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Standardization of AI Ethics : Stakeholders, Values and Profit.

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Format:
Book
Author/Creator:
Corrêa, Nicholas Kluge.
Language:
English
Physical Description:
1 online resource (163 pages)
Edition:
1st ed.
Place of Publication:
Bielefeld : transcript Verlag, 2026.
Summary:
The relationship between AI, ethics, societal values and standardization is complex.The contributors to this volume discuss the challenges and opportunities involved in standardizing AI ethics, including algorithmic audits, stakeholder participation and certification mechanisms.
Contents:
Cover
Contents
Series Preface
Introduction
Should AI Auditors Be Audited?
The Algorithmic Audit Ecosystem and Its Structural Challenges
Auditing as an Algorithmic Governance Tool
Diagnosis of Systemic Failures and Risks
Institutional, Regulatory and Technical Pathways Towards Trustworthy Audits
Regulatory Frameworks and Compliance Mechanisms
Dynamic Auditing and Post‐Market Monitoring
Collaborative Ecosystems and Meta‐Audit Infrastructure
Limitations
Conclusion
References
Citizens Infrastructures as a Way to Govern AI's Power to Shape our Shared Representations
The Misalignment Between AI Deployment, Societal Values and Expectations
Over‐Promising and Under‐Delivering
The Alignment Problem
The Problem with Current Auditing Institutions
Defining AI Auditing
Why Add Infrastructures?
Proposing a Solution: Citizens Infrastructures to Support AI Audit
A Proposition for Governance
A Way to Claim Agency over the Power of AI to Shape Our Shared Representations, Values and Behaviors
Algorithmic Audits of HR‑AI Tools in the United States
IntroductionBackground
Use of Artificial Intelligence in the Human Resource Sector
Algorithmic Audits of HR‑AI Tools
Research Focus
Methods
Data Collection
Sampling Strategy
Demographics
Survey Design
Data Analysis
Statistical calculations
Qualitative analysis
Findings
RQ 1: Trust in AI and Trust in HR‑AI Tools
Trust in AI
Trust in HR‑AI Tools
Knowledge of Job Seekers About Use of AI in Human Resources
Overall Experience Using HR‑AI Tools
Trust of HR Managers and Recruiters and Job Seekers in HR‑AI Tools
RQ 2: Knowledge about Algorithmic Audits, Experience with Audits
Knowledge about Algorithmic Audits and the New York City Law.
Experience with Algorithmic Audits
RQ3: Stakeholders' Perspectives on Algorithmic Audits of HR‑AI Tools
Importance of Algorithmic Audits
Desired Frequency of Algorithmic Audits
Other Thoughts about Algorithmic Auditing
Human‐in‐the‐loop
Performance of Audits
Independence of Auditor
Discussion
Trust of Stakeholders in AI and in HR‑AI tools
Knowledge about Algorithmic Audits and in particular Algorithmic Audits in HR
Perspectives of Stakeholders and Importance of Algorithmic Audits
Limitations and Future Work
Acknowledgements
Annex
Quotes regarding the performance of audits
To be Cared for or Deceived?
Background
Is it Possible to Operationalize Ethics?
The Non‐Neutrality of Technology
STS, SCOT and Feminist Epistemologies
Digital Technologies as a Lens to Read Embedded Values
The Implementation of Moral Values into Technological Design
Value‐Sensitive Design, Care Ethics and User‐Centered Design Approach
Operationalizing Ethics in the Case of Elderly Care Robots
Social Robotics and Robots to Combat Loneliness
How Can Companion Robots be Ethical?
The Accusation of Deception
Another Perspective: Emotions as Coordination and the Relational View of the Self
New Ways to Determine Deception
Ethics by Law in Social Robotics: Preliminary Reflections on Article 5 of the AI Act
Preliminary Guidelines
Practioner's Corner
Navigating Challenges and Opportunities of Standards Developing Organizations in Times of Rapid Technological Advancement
Ethics in AI and Business
Challenges in Standardizing AI Ethics
Formalizing Ethics and Certification Mechanisms in AI
Successful Co‑Creation of AI Standards: Insights from Practice.
Mechanisms for Ensuring Inclusive and Fair Standards
References.
Notes:
Description based on publisher supplied metadata and other sources.
ISBN:
3-8394-7843-X
9783839478431

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