Abstract
The aim of the article is reflecting on a fundamental epistemological issue which characterises our present technological progress: where are we heading to, as humankind, while we are progressively externalising our most crucial decision processes towards algorithms, from which decisive data, coming from human experience and mind (including the very experience of human abilities), are left out? By reflecting on some cases, I shall try to argue that the most puzzling issue which engineers and philosophers should be aware that they have to jointly challenge may be that what we are actually doing through algorithmic automatisation is developing a novel human condition, according to which: (1) we are progressively thinking that algorithmic abstraction is always better than mental abstraction, because, at least in the Western culture, we come from a history of a progressive restriction of the best use of our minds to the realm of rationality, first, then to the realm of computation, second, and then to the realm of algorithmic automatisation, third, which finally exceeds our minds and (2) in doing so, we are progressively externalising not only human contents, but also human abilities, i.e., we are progressively atrophying ourselves, by becoming creatures who are progressively delegating the core of their very essence, which has always included the epistemological ability, together with the ethical courage, of making complex decisions on both our lives and the others’ lives.
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Notes
I am very grateful to an anonymous reviewer for her/his precious comments which surely helped me improve this article.
In the following pages, I shall use the expression “epistemological externalisation” precisely in the sense of shifting our decision processes from the internal processes of our minds to the external algorithms of machines. On the contrary, an “epistemological internalisation” would make reference to the former condition, according to which we found our decision-making on internal processes (from pastry making to other complex decision processes I shall discuss in what follows). Thus, I am not making reference to epistemological externalism and internalism.
I am very grateful to an anonymous reviewer for this brilliant suggestion. The necessarily limited length of this article does not allow me to deepen this possible scenario, but I shall do it elsewhere in the future.
References
Arthur WB (2009) The nature of technology: what it is and how it evolves. Free Press, New York
Bostrom N (2014) Superintelligence: paths, dangers, strategies. Oxford University Press, Oxford
Brende E (2005) Better off: flipping the switch on technology. Harper Perennial, New York
Clark A (2003) Natural-born cyborgs: minds, technologies and the future of human intelligence. Oxford University Press, Oxford
Domingos P (2015) The master algorithm: how the quest for the ultimate learning machine will remake our world. Allen Lane, London
Dyson GB (1997) Darwing among the machines: the evolution of global intelligence. Penguin, London
Eco U (1968) La struttura assente: introduzione alla ricerca semiologica. Bompiani, Milano
Finn E (2017) What algorithms want: imagination in the age of computing. MIT Press, Cambridge
Franssen M, Lokhorst G-J, van de Poel I (2009) Philosophy of technology. Stanford Encyclopaedia of Philosophy, USA. https://plato.stanford.edu/entries/technology/(first published in 2009, substantive revision in 2018)
Garreau J (2006) Radical evolution: The promise and peril of enhancing our minds, our bodies, and what it means to be human. Broadway Books, New York
Golumbia D (2009) The cultural logic of computation. Harvard University Press, Cambridge
Harari YN (2016) Homo deus: a brief history of tomorrow. Harvill Secker, London
Harari YN (2018) 21 Lessons for the 21st century. Jonathan Cape, London
Kelly K (2010) What technology wants. Penguin, New York
Kurzweil R (2005) The singularity is near: when humans transcend biology. Penguin, New York
Noble SU (2018) Algorithms of oppression: how search engines reinforce racism. New York University Press, New York
O’Neil C (2016) Weapons of math destruction: how big data increases inequality and threatens democracy. Crown, New York
Rees M (2018) On the future: prospects for humanity. Princeton University Press, Princeton
Ross A (2016) The industries of the future. Simon and Schuster, New York
Vaidhyanathan S (2011) The googlization of everything (and why we should worry). University of California Press, Berkeley-Los Angeles
Weber M (2013) Economy and society: An outline of interpretive sociology. In: Roth G, Wittiche C (eds). University of California Press, Berkeley-Los Angeles
Zellini P (2018) La dittatura del calcolo. Adelphi, Milano
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Chiodo, S. The greatest epistemological externalisation: reflecting on the puzzling direction we are heading to through algorithmic automatisation. AI & Soc 35, 431–440 (2020). https://doi.org/10.1007/s00146-019-00905-y
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DOI: https://doi.org/10.1007/s00146-019-00905-y