Trolley Crash : Approaching Key Metrics for Ethical Ai Practitioners, Researchers, and Policy Makers

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

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.

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.

Hsin-Fu “Sinker” Wu performs operations research for business development and customer engagement. Sinker served a 20-year career in the U.S. Navy, in which he developed and implemented strategies for coalition, joint, naval, and undersea warfare. He co-authored a report on Ethical Control of autonomous systems for naval missions and is an AI Assurance researcher.

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.