Trolley Crash

Approaching Key Metrics for Ethical AI Practitioners, Researchers, and Policy Makers
Erscheinungsjahr 2024
ISBN: 978-0-443-15991-6
Verlag: Elsevier Science Publishing Co Inc

Buch, Englisch, 264 Seiten, Format (B × H): 152 mm x 226 mm, Gewicht: 440 g

The prolific deployment of Artificial Intelligence (AI) across different fields has introduced novel challenges for AI developers and researchers. AI is permeating decision making for the masses, and its applications range from self-driving automobiles to financial loan approvals. With AI making decisions that have ethical implications, responsibilities are now being pushed to AI designers who may be far-removed from how, where, and when these ethical decisions occur. Trolley Crash: Approaching Key Metrics for Ethical AI Practitioners, Researchers, and Policy Makers provides audiences with a catalogue of perspectives and methodologies from the latest research in ethical computing. This work integrates philosophical and computational approaches into a unified framework for ethical reasoning in the current AI landscape, specifically focusing on approaches for developing metrics. Written for AI researchers, ethicists, computer scientists, software engineers, operations researchers, and autonomous systems designers and developers, Trolley Crash will be a welcome reference for those who wish to better understand metrics for ethical reasoning in autonomous systems and related computational applications.

Autoren/Hrsg.

Wu, Hsin-Fu

Wu, Peggy

Salpukas, Michael

Ellsworth, Shannon

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
• Mathematik | Informatik EDV | Informatik EDV & Informatik Allgemein Soziale und ethische Aspekte der EDV
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

1. Introduction Michael R. Salpukas, Peggy Wu, Shannon Ellsworth and Hsin-Fu Wu 2. Terms and References Michael R. Salpukas, Peggy Wu, Shannon Ellsworth and Hsin-Fu Wu How is AI Changing Human Behavior? 3. Boiling the Frog: Ethical Leniency due to Prior Exposure to Technology Noah Ari, Nusrath Jahan, Johnathan Mell and Pamela Wisniewski Human Oversight vs. Ethical Simulation in Robots 4. Automated Ethical Reasoners Must Be Interpretation-Capable John Licato 5. Towards Unifying the Descriptive and Prescriptive for Machine Ethics Taylor Olson 6. Competent Moral Reasoning in Robot Applications: Inner Dialog as a Step Towards Artificial Phronesis John Paul Sullins III, Antonio Chella and Arianna Pipitone Measuring, Evaluating, and Auditing Ethical AI 7. Autonomy Compliance with Doctrine and Ethics Ontological Frameworks Donald P. Brutzman, Hsin-Fu Wu, Curtis Blais and Carl Andersen 8. Meaningful Human Control and Ethical Neglect Tolerance; Initial Thoughts on How to Define Model and Measure Them Christopher A. Miller and Marcel Baltzer 9. Continuous automation approach for autonomous Ethics Based Audit of AI Systems Guy Lupo, Quoc Bao Vo and Natania Locke 10. A Tiered Approach for Ethical AI Evaluation Metrics Peggy Wu, Hsin-Fu Wu, Brett Israelsen and Robert Grabowski 11. Designing Meaningful Metrics for Demonstrating Ethical Supervision of Autonomous Systems Donald P. Brutzman and Curtis Blais Research Topics and Methods: Ethical AI and Big Questions 12. Obtaining Hints to Understand Language Model-based Moral Decision Making by Generating Consequences of Acts Rafal Rzepka and Kenji Araki 13. Emerging Issues and Challenges Michael R. Salpukas, Peggy Wu, Shannon Ellsworth and Hsin-Fu Wu Acronyms Appendix Hsin-Fu Wu

Über Autor(innen)

Wu, Peggy
Peggy Wu is an award-winning scientist with over 20 years of experience combining cognitive psychology with AI in Human-Machine systems. She conducts research advancing Knowledge Representation and Reasoning, Human-Computer Etiquette, Socially Intelligent Agents, Virtual/Mixed Reality, and AI explainability, transparency, and trust applied to military, commercial, and space domains. She is a speaker, author, judge for XPrize, and an associate producer of a documentary on the psychology of Space Exploration entitled, "The Longest Goodbye." Her work has been covered by media outlets including National Geographic and the BBC.

Ellsworth, Shannon
Shannon Ellsworth currently leads several fundamental research efforts to apply Artificial Intelligence and Machine Learning to U.S. Department of Defense systems. Her research is based on over 20 years of work in the field and is focused on calculated design of algorithms to support smart command and control applications. She also serves as co-chair to the AI/ML Working Group for the Military Operations Research Society.

Salpukas, Michael
Michael Salpukas is a research and development leader with 25 years of experience transitioning advanced algorithms and robust AI into products. He leads a portfolio of government and internally funded research and development projects designed to provide human assistance to the warfighter and rapid updates to mitigate novel inputs. Michael has authored intellectual property and publications on a variety of topics and is a regular conference panelist/moderator in AI Ethics, AI Assurance, and AI for Manufacturing. He is on the advisory board for the Northeastern University Institute for the Wireless Internet of Things, and is a Judge/Mentor for startups via Activate and MassChallenge.