Powerful AI technologies, especially recently developed large language models, are increasingly mediating or even replacing human thinking, from information and knowledge acquisition, judgment and decision making, creativity, to our understanding of the world. In 1962, Douglas Engelbart described a vision of Intelligence Augmentation (IA), in which machines should augment, instead of replacing, human thinking processes.  In this talk, I will revisit this vision and pose the question: Are we moving away from IA with increasingly capable and agentic AI? Drawing on human-computer interaction research, including our own work, I will examine two interconnected threats. First, I will present findings from research that studies and mitigates people’s overreliance on AI, highlighting fundamental obstacles to maintaining human oversight of AI and arguing that a productivity-oriented approach to AI development and use structurally worsens these obstacles. I will then discuss our recent work studying how new affordances of LLMs threaten the integrity of information and knowledge acquisition, and situate this discussion in broader empirical research that has identified how AI is reshaping human cognition. I will close the talk with reflections on what intelligence augmentation actually requires, and how these requirements might be embedded in the technical objectives of AI and the sociotechnical infrastructures through which AI is deployed.

References

Valerie Chen, Q. Vera Liao, Jennifer Wortman Vaughan, and Gagan Bansal. 2023. Understanding the Role of Human Intuition on Reliance in Human-AI Decision-Making with Explanations. Proc. ACM Hum.-Comput. Interact. 7, CSCW2, Article 370 (October 2023), 32 pages. https://doi.org/10.1145/3610219

Nikhil Sharma, Q. Vera Liao, and Ziang Xiao. 2024. Generative Echo Chamber? Effect of LLM-Powered Search Systems on Diverse Information Seeking. In Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems (CHI '24). Association for Computing Machinery, New York, NY, USA, Article 1033, 1–17. https://doi.org/10.1145/3613904.3642459

Lai, Vivian, Chacha Chen, Qingzi Vera Liao, Alison Smith-Renner and Chenhao Tan. “Towards a Science of Human-AI Decision Making: A Survey of Empirical Studies.” ArXiv abs/2112.11471 (2021). https://api.semanticscholar.org/CorpusID:245385821