How Do You Build a Better Robot? By Understanding People.
Computer scientist Dorsa Sadigh discusses the growing field of human-robot interaction.
Whether it’s autonomous vehicles or assistive technology in healthcare that can do things like help the elderly do core tasks like feeding themselves, some of the most challenging problems in the field of robotics involve how robots interact with humans, with all of our many complexities.
Drawing from fields as varied as cognitive neuroscience, psychology, and behavioral economics, Stanford computer scientist Dorsa Sadigh is exploring how to train robots to better understand humans – and how to give humans the skills to more seamlessly work with robots.
She discusses these challenges with Stanford Engineering’s The Future of Everything host Professor Russ Altman, a Stanford HAI associate director, in this latest episode.
Stanford HAI's mission is to advance AI research, education, policy and practice to improve the human condition. Learn more.
Related News
PsychAdapter lets researchers dial in on personality traits, age, and mental health characteristics to generate text that sounds like real individuals, opening the door to training simulations and personalized content.
PsychAdapter lets researchers dial in on personality traits, age, and mental health characteristics to generate text that sounds like real individuals, opening the door to training simulations and personalized content.
Reading Today’s Headlines Through AI: A Real-Time Audit of Six Commercial Chatbots
In a new study, scholars measured how accurately popular AI chatbots answered questions about the emerging news and found substantial regional disparity, dependence on distinct information ecosystems, and acute fragility under imperfect prompts.
In a new study, scholars measured how accurately popular AI chatbots answered questions about the emerging news and found substantial regional disparity, dependence on distinct information ecosystems, and acute fragility under imperfect prompts.
Two models working together perform worse than one alone, exposing a critical gap in artificial intelligence capabilities.
Two models working together perform worse than one alone, exposing a critical gap in artificial intelligence capabilities.