activity
20172026
most citedDissonance Between Human and Machine Understanding

50 citations · 174 across the 25 of their papers we have counts for

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Showing cs.AIShow all

5 papers · 1 filter

cs.AI20252 cited

Fine-Grained Appropriate Reliance: Human-AI Collaboration with a Multi-Step Transparent Decision Workflow for Complex Task Decomposition

Gaole He, Patrick Hemmer, Michael Vössing +2

In recent years, the rapid development of AI systems has brought about the benefits of intelligent services but also concerns about security and reliability. By fostering appropria…

cs.AI20241 cited

To Err Is AI! Debugging as an Intervention to Facilitate Appropriate Reliance on AI Systems

Gaole He, Abri Bharos, Ujwal Gadiraju

Powerful predictive AI systems have demonstrated great potential in augmenting human decision making. Recent empirical work has argued that the vision for optimal human-AI collabor…

cs.AI2024

From Stem to Stern: Contestability Along AI Value Chains

Agathe Balayn, Yulu Pi, David Gray Widder +9

This workshop will grow and consolidate a community of interdisciplinary CSCW researchers focusing on the topic of contestable AI. As an outcome of the workshop, we will synthesize…

cs.AI2021

Towards Benchmarking the Utility of Explanations for Model Debugging

Maximilian Idahl, Lijun Lyu, Ujwal Gadiraju +1

Post-hoc explanation methods are an important class of approaches that help understand the rationale underlying a trained model's decision. But how useful are they for an end-user…

cs.AI202150 cited

Dissonance Between Human and Machine Understanding

Zijian Zhang, Jaspreet Singh, Ujwal Gadiraju +1

Complex machine learning models are deployed in several critical domains including healthcare and autonomous vehicles nowadays, albeit as functional black boxes. Consequently, ther…