[This text is the transcription of part of my lecture “Nature, Life, Data and Algorithms: Old and New Models to Shape the World” at the workshop “AI and Humanities”, organized at BOZAR – Centre for Fine Arts in Brussels by the Joint Research Center (JRC) SciArt Board of the European Commission on the cultural aspects of Big Data, Artificial Intelligence and Digital Transformation. In this reduced form and title it has been published in Freddy Paul Grunert (ed.), Max Craglia, Emilia Gómez, Jutta Thielen-del Pozo (co-eds.), HumaniTies and Artificial Intelligence, Ravenna, Noema, 2022, ISBN 978-88-943827-2-3, publication commissioned by the European Commission under Gold Open Access license and freely downloadable from the above link]
An algorithm is a sequence of unambiguous instructions for solving a problem, i.e., for obtaining a required output for any legitimate input in a finite amount of time. [1]
Although almost exclusively considered as related to calculation systems and computers, algorithms exist since antiquity, and have deeply influenced and shaped the human culture. Humanity and human activities have always been inspired by Nature and the living, that since the Palaeolithic have been represented. Today’s disciplines, tools and technologies have expanded the possibilities of simulation in many fields, from science to art. According to Louis Bec – the French zoosystematicien, a prominent figure in the field of the relationship among art, science, philosophy and technology – simulation opens up new perspectives, it makes possible new worlds.
Depuis l’avènement des sciences cognitives, de l’informatique, de l’intelligence artificielle, de la robotique et de l’interactivité, il est possible de simuler et de modéliser des comportements de plus en plus complexes tout en les effectuant. [2]
Simulation
Since prehistory, the living and Nature have been simulated in pictures, but also the artefacts have taken inspiration from them. Tools, devices and machines have to respond to mechanical and physical issues, in particular when they have to operate in the environment. In these tasks the living is the best model to simulate because it has been co-evolving with the environment for almost 4 billion years, adopting “solutions” that have allowed its survival: it is the best model because it has experience of the world.
Science often simulates events through computer models before observing them in the real world, and a rigorous computer model can be considered as a validation of a theory: in some respects it is a sort of a substitute of reality. In a different field, a photography can be a legal document that sets an identity and a responsibility, or can recall a memory. And through cinema we can create fantastic narratives. The movies with greatest revenues in the history of cinema are based on 3D computer simulations: without this technique lots of stories and worlds enjoyed from many people would simply have never existed.
Simulation has always been nodal, a significant part of our lives is based on simulation. There are three main ways to simulate, that can also be combined to each other:
a) Diegetic simulation, that is representing an existing or invented reality through storytelling, narration, like in orality and writing, directly or through the media, etc.
b) Representative or formal simulation, that is representing the appearance of an existing or invented reality, like in painting, sculpture, photography, cinema, video, 3D computer image and animation, video games, virtual reality, holograms, OS interfaces, software tools, etc.
c) Behavioural simulation, that is representing the behaviour of an existing or invented reality, like in Robotics, Artificial Intelligence, Artificial Life, etc.
Here I will consider points b) and c).
Representative or formal simulation
One of the most successful algorithms in simulating an existing or invented reality through the images is the Renaissance perspective, described by Leon Battista Alberti in his treatise De Pictura (1435-36). It is basically a series of geometric and mathematical tools that transduce or figure a three-dimensional physical space onto a substantially two-dimensional support: a cultural construct that unifies the ancient scattered, discontinuous and multiple space of the representation. In order to achieve this goal the Renaissance perspective is based on the “point of view”, decided by the artist, from which observing the image: moving away from this point implies loosing information. Therefore, the Renaissance perspective does not only regulate the “virtual” space of the representation onto and beyond the surface of the image, but it also rules the external physical space of the observer, who, in order to have the most illusory and informational effect, must view the image from a precise standing point decided by the artist.
Therefore, the Renaissance perspective presents as objective visual representations that are based on the point of view, that is on the most subjective and personal element [3]. This algorithm has deeply influenced and shaped the human culture, since, at least in the Western world, after almost six centuries we still live in a perspective-based era: every time that we have to simulate a real or a realistic space with photography, cinema, video, 3D computer techniques, 3D video games, Virtual Reality…, we use the rules of the Renaissance perspective. Without this algorithm any visual simulation of a real or imaginary space sounds as wrong, unreal or unrealistic. With two main exceptions: children, who have not yet subsumed that cultural model. And artists, who often like to overcome the rules.
A recent way to visually simulate/invent reality are Generative Adversarial Networks (GANs), a class of A.I. algorithms used in unsupervised machine learning [4]. With GANs it is possible to get at the same time a wide variation in the outcome and an impressive photorealism, with pictures that look like photographs but are not referential, that is taken from real physical subjects.
Behavioural simulation. First Life, Second Life and Third Life
The concept of “simulation” also recurs in disciplines like Artificial Intelligence, Artificial Life and Robotics, which mainly simulate the behaviour of the living, and often also its appearance. In particular:
Artificial Intelligence:
[…] every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it. [5]
Artificial Life:
[…] is a new discipline that studies “natural” life by attempting to recreate biological phenomena from scratch within computers and other “artificial” media. AL complements the traditional analytic approach of traditional biology with a synthetic approach in which, rather than studying biological phenomena by taking apart living organisms to see how they work, one attempts to put together systems that behave like living organisms. [6]
Humanity has always been imagining, representing and creating life forms, the thrust for creating life-like entities has been pervading the whole human history. In the symbolic realm from antiquity until the contemporary narratives gods and heroes are present in religions and mythologies, legendary creatures populate the imaginary of all human cultures, through stories, representations, sagas, fictional worlds and legends. Unicorns, dragons, centaurs, chimeras, angels and devils, cyclopes, minotaurs, magicians, sirens, ogres, fairies, witches, elves, goblins, harpies, trolls…, and also monsters, heroes and common people, populate movies, comics, TV series and video games. The symbolic realm is a wonderful “Second Life”, a territory of pulsing imaginary life forms.
In parallel, in the physical world, at least since the Neolithic, humanity has been creating new organic life forms by selecting and hybridising animal and vegetal species, giving birth to varieties that would have never evolved outside the human culture. In the organic realm the ability to operate with the matter of the living through bio-based sciences and technologies has lead to the creation of deeply modified and even totally new organisms. In the inorganic realm humanity has made increasingly powerful and autonomous artefacts, devices and machines that present behaviours similar to the living. Today Robotics, Artificial Intelligence, Artificial Life, Synthetic Biology, Genetic Engineering, Biotechnology, De-Extinction are expanding the boundaries of life and evolution. We are witnessing the extension of life to a complex scenery with organic, inorganic and mixed living forms. A “Third Life” originating from the human culture that expands Nature from within its own domain. “Third Life” being the “First Life” the biological life and the “Second Life” the life in the symbolic dimension [7].
This process is consistent with the progressive externalisation outside the body of human functions and activities. In the beginning, starting from our ancestors, replacing or enhancing body parts and abilities with tools and devices. Then, recording knowledge and memory outside the body with picture and writing. Then, externalising activities and labour with machines and more or less automatic devices. Then, outsourcing narrow reasoning and autonomous action with Artificial Intelligence, Robotics, Artificial Life and algorithms, as well as organic life with Synthetic Biology, Genetic Engineering and Biotechnology. If this trend goes on in the future, more and more human functions and activities will be externalised, and the creations of the human culture will become increasingly independent, evolving, as noted above, into Third Life. Transdisciplinarity, complexity, awareness and a vision of the future are the basis for imagining, participating and designing in such an evolution.
Notes
1) Anany Leviting, Introduction to the design & analysis of algorithms, New Jersey, Pearson, 2003. [back]
2) Louis Bec, “Les Gestes Prolongés. Postface”, Flusser Studies (3/02/2009), online, https://bit.ly/2TI2jxI (last access: 23/07/21). [back]
3) Omar Calabrese, La macchina della pittura, Bari, Laterza, 1985. [back]
4) Ian J. Goodfellow, et al., “Generative Adversarial Networks”, arXiv, 1406.2661, 10 June 2014, online, https://arxiv.org/abs/1406.2661 (last access: 02/08/21). [back]
5) John McCarthy, et al., “A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence,” Dartmouth Summer Research Conference on Artificial Intelligence (1955), https://stanford.io/3rD9O5n (last access: 20/07/21). The italics are mine. [back]
6) Christopher G. Langton, “Preface,” in C.G. Langton, C. Taylor, J.D. Farmer, S. Rasmussen (eds.), Artificial Life II, Redwood City, Addison-Wesley, 1992. The italics are mine. [back]
7) On the concept of “Third Life” among my texts see: “From life to life. The multiplicity of the living”, in R. Ascott, G. Bast, W. Fiel, M. Jahrmann, R. Schnell (eds.), New Realities: Being Syncretic, Wien, Springer-Verlag, 2009; “Declinations of the living: Toward the Third Life”, in Dmitry Bulatov (ed.), Evolution Haute Couture. Art and Science in the Post-Biological Age, Kaliningrad, BB NCCA, 2013; “Arte come filosofia della contemporaneità. Poetiche della complessità, Terza Vita, località e universalità”, in Pier Luigi Capucci, Simonetta Simoni (eds.), Arte e complessità, Ravenna, Noema Media, 2018; “L’art au-delà de l’umanisme”, in Hervé Fischer (ed.), “Art versus Société: l’art doit changer le monde”, M@GM@, vol.18, n. 3 2020, 8 April 2021, online, http://www.analisiqualitativa.com/magma/1803/index.fr.htm (last access: 01/08/21). [back]
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