Ken Holstein

Assistant Professor Carnegie Mellon University

  • Pittsburgh PA

Ken Holstein's research focuses broadly on AI-augmented work and improving how we design and evaluate AI systems for real-world use.

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Carnegie Mellon University

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Biography

Ken Holstein is an Assistant Professor in the Human-Computer Interaction Institute at Carnegie Mellon University, where he directs the CMU CoALA Lab. In addition to his position at CMU, Ken is an inaugural member of the Partnership on AI’s Global Task Force for Inclusive AI. He is also part of Northwestern’s Center for Advancing Safety of Machine Intelligence (CASMI) and the Jacobs Foundation’s CERES network.

Ken's research focuses broadly on AI-augmented work and improving how we design and evaluate AI systems for real-world use. Ken draws on approaches from human–computer interaction (HCI), AI, design, cognitive science, learning sciences, statistics, and machine learning, among other areas.

Ken is deeply interested in: (1) understanding the gaps between human and artificial intelligence across a range of contexts, and (2) using this knowledge to design systems that respect human work, elevating human expertise and on-the-ground knowledge rather than diminishing it. To support these goals, Ken's research develops new approaches and tools that support better incorporation of diverse human expertise across the AI development lifecycle.

Ken's work has been generously supported by the National Science Foundation (NSF), CMU’s Block Center for Technology and Society, Northwestern’s CASMI & UL Research Institutes, Institute for Education Sciences (IES), Cisco Research, Jacobs Foundation, Amazon Research, CMU’s Metro21 Smart Cities Institute, and Prolific.

Areas of Expertise

Elections
Intelligence Augmentation
Applied Machine Learning
Artificial Intelligence
Human-Computer Interaction
Worker-Centered Design

Media Appearances

In Sudden Alarm, Tech Doyens Call for a Pause on ChatGPT

WIRED  online

2023-03-29

Others working in tech also expressed misgivings about the letter's focus on long-term risks, as systems available today including ChatGPT already pose threats. “I find recent developments very exciting,” says Ken Holstein, an assistant professor of human-computer interaction at Carnegie Mellon University, who asked his name be removed from the letter a day after signing it as debate emerged among scientists about the best demands to make at this moment.

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Funding New Research to Operationalize Safety in Artificial Intelligence

Northwestern Engineering  online

2023-02-17

Kenneth Holstein, assistant professor in the Human-Computer Interaction Institute at Carnegie Mellon University, will study how to support effective AI-augmented decision-making in the context of social work. In this domain, predictions regarding human behavior are fundamentally uncertain and ground truth labels upon which an AI system is trained — for example, whether an observed behavior is considered socially harmful — often represent imperfect proxies for the outcomes human decision-makers are interested in modeling.

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These glasses give teachers superpowers

The Hechinger Report  online

2018-10-04

Lumilo is the brainchild of a team at Carnegie Mellon University. Ken Holstein, a doctoral candidate at the university, designed the app with significant input from teachers like Mawhinney who use cognitive tutors in their classrooms. The project treads new ground for the use of artificial intelligence in schools.

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Social

Industry Expertise

Research
Education/Learning
Computer Software

Accomplishments

Best Paper Award

2023

ACM Conference on Fairness, Accountability, and Transparency (FAccT’23)

Best Paper Award

2023

ACM CHI Conference on Human Factors in Computing Systems (CHI’23)

Best Paper Award

2023

IEEE Conference on Secure and Trustworthy Machine Learning (SaTML’23)

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Education

Carnegie Mellon University

Ph.D.

Human–Computer Interaction

2019

Carnegie Mellon University

M.S.

Human–Computer Interaction

2019

University of Pittsburgh

B.S.

Psychology (Cognitive focus)

2014

Affiliations

  • Association for Computing Machinery (ACM) : Member
  • Design Justice Network (DJN) : Member

Event Appearances

Designing for Complementarity in AI-Augmented Work

UCI Informatics Seminar Series  University of California Irvine (UCI), Irvine, CA

Fostering Critical AI Literacy Among Frontline Workers, the Public, & AI Developers

HCI + Design Thought Leaders Lecture  Northwestern University, Evanston, IL

Supporting Effective AI-Augmented Decision-Making in Social Contexts

Toward a Safety Science of AI  Northwestern University, Evanston, IL

Research Grants

AI-Augmented Illustration through Conversational Interaction

Prolific

2023

Scaffolding Responsible AI Practice at the Earliest Stages of Ideation, Problem Formulation and Project Selection

PwC

2023 - 2024

Bridging Policy Gaps in the Life Cycle of Public Algorithmic Systems

Block Center

2022 - 2023

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Articles

Ground(less) Truth: A Causal Framework for Proxy Labels in Human-Algorithm Decision-Making

FAccT '23: Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency

2023

A growing literature on human-AI decision-making investigates strategies for combining human judgment with statistical models to improve decision-making. Research in this area often evaluates proposed improvements to models, interfaces, or workflows by demonstrating improved predictive performance on “ground truth’’ labels. However, this practice overlooks a key difference between human judgments and model predictions.

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Understanding Frontline Workers’ and Unhoused Individuals’ Perspectives on AI Used in Homeless Services

CHI '23: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

2023

Recent years have seen growing adoption of AI-based decision-support systems (ADS) in homeless services, yet we know little about stakeholder desires and concerns surrounding their use. In this work, we aim to understand impacted stakeholders’ perspectives on a deployed ADS that prioritizes scarce housing resources. We employed AI lifecycle comicboarding, an adapted version of the comicboarding method, to elicit stakeholder feedback and design ideas across various components of an AI system’s design.

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Investigating Practices and Opportunities for Cross-functional Collaboration around AI Fairness in Industry Practice

FAccT '23: Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency

2023

An emerging body of research indicates that ineffective cross-functional collaboration – the interdisciplinary work done by industry practitioners across roles – represents a major barrier to addressing issues of fairness in AI design and development. In this research, we sought to better understand practitioners’ current practices and tactics to enact cross-functional collaboration for AI fairness, in order to identify opportunities to support more effective collaboration.

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