Neural Networks, Pattern Recognition and Emotional Data

k 2025

Neural Networks, Pattern Recognition and Emotional Data

FORNACCIARI, Ilaria

Základní údaje

Originální název

Neural Networks, Pattern Recognition and Emotional Data

Autoři

FORNACCIARI, Ilaria

Vydání

Neurons and Machines: Philosophy, Ethics, Policies, and the Law. Politics of Technologies in the Digital Age III. Philosophical and Interdisciplinary Perspectives, 2025

Další údaje

Typ výsledku

Prezentace na konferencích

Stát vydavatele

Řecko

Utajení

není předmětem státního či obchodního tajemství

Odkazy

Conference website

Označené pro přenos do RIV

Klíčová slova česky

AI act; emotion AI; emotional data; critical AI; machine vision; pattern recognition

Štítky

emotion AI

Příznaky

Mezinárodní význam

Změněno: 3. 12. 2025 16:05, Ilaria Fornacciari, PhD.

Anotace

V originále

In light of the European Act (2024/1689), commonly known as the AI Act, the legal definition of ‘artificial intelligence systems for emotion recognition’ and ‘emotional data’ has taken on considerable relevancy. Since February of this year, the decree prohibits the use of emotion AI and sentiment analysis in certain contexts, namely workplaces and educational institutions. The retail and marketing sectors, on the other hand, do not seem to have been affected. Underpinning these technologies subject is the field or movement of “affective computing” (Picard, 1995; Picard, 1997). In my contribution, I would like to propose a genealogical analysis of the production of emotional data, starting from the history of the invention of artificial neural systems. I seek to examine, in particular, the link between the epistemology of “pattern recognition” and modern psychological models of optical vision. The relation between optical models of vision (particularly animal vision) and the automation of perception is well established in the genealogies of cybernetics and connectionist AI (Hayles, 1999; Pasquinelli, 2023). Distinct importance is attached, in this regard, to the publication of the 1959 Jerome Lettvin’s paper on frog’s vision (Lettvin, Maturana, McCulloch, & Pitts). It has been shown that neural networks have more to do with models of visual perception organs than with models of the brain (Virilio, 1994). Very little attention, however, seems to be accorded, until now, on the role of affects and emotion in the physio-psychological models of visual perception. What is the relationship between the automation of emotion inference as pattern recognition and the physio-psychology of vision? How and why is the problem automation of vision (computer vision, image processing, motion segmentation and synthesis) that gave rise to the affective computing movement? Reintroducing the issue of emotion recognition and inference into the question of pattern recognition automation, from which it derives, will allows to reframe the debate on the utilization of basic emotions theories by affective computing and the risks associated with them. In fact, it will not be so much the debate between intentionality and non-intentionality of emotions that will be compelling, but rather the intertwining of psychotechnics and probabilistic universality called upon to technically create distinctions.

Návaznosti

GX23-05692X, projekt VaV

Název: Roboti, programování člověka a autismus/Kulturní imaginace autismu a emoční umělé inteligence

Investor: Grantová agentura ČR, Roboti, programování člověka a autismus/Kulturní imaginace autismu a emoční umělé inteligence

Citovat

FORNACCIARI, Ilaria. Neural Networks, Pattern Recognition and Emotional Data. In Neurons and Machines: Philosophy, Ethics, Policies, and the Law. Politics of Technologies in the Digital Age III. Philosophical and Interdisciplinary Perspectives. 2025.

@proceedings{2537658,
   author = {Fornacciari, Ilaria},
   booktitle = {Neurons and Machines: Philosophy, Ethics, Policies, and the Law. Politics of Technologies in the Digital Age III. Philosophical and Interdisciplinary Perspectives},
   title = {Neural Networks, Pattern Recognition and Emotional Data},
   url = {https://politech.philosophy.uoi.gr/},
   year = {2025}
}

TY  - CONF
ID  - 2537658
AU  - Fornacciari, Ilaria
PY  - 2025
TI  - Neural Networks, Pattern Recognition and Emotional Data
UR  - https://politech.philosophy.uoi.gr/
N2  - In light of the European Act (2024/1689), commonly known as the AI Act, the legal definition of ‘artificial intelligence systems for emotion recognition’ and ‘emotional data’ has taken on considerable relevancy. Since February of this year, the decree prohibits the use of emotion AI and sentiment analysis in certain contexts, namely workplaces and educational institutions. The retail and marketing sectors, on the other hand, do not seem to have been affected. Underpinning these technologies subject is the field or movement of “affective computing” (Picard, 1995; Picard, 1997). In my contribution, I would like to propose a genealogical analysis of the production of emotional data, starting from the history of the invention of artificial neural systems. I seek to examine, in particular, the link between the epistemology of “pattern recognition” and modern psychological models of optical vision. The relation between optical models of vision (particularly animal vision) and the automation of perception is well established in the genealogies of cybernetics and connectionist AI (Hayles, 1999; Pasquinelli, 2023). Distinct importance is attached, in this regard, to the publication of the 1959 Jerome Lettvin’s paper on frog’s vision (Lettvin, Maturana, McCulloch, & Pitts). It has been shown that neural networks have more to do with models of visual perception organs than with models of the brain (Virilio, 1994). Very little attention, however, seems to be accorded, until now, on the role of affects and emotion in the physio-psychological models of visual perception. What is the relationship between the automation of emotion inference as pattern recognition and the physio-psychology of vision? How and why is the problem automation of vision (computer vision, image processing, motion segmentation and synthesis) that gave rise to the affective computing movement? Reintroducing the issue of emotion recognition and inference into the question of pattern recognition automation, from which it derives, will allows to reframe the debate on the utilization of basic emotions theories by affective computing and the risks associated with them. In fact, it will not be so much the debate between intentionality and non-intentionality of emotions that will be compelling, but rather the intertwining of psychotechnics and probabilistic universality called upon to technically create distinctions.
ER  -

FORNACCIARI, Ilaria. Neural Networks, Pattern Recognition and Emotional Data. In \textit{Neurons and Machines: Philosophy, Ethics, Policies, and the Law. Politics of Technologies in the Digital Age III. Philosophical and Interdisciplinary Perspectives}. 2025.

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