Every year at NeurIPS, machine learning researchers gather and discuss exciting applications of machine learning in areas such as public health, disaster response, climate change, education, and more. However, many of these same researchers are expressing growing concern about applications of machine learning for surveillance (Nanayakkara et al., 2021). This paper presents a brief overview of strategies for resisting these surveillance technologies and calls for greater collaboration between machine learning and human-computer interaction researchers to address the threats that these technologies pose.
翻译:每年在NeurIPS,机器学习研究人员收集和讨论机器学习在公共卫生、救灾、气候变化、教育等领域的令人兴奋的应用,然而,许多同样的研究人员对机器学习用于监测的情况日益表示关切(Nanayakkara等人,2021年),本文简要概述了抵制这些监视技术的战略,呼吁加强机器学习和人类计算机互动研究人员之间的合作,以应对这些技术构成的威胁。