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Machine hermeneutics, postphenomenology, and facial recognition technology

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Abstract

I would like to introduce the notion of machine hermeneutics in this paper. The notion refers to hermeneutical activity performed by machines. Machines are now capable of making the very interpretive tasks, using artificial intelligence algorithms based on the technology of machine learning that used to be the exclusive domain of human beings. In making this claim, I am not talking about possible conscious machines of the future, but those existing here and now. With facial recognition algorithms, for example, machines are now performing routinely what must be regarded as hermeneutical analyses with astounding accuracy and power. Thus, machine hermeneutics supplements Don Ihde’s notion of material hermeneutics. In the latter, it is still human beings who do the interpretation, through the lenses provided the natural sciences; in this case, the natural sciences, or the technology afforded by the sciences, intervene between the human being and the world. In machine hermeneutics, on the contrary, the intervening comes in two layers. On the one hand, there is the usual intervention that Ihde talks about, but on the other, the artificial intelligence algorithm performs its own kind of intervention and interpretation, presenting an already interpreted result to the human beings, who then perceive it through the aid of the usual intervention such as the normal eyeglasses. Then the paper discusses the problem of how to justify the kind of perception that undergoes this process. In what sense can it be said that the algorithm is performing the right action, i.e., one such that the process comes up with a right picture of the world? I contend that this does not merely consist of technical excellence for the technology involved, but also ethical excellence. The two cannot be considered one apart from the other.

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Acknowledgements

I would like to thank Arun Kumar Tripathi for his tireless effort in communicating with me during these past many months, giving me a lot of advice, papers to read, and many other things. Research for this article was partially supported by a grant from the Project on “Creating an Environment for Open Science,” Chulalongkorn University, 3rd year.

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Correspondence to Soraj Hongladarom.

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Hongladarom, S. Machine hermeneutics, postphenomenology, and facial recognition technology. AI & Soc 38, 2151–2158 (2023). https://doi.org/10.1007/s00146-020-00951-x

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  • DOI: https://doi.org/10.1007/s00146-020-00951-x

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