Art in the Age of Machine Learning (2021, MIT Press)

Foreword by Yoshua Bengio.

An examination of machine learning art and its practice in new media art and music.

"Over the past decade, an artistic movement has emerged that draws on machine learning as both inspiration and medium. In this book, transdisciplinary artist-researcher Sofian Audry examines artistic practices at the intersection of machine learning and new media art, providing conceptual tools and historical perspectives for new media artists, musicians, composers, writers, curators, and theorists. Audry looks at works from a broad range of practices, including new media installation, robotic art, visual art, electronic music and sound, and electronic literature, connecting machine learning art to such earlier artistic practices as cybernetics art, artificial life art, and evolutionary art."

For more information and buying options

“Audry puts machine learning in historical context and provocatively argues for its unique artistic potential. This book is tremendously useful to scholars and artists alike as a source of theoretical footholds and methodological guidance.” (Allison Parrish, Assistant Arts Professor, NYU ITP/IMA)

“Sofian Audry powerfully demonstrates that artists' imagination, labor, and acute social-political awareness is alive and well in our age of machine learning.” (Chris Salter, Professor of Computation Arts, Concordia University, Montreal; author of Entangled)

“The capacity to learn, adapt, even innovate or 'create' has become a deep issue in machine learning art. Audry plumbs the theoretical and ethical dimensions of these matters in this deep dive into behavior, adaptivity, and metamorphosis in computational systems.” (Simon Penny, Professor, University of California, Irvine; author of Making Sense)


Armand, Edwige, Audry, Sofian, Garcia, Frédérick and Martinucci, TeZ Maurizio (2020). “Who is Speaking ? Artscience Stagings of Nonhuman Sentience”, ISEA 2020 Conference proceedings, Montréal, Canada.

Gee, Erin, Lee, Alex M. and Audry, Sofian (2020). “Playing with Emotions : Biosignal-based Control in Virtual Reality Game Project H.E.A.R.T.”, ISEA 2020 Conference proceedings, Montréal, Canada.

Audry, Sofian (2020). “La matérialité révélatrice de l’apprentissage automatique”, ESPACE art actuel, “IA - Art sans artistes”, No 124, Winter 2020.

Audry, Sofian (2019). “Behavior Morphologies of Machine Learning Agents in Media Artworks”, Leonardo, pp. 1-10, 2019.

Audry, Sofian and Ippolito, Jon (2019). “Can Artificial Intelligence Make Art without Artists ? Ask the Viewer”, Arts (MDPI).

Gee, Erin and Audry, Sofian (2019). “Automation as Echo”, ASAP/Journal.

Audry, Sofian (2019). “Unrolling the Learning Curve : Aesthetics of Adaptive Behaviors with Deep Recurrent Nets for Text Generation”, International Symposium on Computational Media Art 2019 Conference proceedings, Hong Kong, China.

Audry, Sofian (2018). “for the sleepers in that quiet earth. : Experiencing the Behavior of a Deep Learning Neural Network Agent through a Generative Artbook”, ISEA 2018 Conference proceedings, Durban, South Africa.

Salter, Chris and Audry, Sofian (2018). “Towards Probabilistic Worldmaking : Xenakis, n-Polytope and the Cybernetic Path to Chaos”, in Worldmaking as Techné : Exploring Worlds of Participatory Art, Architecture, and Music. de Campo, A., Hosale, M., Murrani, S. (Eds). Riverside Architectural Press, Toronto, Canada.

Audry, Sofian (2018). “Aesthetics of Adaptive Behaviors in Embodied Agents”, Body of Knowledge 2016 Conference proceedings, UCI, Irvine, USA.

Audry, Sofian and al. (2017). “256-Byte Creative Programs” (TROPE-17-02), The Trope Tank, MIT, Cambridge, USA.

Audry, Sofian (2016). “Aesthetics of Adaptive Behaviors in Agent-based Art”, ISEA 2016 Conference proceedings, Hong Kong, China.

2010 Audry, Sofian (2010). “Absences : Public Art Interventions in Natural Spaces using Autonomous Electronic Devices”, ISEA 2010 Conference proceedings, pp. 469–471. Ruhr, Germany.

2008 Bengio, Yoshua and Senécal, Jean-Sébastien (2008). “Adaptive Importance Sampling to Accelerate Training of a Neural Probabilistic Language Model” IEEE Transactions on Neural Networks, Vol. 19, No 4, pp. 713–722.

2006 Bengio, Y., Schwenk, H., Senécal, J. S., Morin, F. and Gauvain, J.-L. (2006). “Neural probabilistic language models”, Studies in Fuzziness and Soft Computing, Vol 194, p. 137-186, Berlin, Germany.

Bengio, Yoshua and Senécal, Jean-Sébastien (2003). “Quick Training of Probabilistic Neural Nets by Importance Sampling”. Ninth International Workshop on Artificial Intelligence and Statistics, Society for Artificial Intelligence and Statistics, Key West, USA.

Thesis and Dissertations

Senécal, Jean-Sébastien (2016). Machines That Learn : Aesthetics of Adaptive Behaviors in Agent-based Art. Thèse de doctorat, Concordia University, Montréal. 307 pages.

Senécal, Jean-Sébastien (2010). Une exploration des processus d’assignation identitaires à travers une expérience interactive. Mémoire de maîtrise, École des Médias, Université du Québec à Montréal, Montréal. 40 pages.

2003 Senécal, Jean-Sébastien (2003). Accélérer l’entraînement d’un modèle non-paramétrique de densité non normalisée par échantillonnage aléatoire. Mémoire de maîtrise, Département d’Informatique and de Recherche Opérationelle, Université de Montréal, Montréal. 91 pages.