Any machine constructed for the purpose of making decisions,
if it does not possess the power of learning, will be completely literal-minded.
Woe to us if we let it decide our conduct, unless we have previously examined its
laws of action, and know fully that its conduct will be carried out on principles
acceptable to us!
(N. Wiener, 1954)
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: 1) Stimulating potential collaborations
among researchers with different background; 2) Identifying critical ethical questions and problems which
may become the subject matter of future research projects within the SMC community and related areas; 3)
Finding a common vocabulary to support the communication of technological achievements to non-expert people
or to the large public; 4) Outlining how ethical aspects could be integrated into educational programme
for future machine learning scientists.
Morning Session | Afternoon Session |
09:00 Welcome address [Slides] [Video] | 14:10 Mireille Hildebrandt, The issue of bias: trade-offs and balance in ML [Abstract] [Slides] [Video] |
09:10 Judith Simon, Big data & machine learning: Reflections on trust, trustworthiness & responsibility [Abstract] [Slides] [Video] | 14:50 Krishna Gummadi, Discrimination in human vs. machine decision making [Abstract] [Slides] [Video] |
09:50 Katherine Strandburg, Decision-making, machine learning and the value of explanation [Abstract] [Slides] [Video] | 15:30 Michael Veale, How do public values get into public sector machine learning systems, if at all? [Abstract] [Slides][Video] |
10:30 Coffee Break | 15:45 Lucia Sommerer, Under the electronic eye: A legal evaluation of predictive policing [Abstract] |
10:50 Fabio Roli, Some thoughts on safety of machine learning [Abstract] [Slides] [Video] | 16:00 Coffee Break |
11:30 Viola Schiaffonati, Preliminary steps for experimentally evaluating the impact of AI and robotic technologies [Abstract] [Slides] [Video] | 16:20 Marília Monteiro, Innovating in democracy - machine learning and social participation: Can we hack law-making? [Abstract] [Slides] [Video] |
12:10 Zackary C. Lipton, The mythos of model interpretability [Abstract] [Slides] [Video] | 16:35 Matthias Treder, Mining the mind: Machine learning in brain research [Abstract] [Slides] [Video] |
12:25 Federico Cabitza, The unintended consequences of chasing electric zebras [Abstract] [Slides] [Video] | 16:50 Arshak Navruzyan, Avoiding bad machine learning predictions in critical decision domains [Abstract] |
12:40 Lunch Break | 17:30 Bettina Berendt, What does it mean to ask about "the human use of machine learning" - on positioning (not only) for engineers [Abstract] [Slides] [Video] |
18:10 - 18:30 Open discussion and closing remarks |
The workshop will take place in the beautiful setting of the European Centre for Living Technology (ECLT), an interdisciplinary research centre devoted to study of complex systems and network science, located in the historical centre of Venice.
European Centre for Living Technology, Ca' Minich, S. Marco 2940 30124 Venice
How to reach us E-mail: eclt@unive.it Website: http://www.ecltech.org/