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Award ID contains: 1917707

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  1. ; ; ; (, AI & SOCIETY)
    In this paper, we outline a new method for evaluating the human impact of machine-learning (ML) applications. In partnership with Underwriters Laboratories Inc., we have developed a framework to evaluate the impacts of a particular use of machine learning that is based on the goals and values of the domain in which that application is deployed. By examining the use of artificial intelligence (AI) in particular domains, such as journalism, criminal justice, or law, we can develop more nuanced and practically relevant understandings of key ethical guidelines for artificial intelligence. By decoupling the extraction of the facts of the matter from the evaluation of the impact of the resulting systems, we create a framework for the process of assessing impact that has two distinctly different phases. 
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  2. ; ; (, Techné: Research in Philosophy and Technology)
    null (Ed.)
    Few sectors are more affected by COVID-19 than higher education. There is growing recognition that reopening the densely populated communities of higher education will require surveillance technologies, but many of these technologies pose threats to the privacy of the very students, faculty, and staff they are meant to protect. The authors have a history of working with our institution’s governing bodies to provide ethical guidance on the use of technologies, especially including those with significant implications for privacy. Here, we draw on that experience to provide guidelines for using surveillance technologies to reopen college campuses safely and responsibly, even under the specter of covid. We aim to generalize our recommendations, so they are sensitive to the practical realities and constraints that universities face. 
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  3. (, The Philosophers' Magazine)
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