医疗保健算法存在隐藏偏见:建立公平数据系统的经验教训
在这个数据驱动的决策日益影响世界的时代,确保这些系统的公平和公正从未如此重要。人工智能模型和其他数据系统的训练,有时会导致最新数据系统的输出中存在历史偏见。
Karla Yee Amezaga is Lead in the Data Policy team (Centre for the Fourth Industrial Revolution) and Lead of the "Resilient Governance and Regulation" working group of the AI Governance Alliance. She is originally from Mexico. She is passionate about exploring the ways in which AI, data and technology in general can promote digital transformation of governments, cross-sector collaboration, user-centered services, and inclusive development around the world. Prior to joining the Forum, Karla worked at the Inter-American Development Bank (IDB), supporting digital government and statistical capacity building projects. Before that, she worked at the World Bank, OECD, Ashoka Changemakers, and the Mexican Ministry of Foreign Affairs.
Karla holds a master’s degree in International Affairs from the University of California - San Diego (UCSD), and bachelor’s degrees in Political Science and in International Relations from the Autonomous Technological Institute of Mexico (ITAM).
在这个数据驱动的决策日益影响世界的时代,确保这些系统的公平和公正从未如此重要。人工智能模型和其他数据系统的训练,有时会导致最新数据系统的输出中存在历史偏见。
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