Shaping the future of responsible AI
Shaping the future of responsible AI
https://www.udel.edu/udaily/2026/march/xiao-fang-artifical-intelligence-ai-responsible-use/
Publish Date: 2026-03-18 09:54:00
Source Domain: www.udel.edu
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Risks and Rewards of AI: Fang emphasizes both the benefits and risks of AI, notably highlighting the ease of generating misinformation and social, gender, and racial biases in AI-generated content.
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Bias Mitigation: Research by Fang and collaborators shows that AI systems can reflect and perpetuate biases present in training data, requiring focus on fairness, transparency, and accountability.
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Improved Industry Classification: Fang’s research developed an AI-based system to more adaptively and objectively classify companies based on their business activities and language, improving upon traditional manual methods.
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Transparent AI Models: Fang’s team introduced an interpretable AI model that explains its predictions, essential for applications like medical diagnosis where transparency is critical.
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Regulation as an Objective: Fang advocates seeing regulation not as a constraint but an objective, suggesting that embedding social objectives like fairness directly into business strategies benefits organizations in the long run.
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Mentorship and Future Research: Fang is dedicated to mentoring doctoral students to foster the next generation of responsible, application-driven AI researchers who can continue to build on his principles.
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Responsible AI Design: Fang promotes responsible AI design that prioritizes transparency, fairness, and accountability, aligning economic and social objectives for sustainable success.
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Innovation and Accountability: Fang believes that innovation and accountability are complementary and that designing responsible AI systems is vital for reshaping business and society positively.
