defined supporting role.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). Builds on 4 of its 25 references that are in the map. First posted on arXiv 16 Nov 2023.

Builds on

4 of 25 references.

References · 4

  1. 2017Explanation in Artificial Intelligence: Insights from the Social Sciencescited by 1,201
  2. 2022Who Goes First? Influences of Human-AI Workflow on Decision Making in Clinical Imagingcited by 32
  3. 2023When to Show a Suggestion? Integrating Human Feedback in AI-Assisted Programmingcited by 25
  4. 2021Human-AI Interactions in Public Sector Decision-Making: "Automation Bias" and "Selective Adherence" to Algorithmic Advicecited by 22

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 6; 2025: 5; 2026: 4.

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  1. 2024NOTSOFAR-1 Challenge: New Datasets, Baseline, and Tasks for Distant Meeting Transcriptioncited by 18
  2. 2025Build Agent Advocates, Not Platform Agentscited by 8
  3. 2026Human oversight of agentic systems in practice: Examining the oversight work, challenges, and heuristics of developers using software agentscited by 6
  4. 2025Generative AI Uses and Risks for Knowledge Workers in a Science Organizationcited by 5
  5. 2025Do It For Me vs. Do It With Me: Investigating User Perceptions of Different Paradigms of Automation in Copilots for Feature-Rich Softwarecited by 5
  6. 2024ChatGPT in Data Visualization Education: A Student Perspectivecited by 3
  7. 2024Design and evaluation of AI copilots -- case studies of retail copilot templatescited by 3
  8. 2024Survey of User Interface Design and Interaction Techniques in Generative AI Applicationscited by 3
  9. 2025Modeling and Optimizing User Preferences in AI Copilots: A Comprehensive Survey and Taxonomycited by 3
  10. 2026AI Agents Push Humans Out of the Loopcited by 3
  11. 2025Can Agents Judge Systematic Reviews Like Humans? Evaluating SLRs with LLM-based Multi-Agent Systemcited by 1
  12. 2026The Psychology of Learning from Machines: Anthropomorphic AI and the Paradox of Automation in Educationcited by 1
3 more
  1. 2024Thorns and Algorithms: Navigating Generative AI Challenges Inspired by Giraffes and Acaciascited by 0
  2. 2024The Model Mastery Lifecycle: A Framework for Designing Human-AI Interactioncited by 0
  3. 2026From Individual Prompts to Collective Intelligence: Mainstreaming Generative AI in the Classroomcited by 0