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Ethical AI

A National Science Foundation Research Traineeship Program

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NRT-AI: Convergent, Responsible, and Ethical Artificial Intelligence Training Experience for Roboticists

Given the potentially disruptive consequences of artificial intelligence (AI)-based systems, humanity cannot afford to wait until problems arise to consider their impacts on society. AI’s ethical and societal implications must be considered as systems are designed, developed, and deployed. The increasingly ubiquitous adoption of robots in homes and cities is poised to transform our society. However, it remains an open question whether this technology will develop in a way that increases the divide between haves and have-nots or results in a more just and equitable society. Thus, there is a need for convergent STEM graduate education to ensure that future roboticists are prepared to consider ethical implications of robotics technology and build a more just and equitable future for everyone.

This National Science Foundation Research Traineeship (NRT) award to the University of Texas at Austin will address the challenge of integrating responsible and ethical AI at all stages of development, design, and deployment of service robots. The Convergent, Responsible, and Ethical AI Training Experience for Roboticists (CREATE Roboticists) program will integrate ethical robotics education, research, and career development. The program will train 32 funded trainees and 150 additional graduate students from the Departments of Aerospace, Computer Science, Electrical Engineering, and Mechanical Engineering, and Schools of Architecture, Information, and Public Affairs.

CREATE Roboticists will train future roboticists who: (i) understand the ethical implications of service robots and can develop new theories, methods, and techniques to satisfy ethical requirements; (ii) design human-centered ethical service robots that respect human autonomy and ethical values; and (iii) develop robotics policy informed by cutting edge convergent research. This program includes six elements: coursework, research opportunities, mentorship, professional development, internships, and public service. Interdisciplinary coursework will include five new courses, four of which are foundation courses, and a project-based capstone course.

Trainees will engage in research projects across four domains: delivery systems, office service mobile robots, personal home robots, and industrial robots. Two faculty members will mentor each trainee over the five years of the program, with at least one mentor external to the student’s home department. Mentors and students will develop personalized individual development plans (IDPs) in the students’ first year as trainees. They will revise these IDPs each semester in subsequent years of the program. The trainees will also participate in ten hours of career development workshops every semester on topics including article publication and grant-writing, startups and industry opportunities, and career planning. Trainees will enhance their education with internships at a private company, government, or non-profit organization. Finally, NRT trainees will spend about one day per month volunteering for a local government program or non-profit organization connected to robotics and AI.

The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary or convergent research areas through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs.

Partners

School of Architecture | The University of Texas at Austin

Department of Computer Science | The University of Texas at Austin

Department of Aerospace Engineering & Engineering Mechanics | The University of Texas at Austin

LBJ School of Public Affairs | The University of Texas at Austin

School of Information | The University of Texas at Austin

Cockrell School of Engineering | The University of Texas at Austin

Office of the Vice President for Research | The University of Texas at Austin

Graduate School | The University of Texas at Austin

Office of the Vice President for Research | The University of Texas at Austin

Good Systems A UT Grand Challenge | The University of Texas at Austin

Texas Robotics | The University of Texas at Austin

Machine Learning Lab | The University of Texas at Austin

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Questions?
Contact Director Dr. Junfeng Jiao or Senior Research Program Coordinator Saleh Afroogh

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