James Wexler

schoolGooglebar_chart#3674 Global Rank

Total Papers

HCI Rank

#3674

Research Areas

Years Active

Recent Publications

Strategic Tradeoffs Between Humans and AI in Multi-Agent Bargaining

Markets increasingly accommodate large language models (LLMs) as autonomous decision-making agents. As this transition occurs, it becomes critical to evaluate how these agents behave relative to their human and task-specific statistical predecessors. In this work, we present results from an empirical study comparing h…

IUI '24CorrespondingGenerative AI (Text, Image, Music, Video) +1

Take It, Leave It, or Fix It: Measuring Productivity and Trust in Human-AI Collaboration

Although recent developments in generative AI have greatly enhanced the capabilities of conversational agents such as Google's Bard or OpenAI's ChatGPT, it's unclear whether the usage of these agents aids users across various contexts. To better understand how access to conversational AI affects productivity and trust…

IUI '243rd AuthorIntelligent Voice Assistants (Alexa, Siri, etc.) +2

ConstitutionMaker: Interactively Critiquing Large Language Models by Converting Feedback into Principles

Large language model (LLM) prompting is a promising new approach for users to create and customize their own chatbots. However, current methods for steering a chatbot's outputs, such as prompt engineering and fine-tuning, do not support users in converting their natural feedback on the model's outputs to changes in th…

DIS '234th AuthorGenerative AI (Text, Image, Music, Video) +1

From Discovery to Adoption: Understanding the ML Practitioners' Interpretability Journey

Models are interpretable when machine learning (ML) practitioners can readily understand the reasoning behind their predictions. Ironically, little is known about the ML practitioners' experience of discovering and adopting novel interpretability techniques in production settings. In a qualitative study with 18 practi…

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