Award Abstract # 2125858
NRT-AI: Convergent, Responsible, and Ethical Artificial Intelligence Training Experience for Roboticists

NSF Org: DGE
Division Of Graduate Education
Recipient: UNIVERSITY OF TEXAS AT AUSTIN
Initial Amendment Date: August 27, 2021
Latest Amendment Date: August 25, 2022
Award Number: 2125858
Award Instrument: Continuing Grant
Program Manager: Daniel Denecke
ddenecke@nsf.gov
 (703)292-8072
DGE
 Division Of Graduate Education
EDU
 Directorate for STEM Education
Start Date: September 1, 2021
End Date: August 31, 2026 (Estimated)
Total Intended Award Amount: $2,999,999.00
Total Awarded Amount to Date: $2,999,999.00
Funds Obligated to Date: FY 2021 = $2,415,108.00
FY 2022 = $584,891.00
History of Investigator:
  • Junfeng Jiao (Principal Investigator)
    jjiao@austin.utexas.edu
  • Luis Sentis (Co-Principal Investigator)
  • Joydeep Biswas (Co-Principal Investigator)
  • Min Kyung Lee (Co-Principal Investigator)
  • Justin Hart (Co-Principal Investigator)
Recipient Sponsored Research Office: University of Texas at Austin
110 INNER CAMPUS DR
AUSTIN
TX  US  78712-1139
(512)471-6424
Sponsor Congressional District: 25
Primary Place of Performance: University of Texas at Austin
310 Inner Campus Drive
Austin
TX  US  78712-1007
Primary Place of Performance
Congressional District:
25
Unique Entity Identifier (UEI): V6AFQPN18437
Parent UEI:
NSF Program(s): NSF Research Traineeship (NRT)
Primary Program Source: 04002122DB NSF Education & Human Resource
04002223DB NSF Education & Human Resource
Program Reference Code(s): 9179, SMET
Program Element Code(s): 199700
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.076

ABSTRACT

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.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Carson, Stark and Bohkyung, Chun and Casey, Charleston and Varsha, Ravi and Luis, Pabon and Surya, Sunkari and Tarun, Mohan and Peter, Stone and Justin, Hart "Dobby: A Conversational Service Robot Driven by GPT-4" IEEE International Symposium on Human-Robot Interactive Communication (RO-MAN) , 2023 Citation Details
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Choi, Seung Jun and Jiao, Junfeng and Karner, Alex "Tracing the effects of COVID-19 on short and long bike-sharing trips using machine learning" Travel Behaviour and Society , v.35 , 2024 https://doi.org/10.1016/j.tbs.2024.100738 Citation Details
Choi, Yoonseo and Kang, Eun Jeong and Lee, Min Kyung and Kim, Juho "Creator-friendly Algorithms: Behaviors, Challenges, and Design Opportunities in Algorithmic Platforms" 9. Creator-Friendly Algorithms: Behaviors, Challenges, and Design Opportunities in Algorithmic Platforms , 2023 https://doi.org/10.1145/3544548.3581386 Citation Details
Claure, Houston and Chang, Mai Lee and Kim, Seyun and Omeiza, Daniel and Brandao, Martim and Lee, Min Kyung and Jung, Malte "Fairness and Transparency in Human-Robot Interaction" 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI) , 2022 https://doi.org/10.1109/HRI53351.2022.9889421 Citation Details
Collier, C. "AI as an Emancipatory Technology: Smart Hand Tools for Skilled Trade Workers" 57th Annual Hawaii International Conference on System Sciences. , 2023 Citation Details
Collier, C. "Co-Designing Socio-Technical Interventions with Skilled Trade Workers" IEEE International Symposium on Technology and Society, Public Interest Technology (PIT) for Innovation in Global Development Workshop , 2023 Citation Details
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