UT Austin: Tenure-Track Faculty Hiring in Human-Centered and Responsible AI Systems
UT Austin is hiring up to two tenure-track faculty in Building Human-Centered, Ethical, and Responsible AI Systems. The last day to apply isis December 1, 2024. The positions are focused on research that advances and supports the development of human-centered and responsible AI systems.
UT Austin is hiring up to two tenure-track faculty in Human-Centered and Responsible AI Systems.
The School of Information (iSchool) at The University of Texas at Austin (UT Austin) seeks to hire up to two tenure-track faculty in Building Human-Centered, Ethical, and Responsible AI Systems. The last day to apply isis December 1, 2024. The application review and scheduling of initial zoom interviews will begin on November 1, 2024.
The positions are focused on research that advances and supports the development of human-centered and responsible AI systems. The call is intended to be broadly inclusive of various AI subdisciplines, such as machine learning, natural language processing, and computer vision. Candidates should develop AI systems in their research and investigate methods that integrate AI with human computation, complementary human-AI teaming and workflow design, human-in-the-loop decision-making and decision support, AI-assisted data annotation, accelerating and improving human-centered AI evaluation protocols, and imagining other novel forms of human-AI partnerships.
Potential outcomes of such research may include advancing fundamental understanding of the nature and range of human-AI partnerships, as well as how best to design, build, and evaluate them, investigating potential productivity benefits, such as the speed, scale, quality, and/or economics of human labor with vs. without AI-augmentation, advancing ethical and responsible design for system users, AI supply-chain workers, and society at-large around issues such as trustworthiness andreliability; transparency and interpretability; fairness andsocial justice (for both AI users and workers); and accountability and algorithmic recourse, protecting private and sensitive data; the information environment andand information integrity; human safety, health, and wellbeing; and sustainable, green computing.
Tags: UT Austin, AI Systems, Human-Centered AI, Responsible AI, Faculty Hiring, Machine Learning, Natural Language Processing, Computer Vision, Human-Computation, Workflow Design, Human-AI Teaming, Data Annotation, Evaluation Protocols, Human-AI Partnerships, Productivity Benefits, Ethical Design, Research, Sustainable Computing