Intelligence Augmentation: Effective Human-AI Interaction to Supercharge Scientific Research
Daniel S. Weld
Recent advances in artificial intelligence are powering revolutionary interactive tools that will transform the capabilities of everyone, especially knowledge workers. But in order to create synergy, where humans’ augmented intelligence and creativity reaches its true potential, we need improved interaction methods. AI presents several challenges to existing UI paradigms, including nondeterminism, inexplicable behavior, and significant errors (such as large language model hallucinations).
We discuss principles and pitfalls for effective human-AI interaction, grounding our discussion in Semantic Scholar — a free, open, AI-powered scientific discovery platform aimed at augmenting the intelligence of human researchers.
Daniel S. Weld is chief scientist and general manager of Semantic Scholar at the Allen Institute of Artificial Intelligence and professor emeritus at the University of Washington. After formative education at Phillips Academy, he received bachelor’s degrees in both computer science and biochemistry at Yale University in 1982. He landed a Ph.D. from the MIT Artificial Intelligence Lab in 1988, received a Presidential Young Investigator Award in 1989 and an Office of Naval Research Young Investigator Award in 1990; he is a fellow of the Association for Artificial Intelligence (AAAI), the American Association for the Advancement of Science (AAAS), and the Association for Computing Machinery (ACM). Dan was a founding editor for the Journal of AI Research, was area editor for the Journal of the ACM and on the editorial board for the Artificial Intelligence journal. Weld is a venture partner at the Madrona Venture Group and has co-founded three companies: Netbot (sold to Excite), Adrelevance (sold to Media Metrix), and Nimble Technology (sold to Actuate).