Artificial intelligence in melanoma diagnosis: Three scenarios, shifts in competencies, need for regulation, and reconciling dissent between humans and AI
Tools based on machine learning (so-called artificial intelligence, AI) are increasingly being developed to diagnose malignant melanoma in dermatology. This contribution discusses (1) three scenarios for the use of AI in different medical settings, (2) shifts in competencies from dermatologists to...
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| Format: | Article |
| Language: | deu |
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oekom verlag GmbH
2024-03-01
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| Series: | TATuP – Zeitschrift für Technikfolgenabschätzung in Theorie und Praxis |
| Subjects: | |
| Online Access: | https://www.tatup.de/index.php/tatup/article/view/7102 |
| _version_ | 1827317599472451584 |
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| author | Jan C. Zoellick Hans Drexler Konstantin Drexler |
| author_facet | Jan C. Zoellick Hans Drexler Konstantin Drexler |
| author_sort | Jan C. Zoellick |
| collection | DOAJ |
| description |
Tools based on machine learning (so-called artificial intelligence, AI) are increasingly being developed to diagnose malignant melanoma in dermatology. This contribution discusses (1) three scenarios for the use of AI in different medical settings, (2) shifts in competencies from dermatologists to non-specialists and empowered patients, (3) regulatory frameworks to ensure safety and effectiveness and their consequences for AI tools, and (4) cognitive dissonance and potential delegation of human decision-making to AI. We conclude that AI systems should not replace human medical expertise but play a supporting role. We identify needs for regulation and provide recommendations for action to help all (human) actors navigate safely through the choppy waters of this emerging market. Potential dilemmas arise when AI tools provide diagnoses that conflict with human medical expertise. Reconciling these conflicts will be a major challenge.
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| first_indexed | 2024-04-24T23:41:37Z |
| format | Article |
| id | doaj.art-c3eecc463d6c48ad916f78facb081ff5 |
| institution | Directory Open Access Journal |
| issn | 2568-020X 2567-8833 |
| language | deu |
| last_indexed | 2024-04-24T23:41:37Z |
| publishDate | 2024-03-01 |
| publisher | oekom verlag GmbH |
| record_format | Article |
| series | TATuP – Zeitschrift für Technikfolgenabschätzung in Theorie und Praxis |
| spelling | doaj.art-c3eecc463d6c48ad916f78facb081ff52024-03-15T12:19:41Zdeuoekom verlag GmbHTATuP – Zeitschrift für Technikfolgenabschätzung in Theorie und Praxis2568-020X2567-88332024-03-0133110.14512/tatup.33.1.48Artificial intelligence in melanoma diagnosis: Three scenarios, shifts in competencies, need for regulation, and reconciling dissent between humans and AIJan C. Zoellick0Hans Drexler1Konstantin Drexler2Institute of Medical Sociology and Rehabilitation Science, Charité – University medecine Berlin, BerlinInstitut und Poliklinik für Arbeits-, Sozial- und Umweltmedizin, FAU Erlangen-Nürnberg, ErlangenDepartment for Dermatology, University Hospital Regensburg, Regensburg Tools based on machine learning (so-called artificial intelligence, AI) are increasingly being developed to diagnose malignant melanoma in dermatology. This contribution discusses (1) three scenarios for the use of AI in different medical settings, (2) shifts in competencies from dermatologists to non-specialists and empowered patients, (3) regulatory frameworks to ensure safety and effectiveness and their consequences for AI tools, and (4) cognitive dissonance and potential delegation of human decision-making to AI. We conclude that AI systems should not replace human medical expertise but play a supporting role. We identify needs for regulation and provide recommendations for action to help all (human) actors navigate safely through the choppy waters of this emerging market. Potential dilemmas arise when AI tools provide diagnoses that conflict with human medical expertise. Reconciling these conflicts will be a major challenge. https://www.tatup.de/index.php/tatup/article/view/7102melanomadiagnosisartificial intelligencepatient-doctor relationshipdiagnostic accuracy |
| spellingShingle | Jan C. Zoellick Hans Drexler Konstantin Drexler Artificial intelligence in melanoma diagnosis: Three scenarios, shifts in competencies, need for regulation, and reconciling dissent between humans and AI TATuP – Zeitschrift für Technikfolgenabschätzung in Theorie und Praxis melanoma diagnosis artificial intelligence patient-doctor relationship diagnostic accuracy |
| title | Artificial intelligence in melanoma diagnosis: Three scenarios, shifts in competencies, need for regulation, and reconciling dissent between humans and AI |
| title_full | Artificial intelligence in melanoma diagnosis: Three scenarios, shifts in competencies, need for regulation, and reconciling dissent between humans and AI |
| title_fullStr | Artificial intelligence in melanoma diagnosis: Three scenarios, shifts in competencies, need for regulation, and reconciling dissent between humans and AI |
| title_full_unstemmed | Artificial intelligence in melanoma diagnosis: Three scenarios, shifts in competencies, need for regulation, and reconciling dissent between humans and AI |
| title_short | Artificial intelligence in melanoma diagnosis: Three scenarios, shifts in competencies, need for regulation, and reconciling dissent between humans and AI |
| title_sort | artificial intelligence in melanoma diagnosis three scenarios shifts in competencies need for regulation and reconciling dissent between humans and ai |
| topic | melanoma diagnosis artificial intelligence patient-doctor relationship diagnostic accuracy |
| url | https://www.tatup.de/index.php/tatup/article/view/7102 |
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