- We need to research on how the interaction with machines affects human intelligence and cognitive capacities, if changing or diminishing them. In addition, we should research on how artificial intelligence changes relations between humans and between humans and the environment. While recent literature is focusing on the interaction between AI systems and adults, there are important differences in the way children deal with artificial systems that should be further researched, being the next generation to come.
- Machine intelligence systems should be developed by humans in a responsible way. We should formalize and incorporate ethical principles in machine intelligence development and evaluation. We should also foster diversity (in terms of expertise and demographics, particularly gender), in teams that develop and are empowered with artificial intelligence to reflect varied perspectives into the developed systems.
- Machine intelligence has a wide range of potential economic implications. There are already major concerns about the impact on human employment, wages and income distribution. The growing information asymmetry between humans and intelligent machines, and the potential for moral hazard and exploitation of human cognitive biases, will affect human behaviour and welfare. Competition between machines with scalable information processing capacities and humans with limited capacities will induce systemic shifts, including in the institutional structures of human societies.
- There is a need to understand who controls the results of AI, what is done in AI, and for whom, and establish adequate forecasting, control mechanisms and legal provisions to anticipate and revert situations in which algorithms can be used against people's welfare, as well as establish adequate laws that ensure algorithms are used for people's welfare. Finally, these mentioned points can be applied in different application domains. In this respect, we concluded that there are some aspects of algorithms that can be analysed independently of the application context. For instance, we agreed that the potential construction of isolation bubbles on the side of users in music recommender systems should be carefully counter-acted in order to keep the collective and transformative power of music at its best. This is also shared in other domains. However, there are some other issues that should be considered for particular use cases. In terms of algorithmic transparency, for instance, the interpretability of algorithms is crucial in healthcare applications, while it can be less critical in music recommendation. All of this requires multidisciplinary thinking, diverse teams and future impact assessment, as we should be watchful for forthcoming disruption on the way we see ourselves and the surrounding world.
25 List of workshop participants and report contributors
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Dr. Alessandro Annoni, Head of Digital Economy Unit, Leader of Artificial Intelligence Project.
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Dr. Benito Arruñada, Economy and Business Department, Universitat Pompeu Fabra, Barcelona
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Dr. Xerxes D. Arsiwalla, Institute for Bioengineering of Catalonia.
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Dr. Carlos Castillo, Social Computing and Web Mining.
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Dr. Vicky Charisi, Centre for Advanced Studies, Joint Research Centre, European Commission.
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Emanuele Cuccillato, Behavioural Insights and Design for Policy Unit, Joint Research Centre, European Commission.
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Prof. Veronica Dahl, Professor of Computing Science, Simon Fraser University, Canada.
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Prof. Dr. Gustavo Deco, Computational neuroscience, Director of the Centre for Brain and Cognition, Universitat Pompeu Fabra.
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Dr. Blagoj Delipetrev, Digital Economy Unit, Joint Research Centre, European Commission.
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Dr. Paul Desruelle, Digital Economy Unit, Joint Research Centre, European Commission.
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Nicole Dewandre, Joint Research Centre, European Commission.
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Dr. Fabien Giraldin (PhD), BBVA Data & Analytics.
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Dr. Emilia Gómez, Joint Research Centre, European Commission and Universitat Pompeu Fabra.
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Prof. Dr. Miguel Ángel González-Ballester, Simulation, Imaging and Modelling for Biomedical Systems, ICREA and Universitat Pompeu Fabra.
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Dr. Fabien Gouyon, Principal researcher, Pandora.
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Dr. José Hernández-Orallo, Universidad Politécnica de Valencia-Leverhulme Centre for the Future of Intelligence, University of Cambridge.
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Perfecto Herrera, Music Technology Group-Universitat Pompeu Fabra / Escola Superior de Música de Catalunya, Barcelona, Spain.
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Maria Iglesias, Legal Officer, Intellectual Property and Technology Transfer, Joint Research Centre, European Commission.
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Dr. Lorena Jaume-Palasi, co-founder and executive director of AlgorithmWatch (Germany).
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Dr. Anders Jonsson, Artificial Intelligence and Machine Learning group, Universitat Pompeu Fabra.
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Dr. Sergi Jordà, Music Technology Group, Universitat Pompeu Fabra.
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Dr. Ansgar Koene, University of Nottingham.
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Dr. Martha Larson, Radboud University and TU Delft.
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Prof. Ramón López de Mantaras, Director of the IIIA (Artificial Intelligence Research Institute) of the CSIC (Spanish National Research Council), Barcelona, Spain.
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Dr. Bertin Martens, Senior Scientist, Digital Economy Unit.
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Ever Meijer, Geodan.
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Dr. Marius Miron, Centre for Advanced Studies, Joint Research Centre, European Commission.
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Dr. Rubén Moreno-Bote, Centre for Brain and Cognition, DTIC, Universitat Pompeu Fabra.
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Dr. Pablo Noriega, Artificial Intelligence Institute, Spanish Council for Scientific Research (CSIC).
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Dr. Nuria Oliver, Vodafone Research and Data-Pop Alliance.
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Antonio Puertas Gallardo, Knowledge for Health and Consumer Safety Unit, Joint Research Centre, European Commission.
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Jordi Pons, Universitat Pompeu Fabra.
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Aurelio Ruiz, Universitat Pompeu Fabra.
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Prof. Dr. Heike Schweitzer, Free University of Berlin, Germany.
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Prof. Dr. Nuria Sebastian-Galles, Speech Acquisition and Perception Group, Centre for Brain and Cognition, Universitat Pompeu Fabra.
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Dr. Joan Serrà, Telefònica Research, Barcelona, Spain.
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Prof. Dr. Xavier Serra, Music Technology Group-Maria de Maeztu Strategic Program on Data-Driven Knowledge Extraction, Department of Information and Communication Technologies, Universitat Pompeu Fabra.
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Prof. Dr. Luc Steels, ICREA and Universitat Pompeu Fabra.
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Dr. Jutta Thielen del Pozo, Head of Scientific Development Unit and Director of the Centre for Advanced Studies, Joint Research Centre, European Commission.
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Dr. Songul Tolan, Centre for Advanced Studies, Joint Research Centre, European Commission.
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Dr. Karina Vold, Leverhulme Centre for the Future of Intelligence, University of Cambridge.
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Prof. Henk Scholten, University of Amsterdam, Co-Lead Scientist of Digital Transformation-Governance Project.
List of figures
Figure 1. Benefit for protected and unprotected groups.............................................24
Figure 2. COMPAS scores distribution......................................................................25
Figure 3. Ranking comparison for different genres. ...................................................26
Figure 4. Machine Learning (ML) Pipeline. Evaluation of AI with respect to requirements
and opportunities for regulation can be identified at every stage of the pipeline. ..........35
Figure 5. Uncanny Valley effect. .............................................................................57
Figure 6. Summary of requirements for positive data-driven disruption.......................62
Figure 7. Areas of interest for Quantum Computing ..................................................66
Figure 8. Computing science domains .....................................................................67
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