Content Aware and Other Case Studies: Museum of Synthetic History

With the rise of artificial intelligence and related computational tools in everyday dealings with knowledge organisation, production, and distribution, incl. for example archives and history-related applications, we’re concerned whether these computational methods 'colonize' and fundamentally change our common approaches to what constitutes studying and knowing a subject matter. We will unpack upon these concerns, looking at phenomena such as a lack of completion and categorisation in biodiversity archives, or new methods of creating artificial fossils as ways of filling gaps within historical datasets and potentially narratives. We also call back into how ontological architectures of computer science have emerged and how they defined ways in which knowledge is accessed. Via the examples of various case studies and thought experiments, the paper tries to examine the initial concern and predict its potential consequences, building upon the question as to what degree machine-learning-based approaches can augment our methods of analysis not just in history but in cultural behaviours.

In other words, how might computational models of ontology be producing an epistemological shift within the quality of knowing by imposing a knowledge system of references, linked nodes, hashtags, and databases that are never entirely complete in representing subjects they are set to define. Thus, asking if we shall hold on to our approaches of comprehension of things and their emergence or instead succumb to the generative, on-demand, a click away, always-at-your-fingertips forms of knowing and comprehending?

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Author and article information

Contributors

Egor Kraft

Ekaterina Kormilitsyna

Conference

Publication date: September 2021

Publication date (Print): September 2021

Pages: 303-308

Affiliations

[0001]Academy of Fine Arts Vienna

Vienna, Austria

Article

DOI: 10.14236/ewic/POM2021.40

SO-VID: 7c2fa4a0-20a0-4075-aad0-0ca239e37a21

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This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

Conference name: Proceedings of Polititcs of the machines - Rogue Research 2021

Conference acronym: POM 2021

Conference number: 3

Conference location: Berlin, Germany

Conference date: September 14-17, 2021

Conference sponsor: Electronic Workshops in Computing (eWiC)

Conference theme: debate and devise concepts and practices that seek to critically question and unravel novel modes of science

History

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1477-9358 BCS Learning & Development

Self URI (article page): https://www.scienceopen.com/hosted-document?doi=10.14236/ewic/POM2021.40

Self URI (journal page): https://ewic.bcs.org/

REFERENCES

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[2] W Benjamin (1935; 2003). The work of art in the age of mechanical reproduction. London: Penguin Books.

[3] S Earley (2020). The Role of Ontology and Information Architecture in AI. [online] Earley Information Science. Available at: http://www.earley.com/insights/role-ontology-and-information-architecture-ai (Accessed 13 Sep. 2021).

[4] Field Museum (2018). Press Release: Easy-Bake Fossils. [online] Field Museum. Available at: http://www.fieldmuseum.org/about/press/easy-bake-fossils (Accessed 7 Sep. 2021).

[5] S Goled (2021). Ontology In AI: A Common Vocabulary To Accelerate Information Sharing [online] Analytics India Magazine. Available at: http://analyticsindiamag.com/ontology-in-ai-a-common-vocabulary-to-accelerate-information-sharing/ (Accessed 3 Sep. 2021).

[6] T.R Gruber (1993). A translation approach to portable ontology specifications. Knowledge Acquisition, 5(2), pp.199–220

[7] T.R Gruber (1995). Toward principles for the design of ontologies used for knowledge sharing? International Journal of Human-Computer Studies, 43(5-6), pp.907–928

[8] L Krishtalka and P.S Humphrey (2000). Can Natural History Museums Capture the Future? BioScience, 50(7), p.611.

[9] E.T Saitta, T.G Kaye and J Vinther (2018). Sediment-encased maturation: a novel method for simulating diagenesis in organic fossil preservation. Palaeontology, 62(1), pp.135–150

[10] Í Sampaio, M Carreiro-Silva, A Freiwald, G Menezes and M Grasshoff (2019). Natural history collections as a basis for sound biodiversity assessments: Plexauridae (Octocorallia, Holaxonia) of the Naturalis CANCAP and Tyro Mauritania II expeditions. ZooKeys, 870, pp.1–32

[11] M Starr (2018). Researchers Have Discovered How to Make Proper Fossils - In a Day. [online] ScienceAlert. Available at: http://www.sciencealert.com/fake-fossil-method-baked-in-a-day-artificial-maturation-sediment (Accessed 11 Aug. 2021).

[12] D Stout (2016). Tales of a Stone Age Neuroscientist. Scientific American, 314(4), pp.28–35 DOI: 10.1038/scientificamerican0416-28

[13] S Thielman (2016). Donald Trump is technology’s befuddled (but dangerous) grandfather. [online] The Guardian Available at: http://www.theguardian.com/technology/2016/dec/30/donald-trump-technology-computers-cyber-hacks-surveillance

[14] J Troudet, Vignes-R Lebbe, P Grandcolas and F Legendre (2018). The Increasing Disconnection of Primary Biodiversity Data from Specimens: How Does It Happen and How to Handle It? Systematic Biology, 67(6), pp.1110–1119

[15] E.O Wilson (2003). The encyclopedia of life. Trends in Ecology & Evolution, 18(2), pp.77–80

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