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20122026
most citedTowards A Rigorous Science of Interpretable Machine Learning

3.2k citations · 5.1k across the 137 of their papers we have counts for

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Showing cs.HCShow all

8 papers · 1 filter

cs.HC2026

"ChatGPT, what am I missing?": Designing AI Workflows around Professional Task Structure to Shape Analytic AI Use

Zilin Ma, Suzi Jazmati, Marco Chimenton +4

General-purpose AI lets users choose what support to request, but leaves them to structure the support a professional task requires. We examine how interactive workflows can embed…

cs.HC2026

From Wearable Data to Personalized and Actionable Health Insights

Esther Brown, Karis Moon, Victoria Dean +1

Commercial wearable devices continuously capture rich physiological data (e.g., heart rate, respiration), opening new possibilities for monitoring health conditions, notably around…

cs.HC2026

A Benchmark to Assess Common Ground in Human-AI Collaboration

Christian Poelitz, Finale Doshi-Velez, Siân Lindley

AI is becoming increasingly integrated into everyday life, both in professional work environments and in leisure and entertainment contexts. This integration requires AI to move be…

cs.HC2024★ 1 cited

Contrastive Explanations That Anticipate Human Misconceptions Can Improve Human Decision-Making Skills

Zana Buçinca, Siddharth Swaroop, Amanda E. Paluch +2

People's decision-making abilities often fail to improve or may even erode when they rely on AI for decision-support, even when the AI provides informative explanations. We argue t…

cs.HC2024

A Sim2Real Approach for Identifying Task-Relevant Properties in Interpretable Machine Learning

Eura Nofshin, Esther Brown, Brian Lim +2

Explanations of an AI's function can assist human decision-makers, but the most useful explanation depends on the decision's context, referred to as the downstream task. User studi…

cs.HC2023★ 39 cited

Accuracy-Time Tradeoffs in AI-Assisted Decision Making under Time Pressure

Siddharth Swaroop, Zana Buçinca, Krzysztof Z. Gajos +1

In settings where users both need high accuracy and are time-pressured, such as doctors working in emergency rooms, we want to provide AI assistance that both increases decision ac…

cs.HC2022★ 4 cited

"If it didn't happen, why would I change my decision?": How Judges Respond to Counterfactual Explanations for the Public Safety Assessment

Yaniv Yacoby, Ben Green, Christopher L. Griffin +1

Many researchers and policymakers have expressed excitement about algorithmic explanations enabling more fair and responsible decision-making. However, recent experimental studies…

cs.HC2021★ 164 cited

Designing AI for Trust and Collaboration in Time-Constrained Medical Decisions: A Sociotechnical Lens

Maia Jacobs, Jeffrey He, Melanie F. Pradier +6

Major depressive disorder is a debilitating disease affecting 264 million people worldwide. While many antidepressant medications are available, few clinical guidelines support cho…