Michelle Brachman

schoolIBMbar_chart#1103 Global Rank

Total Papers

HCI Rank

#1103

Research Areas

Years Active

Recent Publications

Current and Future Use of Large Language Models for Knowledge Work

Large Language Models (LLMs) have introduced a paradigm shift in interaction with AI technology, enabling knowledge workers to complete tasks by specifying their desired outcome in natural language. LLMs have the potential to increase productivity and reduce tedious tasks in an unprecedented way. A systematic study of…

CC '252nd AuthorHuman-LLM Collaboration +1

"The Diagram is like Guardrails": Structuring GenAI-assisted Hypotheses Exploration with an Interactive Shared Representation

Data analysis encompasses a spectrum of tasks, from high-level conceptual reasoning to lower-level execution. While AI-powered tools increasingly support execution tasks, there remains a need for intelligent assistance in conceptual tasks. This paper investigates the design of an ordered node-link tree interface augme…

IUI '251st AuthorConversational Chatbots +2

Building Appropriate Mental Models: What Users Know and Want to Know about an Agentic AI Chatbot

Agentic systems aim to handle complex problems with increasing system autonomy using generative AI. These new agentic systems are becoming more feasible and easier to build. Yet we know little about what end-users need to know to use these systems appropriately. We study one such agentic system, "Gent," which can brea…

CSCW '242nd AuthorSession 1e: Human-AI Collaboration

Grounding with Structure: Exploring Design Variations of Grounded Human-AI Collaboration in a Natural Language Interface

Selecting an effective utterance among countless possibilities that match a user's intention poses a challenge when using natural language interfaces. To address the challenge, we leveraged the principle of least collaborative effort in communication grounding theory and designed three grounded conversational interact…

CSCW '242nd AuthorSession 3e: Trusting the Machine: Fake News. AI Decision-Making, and Auditing

Evaluating What Others Say: The Effect of Accuracy Assessment in Shaping Mental Models of AI Systems

Forming accurate mental models that align with the actual behavior of an AI system is critical for successful user experience and interactions. One way to develop mental models is through information shared by other users. However, this social information can be inaccurate and there is a lack of research examining whe…

DIS '235th+ AuthorHuman-LLM Collaboration +2

SME-in-the-loop: Interaction Preferences when Supervising Bots in Human-AI Communities

Subject matter experts play an important role in customer support communities by responding to user queries. Some communities have adopted chatbots in addition to SMEs to address commonly asked questions. Yet, SME-bot interactions, particularly teaching paradigms between SMEs and bots remain understudied. We investiga…

CSCW '221st AuthorHuman-AI collaboration; Human-AI collaboration

Reliance and Automation for Human-AI Collaborative Data Labeling Conflict Resolution

Human data labeling with multiple labelers and the resulting conflict resolution remains the norm for many enterprise machine learning pipelines. Conflict resolution can be a time-intensive and costly process. Our goal was to study how human-AI collaboration can improve conflict resolution, by enabling users to automa…

CSCW '21CorrespondingData Work and AI

AI-Assisted Human Labeling: Batching for Efficiency without Overreliance

Human labeling of training data is often a time-consuming, expensive part of machine learning. In this paper, we study "batch labeling", an AI-assisted UX paradigm, that aids data labelers by allowing a single labeling action to apply to multiple records. We ran a large scale study on Mechanical Turk with 156 particip…

IUI '215th+ AuthorExplainable AI (XAI) +2

Increasing the Speed and Accuracy of Data Labeling Through an AI Assisted Interface

Labeling data is an important step in the supervised machine learning lifecycle. It is a laborious human activity comprised of repeated decision making: the human labeler decides which of several potential labels to apply to each example. Prior work has shown that providing AI assistance can improve the accuracy of bi…

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