Trust Engineering for Human-AI Teams
| العنوان: | Trust Engineering for Human-AI Teams |
|---|---|
| المؤلفون: | Sam Hepenstal, Christopher A. Miller, Yang Cai, Sylvain Bruni, Dylan D. Schmorrow, Neta Ezer |
| المصدر: | Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 63:322-326 |
| بيانات النشر: | SAGE Publications, 2019. |
| سنة النشر: | 2019 |
| مصطلحات موضوعية: | Medical Terminology, Knowledge management, Computer science, business.industry, 05 social sciences, 0501 psychology and cognitive sciences, business, 050107 human factors, 050105 experimental psychology, Medical Assisting and Transcription |
| الوصف: | Human-AI teaming refers to systems in which humans and artificial intelligence (AI) agents collaborate to provide significant mission performance improvements over that which humans or AI can achieve alone. The goal is faster and more accurate decision-making by integrating the rapid data ingest, learning, and analyses capabilities of AI with the creative problem solving and abstraction capabilities of humans. The purpose of this panel is to discuss research directions in Trust Engineering for building appropriate bi-directional trust between humans and AI. Discussions focus on the challenges in systems that are increasingly complex and work within imperfect information environments. Panelists provide their perspectives on addressing these challenges through concepts such as dynamic relationship management, adaptive systems, co-discovery learning, and algorithmic transparency. Mission scenarios in command and control (C2), piloting, cybersecurity, and criminal intelligence analysis demonstrate the importance of bi-directional trust in human-AI teams. |
| تدمد: | 1071-1813 2169-5067 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::95112bc28ec4749ee92321f0c3284ffc https://doi.org/10.1177/1071181319631264 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi...........95112bc28ec4749ee92321f0c3284ffc |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 10711813 21695067 |
|---|