"Chinese philosophy before our Christian era is emphasized in this nontechnical summary of Chinese thought. Professor Creel also deals with Confucianism, the ideas of Mo-tsu and Mencius, Taoism, Legalism, and their variations and adaptations. As an introduction for the general reader, this book stands among the best."—_China: A Resource and Curriculum Guide_ "There exists nowhere else such a well-written presentation of the main trends in Chinese thought in so brief a space. The text is not cluttered with Chinese names (...) and the pages are not weighed down with footnotes—but the references are there for those who want them, with suggestions for further readings. This is a book which can be understood by those who have never read anything else about China."—_The New York Times Book Review _. (shrink)

Scientists depend on complex computational systems that are often ineliminably opaque, to the detriment of our ability to give scientific explanations and detect artifacts. Some philosophers have s...

While feminist critiques of AI are increasingly common in the scholarly literature, they are by no means new. Alison Adam’s Artificial Knowing (1998) brought a feminist social and epistemological stance to the analysis of AI, critiquing the symbolic AI systems of her day and proposing constructive alternatives. In this paper, we seek to revisit and renew Adam’s arguments and methodology, exploring their resonances with current feminist concerns and their relevance to contemporary machine learning. Like Adam, we ask how new AI (...) methods could be adapted for feminist purposes and what role new technologies might play in addressing concerns raised by feminist epistemologists and theorists about algorithmic systems. In particular, we highlight distributed and federated learning as providing partial solutions to the power-oriented concerns that have stymied efforts to make machine learning systems more representative and pluralist. (shrink)

This article examines the complaint that arbitrary algorithmic decisions wrong those whom they affect. It makes three contributions. First, it provides an analysis of what arbitrariness means in this context. Second, it argues that arbitrariness is not of moral concern except when special circumstances apply. However, when the same algorithm or different algorithms based on the same data are used in multiple contexts, a person may be arbitrarily excluded from a broad range of opportunities. The third contribution is to explain (...) why this systemic exclusion is of moral concern and to offer a solution to address it. (shrink)