38 citations · 48 across the 7 of their papers we have counts for
7 papers
A Case Study Investigating the Role of Generative AI in Quality Evaluations of Epics in Agile Software Development
Werner Geyer, Jessica He, Daita Sarkar +6
The broad availability of generative AI offers new opportunities to support various work domains, including agile software development. Agile epics are a key artifact for product m…
"The Diagram is like Guardrails": Structuring GenAI-assisted Hypotheses Exploration with an Interactive Shared Representation
Zijian Ding, Michelle Brachman, Joel Chan +1
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 rem…
Current and Future Use of Large Language Models for Knowledge Work
Michelle Brachman, Amina El-Ashry, Casey Dugan +1
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…
Design and Evaluation of Camera-Centric Mobile Crowdsourcing Applications
Abby Stylianou, Michelle Brachman, Albatool Wazzan +2
The data that underlies automated methods in computer vision and machine learning, such as image retrieval and fine-grained recognition, often comes from crowdsourcing. In contexts…
Emerging Reliance Behaviors in Human-AI Content Grounded Data Generation: The Role of Cognitive Forcing Functions and Hallucinations
Zahra Ashktorab, Qian Pan, Werner Geyer +5
We investigate the impact of hallucinations and Cognitive Forcing Functions in human-AI collaborative content-grounded data generation, focusing on the use of Large Language Models…
Exploring Prompt Engineering Practices in the Enterprise
Michael Desmond, Michelle Brachman
Interaction with Large Language Models (LLMs) is primarily carried out via prompting. A prompt is a natural language instruction designed to elicit certain behaviour or output from…
Increasing the Speed and Accuracy of Data LabelingThrough an AI Assisted Interface
Michael Desmond, Zahra Ashktorab, Michelle Brachman +8
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 w…