Description
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.- Presents a comparison between human oversight and ethical simulation in robots- Introduces approaches for measuring, evaluating, and auditing ethical AI- Investigates how AI and technology are changing human behavior
Table of Contents
1. IntroductionMichael R. Salpukas, Peggy Wu, Shannon Ellsworth and Hsin-Fu Wu2. Terms and ReferencesMichael R. Salpukas, Peggy Wu, Shannon Ellsworth and Hsin-Fu WuHow is AI Changing Human Behavior?3. Boiling the Frog: Ethical Leniency due to Prior Exposure to TechnologyNoah Ari, Nusrath Jahan, Johnathan Mell and Pamela WisniewskiHuman Oversight vs. Ethical Simulation in Robots4. Automated Ethical Reasoners Must Be Interpretation-CapableJohn Licato5. Towards Unifying the Descriptive and Prescriptive for Machine EthicsTaylor Olson6. Competent Moral Reasoning in Robot Applications: Inner Dialog as a Step Towards Artificial PhronesisJohn Paul Sullins III, Antonio Chella and Arianna PipitoneMeasuring, Evaluating, and Auditing Ethical AI7. Autonomy Compliance with Doctrine and Ethics Ontological FrameworksDonald P. Brutzman, Hsin-Fu Wu, Curtis Blais and Carl Andersen8. Meaningful Human Control and Ethical Neglect Tolerance; Initial Thoughts on How to Define Model and Measure ThemChristopher A. Miller and Marcel Baltzer9. Continuous automation approach for autonomous Ethics Based Audit of AI SystemsGuy Lupo, Quoc Bao Vo and Natania Locke10. A Tiered Approach for Ethical AI Evaluation MetricsPeggy Wu, Hsin-Fu Wu, Brett Israelsen and Robert Grabowski11. Designing Meaningful Metrics for Demonstrating Ethical Supervision of Autonomous SystemsDonald P. Brutzman and Curtis BlaisResearch Topics and Methods: Ethical AI and Big Questions12. Obtaining Hints to Understand Language Model-based Moral Decision Making by Generating Consequences of ActsRafal Rzepka and Kenji Araki13. Emerging Issues and ChallengesMichael R. Salpukas, Peggy Wu, Shannon Ellsworth and Hsin-Fu WuAcronyms AppendixHsin-Fu Wu
