The Human Use of Machine Learning: An Interdisciplinary Workshop
The development of machine learning has suggested ethical worries from its very beginning. Norbert Wiener, for example, as early as mid-fifties warned against a too simplistic idea of progress, divorced from any ethical guidance thereby reminding us the idea that there is no isolated “pure” science and that scientific and technological progress is in most of the cases socially and ethically mediated. Inspired by that far-seeing reflection, we would like to stimulate a discussion starting from very basic questions such as: How do we reframe the notions of “wrong” and “good” in the context of machine learning and of data-driven technologies? What does it mean being responsible in today’s machine learning research and application? What is the place of moral values in the design process? How could we deal with engineering constrains, like efficacy or costs, in an ethical way? What is social good? What could be the social mission of machine learning? We do feel that this could provoke researchers to think critically about the philosophical underpinnings of today’s machine learning research encouraging a cross-fertilization of ideas and an “imaginative forward glance.”
With this workshop we aim at:
- Stimulating potential collaborations among researchers with different background;
- Identifying critical ethical questions and problems which may become the subject matter of future research projects within the SMC community and related areas;
- Finding a common vocabulary to support the communication of technological achievements to non-expert people or to the large public;
- Outlining how ethical aspects could be integrated into educational programme for future machine learning scientists.
See the workshop's website for details: http://www.dsi.unive.it/HUML2016/.