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Record W2887841565

Non-Human Gaming: Video Games in the Post-Anthropocene

2018· article· en· W2887841565 on OpenAlexaboutno aff
Paolo Ruffino

Bibliographic record

VenueLincoln Repository (University of Lincoln) · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsnot available
Fundersnot available
KeywordsAnthropoceneComputer scienceVideo gameAstrobiologyMultimediaHuman–computer interactionRemote sensingEnvironmental scienceGeologyPaleontologyBiology
DOInot available

Abstract

fetched live from OpenAlex

In this presentation, I will address the possibility of an imminent mass extinction of all living beings from planet Earth, and the implications of such a catastrophic event for games studies. 
\nThe Anthropocene, a term popularized by the end of the 20th century to refer to the geological impact of human beings on planet Earth, assumes a temporal development, a ‘before’ and ‘after’ the appearance of humankind. The ‘after’ period, known as the Post-Anthropocene, is repeatedly claimed by scientists to be approaching within the next few decades, as over-consumption is destroying vital resources of the planet. Allegedly, the sixth mass extinction in the history of our planet is already unfolding, and might determine the disappearance of life from Earth and, as far as we know, from the Universe and beyond (Zylinska 2014; Wark 2015; Haraway 2016; Thacker 2010).
\nVideo games have been responding to the arrival of the Post-Anthropocene. In recent years, an increasing number of games appear to capture the fascination and creepiness of a world with no humans. This impending future is not just imagined in fictional settings (e.g. The Legenda of Zelda: Majora’s Mask, Nintendo, 2000; Horizon: Zero Dawn, Guerrilla Games, 2017), but within game design. In the last decade an increasing number of video games requiring limited human intervention has been released. Idle games such as Cookie Clicker (Julien Thiennot, 2013) and AdVenture Capitalist (Hyper Hippo Productions, 2014) require an initial input from the player to start, and then keep playing themselves in the background operations of a laptop or smartphone. Virtual environments can be entirely designed by algorithms, as experimented by Hello Games for No Man’s Sky (2016). Artificial Intelligence is also used to play games. Screeps, a massive-multiplayer online game, requires players to program an AI that will play the game in their place, and which will ‘live within the game even while you are offline’ (Screeps Team, 2014). Ghost cars in racing games replace the human actor with a representation of their performance. The same concept is further explored by the Drivatar of the Forza Motorsport series (Microsoft Studios, 2005-2017), which simulates the driving style of the player and competes online against other AI-controlled cars (Bittanti 2015). These are only some of the example that suggest that human beings are becoming peripheral in the act of playing games. The video installation Emissaries, at MoMA PS1, by Ian Cheng (2017), and Twitch streaming of computer-controlled avatars in Grand Theft Auto by Ben Watanabe (San Andreas Deer Cam, 2016; San Andreas Community Cam, 2017) are further investigations in how games could play themselves even after the disappearance of human beings.
\nDrawing on Sonia Fizek’s analysis of the concept of interpassivity in digital games (via the work of Robert Pfaller and Slavoj Zizek), and on studies on gamification and self-tracking, I argue that Non-Human Gaming is not necessarily an exception to oppose to ‘standard’ video games, or a (con)temporary trend (Fizek 2018; Ruffino 2016). The non-human has always been haunting the medium, and studies on interactivity, agency, and player’s skills and competences have been providing, so far, a comforting perspective that places the human at the center, or at an equal hierarchical importance than the machine (Giddings 2005; Björk and Juul 2012). Alexander Galloway imagined how machines could take the lead in the process of enacting a video game, creating ‘ambience acts’ where the game plays itself with no need for the human being to be present (Galloway 2006). Galloway was concerned with the allegories that computer games provide, and the ways in which games mimic the social reality in which we live in. Since 2006, fears of economic, political, social, and geological crises at global level have been prominent. Non-Human gaming can be interpreted as a response to those fears, and put in relation to the rise of self-driving cars, algorithmic trade exchange, and remote warfare, which similarly operate by replacing human beings. In fact, Non-Human Gaming is an adequate response to the disappearance of life from Earth – as it has been imagined, feared, and prophesized by scientists in recent years, and even more insistently since the time of Galloway’s contribution.
\nIn this talk I will attempt to map the broad category of Non-Human gaming. Roger Caillois, in his early work on mimicry and mythology, was already describing how living beings develop forms of dispersal and waste of energy that cannot be explained through a rationalistic view on evolution and preservation, and which bring the organism closer to its own disappearance and assimilation in the surrounding environment, but are nonetheless defining characteristics of life (Caillois 1934; 1935). My concern is to highlight the weirdness and creepiness, the irony and spoofs, the paradoxes and contradictions of video games made by no one and/or for no one. As Haraway’s vision of the cyborg did with cybernetics, Non-Human gaming confuses and complicates the ontologies of digital texts, and could be used to shed light on the situatedness, temporality, and partiality of our knowledge, of both humans and games (Haraway 1991; Kember 2018). Life might be disappearing from Earth at some point, but we are not there yet. We are in-between birth and death, the beginning and the end, and we have always been. Non-Human gaming helps us articulating this space and time in-between, and has the potential to re-route gaming (and game studies) from false myths of agency, interactivity, and instrumentalism (the ‘games for’ health, education, self-improvement, and so on). Non-human games are companions for earthly survival.
\n 
\nBIBLIOGRAPHY
\nBittanti, M. (2015) Orizzonti di Forza: Fenomenologia della Guida Videoludica, Edizioni Unicopli
\nBjörk, S. and Juul, J. (2012) ‘Zero-Player Games, or: What We Talk About When We Talk About Players’, presented at the Philosophy of Computer Games Conference, Madrid 2012
\nCaillois, R. (1934) [2014] ‘The Praying Mantis: from Biology to Psychoanalysis’, in The Edge of Surrealism: A Roger Caillois Reader, Durkham: Duke University Press
\nCaillois, R. (1935) [1984] ‘Mimicry and Legendary Psychastenia’, in October (31), Cambridge (MA): The MIT Press
\nFizek, S. (2018) ‘Interpassivity and the Joy of Delegated Play’. ToDiGRA Journal (to be published).
\nGalloway, A. (2006) Gaming: Essays on Algorithmic Culture. Minneapolis (MN): University of Minnesota Press.
\nGiddings, S. (2005) Playing with non-humans: digital games as technocultural form. In: Proceedings of DiGRA 2005 Conference: Changing Views - Worlds in Play, Vancouver, British Columbia, Canada, 16-20 June 2005.
\nHaraway, D. J. (1991) Simians, Cyborgs and Women. The Reinvention of Nature. London: Free Association Books.
\nHaraway, D. J. (2016) Staying with the Trouble: Making Kin in the Chthulucene, Duke University Press
\nKember, S. (2017) ‘After the Anthropocene: the photographic for earthly survival?’ in Digital Creativity, vol. 28, no. 4, pp. 348-353
\nRuffino, P. (2016) ‘Games to Live With: Speculations Regarding NikeFuel’ in Digital Culture and Society, vol. 2, no. 1, pp. 153-`159 
\nThacker, E. (2010) After Life, London and Chicago: Chicago University Press
\nWark, M. (2015) Molecular Red. Theory for the Anthropocence. London: Verso.
\nZylinska, J. (2014) Minimal Ethics for the Anthropocene. Michigan (MA): Open Humanities Press

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.671
Threshold uncertainty score0.823

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.271
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Published2018
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