Connectionists: ESANN 2019 SS - Societal Issues in Machine Learning: When Learning from Data is Not Enough

[Luca Oneto]

[Apologies if you receive multiple copies of this CFP]

Call for papers: special session on "Societal Issues in Machine Learning:
When Learning from Data is Not Enough" at ESANN 2019

European Symposium on Artificial Neural Networks, Computational
Intelligence and Machine Learning (ESANN 2019).
24-26 April 2019, Bruges, Belgium - http://www.esann.org

DESCRIPTION:
It has been argued that Artificial Intelligence (AI) is experiencing a fast
process of commodification. This characterization is on the interest of big
IT companies, but it correctly reflects the current industrialization of
AI. This phenomenon means that AI systems and products are reaching the
society at large and, therefore, that societal issues related to the use of
AI and Machine Learning (ML) cannot be ignored any longer. Designing ML
models from this human-centered perspective means incorporating
human-relevant requirements such as safety, fairness, privacy, and
interpretability, but also considering broad societal issues such as ethics
and legislation. These are essential aspects to foster the acceptance of
ML-based technologies, as well as to be able to comply with an evolving
legislation concerning the impact of digital technologies on ethically and
privacy sensitive matters. This special session aims to put forward the
state-of-the-art on these increasingly relevant topics among ML
theoretician and practitioners. For this purpose, we welcome both solid
contributions and preliminary relevant results showing the potential, the
limitations and the challenges of new ideas, refinements, or contaminations
between the different fields of research, ML, and related approaches in
facing real-world problems involving societal issues. We welcome works on
ML theory, applications to topics listed below as well as other topics of
social relevance. Studies stemming from major research initiatives and
projects focusing on the session topics are particularly welcome.

TOPICS OF INTEREST:
- Fairness as an element in the development of ML techniques;
- Ethical issues in the application of ML and related techniques in areas
of social impact;
- Privacy as a challenge in ML application to problems in the social domain;
- Interpretability and explainability of ML and related approaches;
- Safety and Security of ML and related methods in safety critical contexts;
- Legislative challenges to the use of ML and related methods;
- The challenge of complex data for ML and related methods;
- Transparency and open data.

SUBMISSION:
Prospective authors must submit their paper through the ESANN portal
following the instructions provided in
https://www.elen.ucl.ac.be/esann/index.php?pg=submission  Each paper will
undergo a peer reviewing process for its acceptance. Authors should send as
soon as possible an e-mail with the tentative title of their contribution
to the special session organisers.

IMPORTANT DATES:
Submission of papers: 19 November 2018
Notification of acceptance: 31 January 2019
ESANN conference: 24 - 26 April 2019

SPECIAL SESSION ORGANISERS:
Davide Bacciu, University of Pisa (Italy)
Battista Biggio, University of Cagliari (Italy)
José D. Martín, Universitat de València (Spain)
Luca Oneto, University of Genoa (Italy)
Alfredo Vellido, Universitat Politècnica de Catalunya (Spain)
Paulo J. G. Lisboa, Liverpool John Moores University (UK)

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Luca Oneto, PhD                            University of Genoa
web: www.lucaoneto.com               DIBRIS Department
e-mail: Luca.Oneto at unige.it          SmartLab Laboratory
e-mail: Luca.Oneto at gmail.com     Via Opera Pia 11a
Fax: +39-010-3532897                   16145 Genoa ITALY
Phone: +39-010-3532192               www.smartlab.ws
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