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cover of episode On Shaping the Global Terrain of AI Competition with Tim Hwang

On Shaping the Global Terrain of AI Competition with Tim Hwang

2020/6/25
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Last Week in AI

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Tim Hwang: 本文主要探讨民主国家如何在不牺牲自身价值观的情况下,有效地与人工智能领域的专制政权竞争。作者认为,人工智能并非一成不变,其发展方向是可以塑造的。通过优先发展某些技术方向,例如减少对数据的依赖、促进支持民主合法性的技术以及挑战人工智能在社会控制方面的应用,民主国家可以在人工智能竞争中获得优势。 作者提出了“地形策略”的概念,即通过塑造人工智能的研究方向和优先级,来创造对民主国家有利的竞争环境。具体来说,可以通过投资单样本学习、元学习和模拟学习等技术来减少对数据的依赖;可以通过投资可解释性和公平性等技术来促进支持民主合法性的技术;可以通过投资对抗样本技术并将其应用于赋能活动家来挑战人工智能在社会控制方面的应用。 作者认为,单纯增加资金投入并非有效的竞争策略,应该更关注如何引导研究方向,并考虑不同治理体系对人工智能部署的影响。 Andrey Kurenkov: Andrey Kurenkov主要就Tim Hwang提出的观点进行提问和讨论,并结合自身的研究经历和对AI领域的理解,对Tim Hwang的观点进行补充和佐证。例如,Andrey Kurenkov就模拟学习的应用和政府激励措施的有效性发表了自己的看法,并提及了DARPA竞赛等案例。同时,Andrey Kurenkov也对深度伪造技术、面部识别技术等具体应用场景进行了探讨,并表达了对这些技术潜在风险的担忧。

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Tim Hwang discusses the challenge democracies face in competing with authoritarian regimes in AI, suggesting that democracies can advance AI without sacrificing their values by focusing on areas within AI that align with democratic principles.

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Stanford AI Lab PhD Andrey Kurenkov interviews Tim Hwang, Research Fellow at Georgetown’s Center for Security and Emerging Technology (CSET) about his new report “Shaping the Terrain of AI Competition” and more.

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