PreprintArticleVersion 1Preserved in Portico This version is not peer-reviewed
Phenotyping Genetic Diseases Through Artificial Intelligence Use of Large Datasets of Government-stored Facial Photographs: Concept, Legal Issues, and Challenges in the European Union
Version 1
: Received: 13 April 2023 / Approved: 14 April 2023 / Online: 14 April 2023 (03:56:59 CEST)
How to cite:
Kováč, P.; Alexandra, B.; Ivan, V.; Lukáš, M.; Michal, A.; Martin, S.; Thurzo, A. Phenotyping Genetic Diseases Through Artificial Intelligence Use of Large Datasets of Government-stored Facial Photographs: Concept, Legal Issues, and Challenges in the European Union. Preprints2023, 2023040344. https://doi.org/10.20944/preprints202304.0344.v1
Kováč, P.; Alexandra, B.; Ivan, V.; Lukáš, M.; Michal, A.; Martin, S.; Thurzo, A. Phenotyping Genetic Diseases Through Artificial Intelligence Use of Large Datasets of Government-stored Facial Photographs: Concept, Legal Issues, and Challenges in the European Union. Preprints 2023, 2023040344. https://doi.org/10.20944/preprints202304.0344.v1
Kováč, P.; Alexandra, B.; Ivan, V.; Lukáš, M.; Michal, A.; Martin, S.; Thurzo, A. Phenotyping Genetic Diseases Through Artificial Intelligence Use of Large Datasets of Government-stored Facial Photographs: Concept, Legal Issues, and Challenges in the European Union. Preprints2023, 2023040344. https://doi.org/10.20944/preprints202304.0344.v1
APA Style
Kováč, P., Alexandra, B., Ivan, V., Lukáš, M., Michal, A., Martin, S., & Thurzo, A. (2023). Phenotyping Genetic Diseases Through Artificial Intelligence Use of Large Datasets of Government-stored Facial Photographs: Concept, Legal Issues, and Challenges in the European Union. Preprints. https://doi.org/10.20944/preprints202304.0344.v1
Chicago/Turabian Style
Kováč, P., Smatana Martin and Andrej Thurzo. 2023 "Phenotyping Genetic Diseases Through Artificial Intelligence Use of Large Datasets of Government-stored Facial Photographs: Concept, Legal Issues, and Challenges in the European Union" Preprints. https://doi.org/10.20944/preprints202304.0344.v1
Abstract
One in 12 babies is born with a rare genetic disease. Sadly, most cases are undetected until later age, missing time for early treatment and opportunity to prevent complications. Humanity has entered a new era where Big Data collected by governments, including 2D and 3D facial scans, are available. Many rare genetic diseases can be identified by artificial intelligence (AI) analysis of the facial photo. Phenotyping AI utilizations facilitate comprehensive and accurate genetic evaluations. AI processing of this Big Data to identify rare genetic diseases could bring unimaginable benefits to healthcare, although this would be a questionable step in terms of citizen privacy and could lead to future "Orwellian" ramifications with government abuse. Going forward, a balance must be found between protecting the privacy of citizens and the enticing use of AI for their health risks and cost savings through prevention. The unimaginable potential of AI early diagnostics from facial photos also raises various ethical and legal concerns. This paper presents concept, protentional methods and legal and other limitations within EU legal framework in contrast with potential benefits. This paper is focused on AI utilization to early diagnostic of rare genetic diseases. Shift of paradigm in the screening for rare genetic diseases in population with AI face analysis is expected to have a significant impact. The potential of AI algorithms utilizations similar to face2gene app in general population or systematically on Big governmental datasets recording facial traits changes in time can have significant impact on public health but at the same time give raise to profound concern as violation of one’s privacy.
Keywords
Deep phenotyping; AI; 2D and 3D facial scans; Genetic diseases; Early treatment; Big data; 2D and 3D facial scans; Facial traits; Healthcare; Citizen privacy; Ethical concerns; EU legal framework; Forensic medicine; Orwellian ramifications
Subject
Medicine and Pharmacology, Epidemiology and Infectious Diseases
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.