AI and Ethics Handbook

This Handbook summarizes in everyday language the ethical, regulatory, and policy implications that arise from the use of Artificial Intelligence (AI). Designed to bridge the gap between technical and non-technical professionals, it focuses on where AI techniques, tools, and technologies may lead in the future. Particular attention is given to the potential intentional and unintentional misuses of AI, and how these misuses may be prevented.

Coverage includes:

• Ethical questions and concerns that arise from basic research and the design and use of practical applications of AI
• Regulatory frameworks and guidelines, including self-regulation and constraints, and controls on development and implementation of AI technologies
• Emergent public policy and the possibility of legislative interventions linked to current and future ethical issues related to the use of AI technologies and their applications
• How to balance the relation between technology-law-society

• Data provenance and validity

  Provides easy and convenient access to critical topics by including vetted references Bridges the gap between system developers, and corporate and government policymakers Pulls together perspectives of many disciplines in one volume

  Autorentext

Larry Medsker is Past Chair of the US Technology Policy Committee for the Association for Computing Machinery. He is an Affiliate Faculty at George Mason University where he is the Director of the Science & Technology Ethics Policy (STEP) Collaborative. He is also Research Professor of Physics at the University of Vermont (UVM). He is a member of the Human-Technology Collaboration Lab at George Washington University and was Founding Director of their Master s Program in Data Science. Medsker serves as Co-Editor-in-Chief of AI and Ethics, Associate Editor of Neural Computing and Applications, and Policy Officer for ACM s Special Interest Group on Artificial Intelligence (SIGAI). He is the author of four books and over 100 publications on neural networks and AI.

Inhalt

Foundational and Critical Ethical Concerns.- 1 Fairness and Bias -- Racial and Gender Bias.- 2 Privacy and Date Protection -- Digital systems, data privacy.- 3 Misinformation and Disinformation.- 4 Transparency.- 5 Accountability.- 6 Safety -- Safe Systems -- Safer Technology and Systems.- 7 Cybersecurity.- 8 Trustworthy AI.- 9 Explainable AI.- 10 Human Oversight and Human-centered AI.- 11 Generative AI Use and Misuse.- 12 Disabilities -- Accessibility.- 13 AI and Workfore -- Future of Work.- 14 Education and Training.- 15 Data Science -- Machine Learning and Deep Learning.- 16 AI and Data Governance.- 17 Provenance -- Data Quality.- 18 Algorithmic Systems and Decision Systems.- 19 AI for Social Good.- 20 Cultural and Ethical Values in AI.- Applications, Governance, and Societal Impact.- 1 Racial and Gender Bias.- 2 Compliance and Regulation.- 3 Election Security.- 4 Health and Medicine.- 5 Society -- Social Impact Social Media.- 6 Technology Impact on Youth and Children.- 7 Automation Technology -- Automated vehicles, weapons, robotics.- 8 Sustainability -- Environment -- Climate -- Environmental Impacts of AI.- 9 State and Local Govenment.- 10 Technology Impact on Youth and Children.- Specialized Topics, Emerging Areas.- 1 Digital Twins.- 2 Agricultural Economics & Policy.- 3 Manufacturing and Industry.- 4 Entertainment Industry.- 5 General Intelligence.- 6 Quantum Computing.- 7 Internet of Things.- 8 Religion and Theology.- 9 Law Practice and Legal Technology.- 10 Business and Finance -- Human Resources -- Marketing.- 11 Intellectual Property.