Ethical Responsibility vs. Ethical Responsiveness in Conscious and Unconscious Communication Agents
In this contribution, I start from Levy’s precious suggestion about the neuroethics of distinguishing between “the slow-conscious <i>responsibility</i>” of us as persons, versus “the fast-unconscious <i>responsiveness</i>” of sub-personal brain mechanisms studied in cognitive...
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doaj-58d49a38194944d084a7eb526724883f2020-11-25T02:10:01ZengMDPI AGProceedings2504-39002020-05-0147686810.3390/proceedings47010068Ethical Responsibility vs. Ethical Responsiveness in Conscious and Unconscious Communication AgentsGianfranco Basti0Faculty of Philosophy, Pontifical Lateran University, 00120 Vatican City, ItalyIn this contribution, I start from Levy’s precious suggestion about the neuroethics of distinguishing between “the slow-conscious <i>responsibility</i>” of us as persons, versus “the fast-unconscious <i>responsiveness</i>” of sub-personal brain mechanisms studied in cognitive neurosciences. However, they are both <i>accountable</i> for how they respond to the environmental (physical, social, and ethical) constraints. I propose to extend Levy’s suggestion to the fundamental distinction between “moral responsibility of conscious communication agents” versus the “ethical responsiveness of unconscious communication agents”, like our brains but also like the AI decisional supports. Both, indeed, can be included in the category of the “sub-personal modules” of our moral agency as persons. I show the relevance of this distinction, also from the logical and computational standpoints, both in neurosciences and computer sciences for the actual debate about an ethically accountable AI. Machine learning algorithms, indeed, when applied to automated supports for decision making processes in several social, political, and economic spheres are not at all “value-free” or “amoral”. They must satisfy an ethical responsiveness to avoid what has been defined as the unintended, but real, “algorithmic injustice”.https://www.mdpi.com/2504-3900/47/1/68neuroethicsdigital ethicsquantum field theory |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Gianfranco Basti |
spellingShingle |
Gianfranco Basti Ethical Responsibility vs. Ethical Responsiveness in Conscious and Unconscious Communication Agents Proceedings neuroethics digital ethics quantum field theory |
author_facet |
Gianfranco Basti |
author_sort |
Gianfranco Basti |
title |
Ethical Responsibility vs. Ethical Responsiveness in Conscious and Unconscious Communication Agents |
title_short |
Ethical Responsibility vs. Ethical Responsiveness in Conscious and Unconscious Communication Agents |
title_full |
Ethical Responsibility vs. Ethical Responsiveness in Conscious and Unconscious Communication Agents |
title_fullStr |
Ethical Responsibility vs. Ethical Responsiveness in Conscious and Unconscious Communication Agents |
title_full_unstemmed |
Ethical Responsibility vs. Ethical Responsiveness in Conscious and Unconscious Communication Agents |
title_sort |
ethical responsibility vs. ethical responsiveness in conscious and unconscious communication agents |
publisher |
MDPI AG |
series |
Proceedings |
issn |
2504-3900 |
publishDate |
2020-05-01 |
description |
In this contribution, I start from Levy’s precious suggestion about the neuroethics of distinguishing between “the slow-conscious <i>responsibility</i>” of us as persons, versus “the fast-unconscious <i>responsiveness</i>” of sub-personal brain mechanisms studied in cognitive neurosciences. However, they are both <i>accountable</i> for how they respond to the environmental (physical, social, and ethical) constraints. I propose to extend Levy’s suggestion to the fundamental distinction between “moral responsibility of conscious communication agents” versus the “ethical responsiveness of unconscious communication agents”, like our brains but also like the AI decisional supports. Both, indeed, can be included in the category of the “sub-personal modules” of our moral agency as persons. I show the relevance of this distinction, also from the logical and computational standpoints, both in neurosciences and computer sciences for the actual debate about an ethically accountable AI. Machine learning algorithms, indeed, when applied to automated supports for decision making processes in several social, political, and economic spheres are not at all “value-free” or “amoral”. They must satisfy an ethical responsiveness to avoid what has been defined as the unintended, but real, “algorithmic injustice”. |
topic |
neuroethics digital ethics quantum field theory |
url |
https://www.mdpi.com/2504-3900/47/1/68 |
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