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1
Introduction
2
Information Visualization
3
Big Data
4
Weapons of Mass Destruction
5
Enhancing Human Control
6
People Not Apps
7
Responsibility
8
Statement of Principles
9
Awareness
10
Data provenance
11
Independent oversight
12
National algorithm safety book
13
Planning oversight
14
Continuous monitoring
15
retrospective analyses
16
summary
17
how to ensure human control
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Clarify responsibility
19
Questions
20
Algorithms
21
Modular Design
22
Explainable AI
23
Safe vs Dangerous Algorithms
24
Meaningful Control
25
Liability
26
Ethically aligned design
27
Audience questions
28
Algorithms vs humans
29
Big corporations vs small companies
Description:
Explore the concept of algorithmic accountability in this Turing Lecture by Professor Ben Shneiderman from the University of Maryland. Delve into strategies for designing safer systems through human-centered independent oversight, covering topics such as information visualization, big data, and enhancing human control. Learn about the importance of planning oversight, continuous monitoring, and retrospective analyses in preventing failures in vital services like communications, financial trading, healthcare, and transportation. Discover how to create more reliable and trustworthy systems by implementing comprehensible, predictable, and controllable human-centered approaches. Examine the significance of clarifying responsibility for failures to improve design thinking and investigate the balance between algorithms and human decision-making. Gain insights into modular design, explainable AI, and ethically aligned design principles. This lecture also addresses the challenges faced by both large corporations and small companies in ensuring algorithmic accountability. Read more

Turing Lecture - Algorithmic Accountability - Professor Ben Shneiderman, University of Maryland

Alan Turing Institute
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