论文标题
通过负责AI创新来解决Covid-19：朝正确方向五个步骤
Tackling COVID-19 through Responsible AI Innovation: Five Steps in the Right Direction
论文作者
论文摘要
数据科学和AI/ML的创新在支持全球与Covid-19的努力方面起着核心作用。 AI/ML技术的多功能性使科学家和技术人员能够应对广泛的生物医学，流行病学和社会经济挑战。然而，这种广泛的科学能力也引起了各种各样的道德挑战。研究人员需要在解决SARS-COV-2方面迅速和全球采取行动，要求在创新生态系统受到专有保护主义，不平等和缺乏公众信任的障碍时，需要开放研究和负责任的数据共享的前所未有的做法。此外，诸如数字接触跟踪之类的社会影响力干预措施正在引起人们对监视蠕变的担忧，并且挑战了对隐私，自治和公民自由的广泛承诺。鉴于病毒对弱势社会群体的不同影响以及有偏见和歧视性的公共卫生局势的生命和死亡后果，同样，对数据驱动的创新可能起作用，以增强基于社会不平等的动态以及有偏见和歧视性公共卫生欧现代的影响，这同样加剧了大一的关注。为了解决这些问题，我提供了五个步骤，以鼓励负责任的研究和创新。这些提供了基于练习的途径，以开放，负责，公平和民主管理的流程和产品为中心。从一开始就采取这些步骤，这些步骤不仅将增强创新者负责任地解决COVID-19的能力，而且更广泛地将有助于更好地为数据科学和AI/ML社区配备来应对未来的大流行，并支持更加人性化，理性和公正的社会。
Innovations in data science and AI/ML have a central role to play in supporting global efforts to combat COVID-19. The versatility of AI/ML technologies enables scientists and technologists to address an impressively broad range of biomedical, epidemiological, and socioeconomic challenges. This wide-reaching scientific capacity, however, also raises a diverse array of ethical challenges. The need for researchers to act quickly and globally in tackling SARS-CoV-2 demands unprecedented practices of open research and responsible data sharing at a time when innovation ecosystems are hobbled by proprietary protectionism, inequality, and a lack of public trust. Moreover, societally impactful interventions like digital contact tracing are raising fears of surveillance creep and are challenging widely held commitments to privacy, autonomy, and civil liberties. Prepandemic concerns that data-driven innovations may function to reinforce entrenched dynamics of societal inequity have likewise intensified given the disparate impact of the virus on vulnerable social groups and the life-and-death consequences of biased and discriminatory public health outcomes. To address these concerns, I offer five steps that need to be taken to encourage responsible research and innovation. These provide a practice-based path to responsible AI/ML design and discovery centered on open, accountable, equitable, and democratically governed processes and products. When taken from the start, these steps will not only enhance the capacity of innovators to tackle COVID-19 responsibly, they will, more broadly, help to better equip the data science and AI/ML community to cope with future pandemics and to support a more humane, rational, and just society.
