From Black Box to Glass Box: Building Trustworthy AI in Education
Автор: Stanford Accelerator for Learning
Загружено: 2026-02-06
Просмотров: 27
Описание:
During this session, panelists discuss strategies for designing transparent, accountable, and equitable AI-powered systems that support opportunity and social mobility for all learners.
As AI transforms education, a critical question arises: How can we harness AI to support the development and measurement of the skills and competencies that will drive opportunity and social mobility in the future economy?
This panel confronts pressing challenges such as algorithmic bias, opaque decision-making, and the risk of inequitable outcomes. Our conversation spotlight actionable strategies for building AI-powered systems that are human-centered in design, transparent in operation and accountable to the stakeholders they impact.
Panelists:
Emma Brunskill, Professor of Computer Science, Stanford University
Tony Chan, Former President of King Abdullah University of Science and Technology (KAUST)
Maureen Heymans, VP of Learning (Engineering & GM), Advisor on Sustainability, Google
Matt Johnson, Managing Director, Innovation Research, ETS
Moderator:
Kevin Gutherie, President, ITHAKA
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