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1
Introduction
2
Machine Learning Algorithms
3
Challenges
4
Explanation Matters
5
Our Goal
6
Innovation Strategy 1
7
Innovation Strategy 2
8
Summary
9
Methods
10
Design Process
11
User Profile
12
User Demographic
13
Results
14
Research Question 1
15
Trust
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Why
17
Future
18
Thank you
19
Questions
20
Confidence
Description:
Explore strategies for explaining decision-making algorithms through user interfaces to non-expert stakeholders in this 20-minute conference talk from the ACM CHI Conference on Human Factors in Computing Systems. Delve into research findings on design principles for explanation interfaces that effectively communicate algorithmic decision-making processes. Discover how interactive and "white-box" explanations can improve users' comprehension of algorithms, and examine the trade-offs between effectiveness and time investment. Gain insights into the surprising relationship between algorithm comprehension and user trust. Learn about the study's methodology, design process, and user demographics, and consider the implications for future research and development in the field of algorithmic transparency and explainability.

Explaining Decision-Making Algorithms through UI - Strategies to Help Non-Expert Stakeholders

Association for Computing Machinery (ACM)
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