Humanizing AI in medical training: ethical framework for responsible design
<p dir="ltr">The increasing use of artificial intelligence (AI) in healthcare has brought about numerous ethical considerations that push for reflection. Humanizing AI in medical training is crucial to ensure that the design and deployment of its algorithms align with ethical princip...
محفوظ في:
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| مؤلفون آخرون: | , , |
| منشور في: |
2023
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إضافة وسم
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| _version_ | 1864513522546769920 |
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| author | Mohammed Tahri Sqalli (18420840) |
| author2 | Begali Aslonov (23275483) Mukhammadjon Gafurov (23275486) Shokhrukhbek Nurmatov (23275507) |
| author2_role | author author author |
| author_facet | Mohammed Tahri Sqalli (18420840) Begali Aslonov (23275483) Mukhammadjon Gafurov (23275486) Shokhrukhbek Nurmatov (23275507) |
| author_role | author |
| dc.creator.none.fl_str_mv | Mohammed Tahri Sqalli (18420840) Begali Aslonov (23275483) Mukhammadjon Gafurov (23275486) Shokhrukhbek Nurmatov (23275507) |
| dc.date.none.fl_str_mv | 2023-05-16T09:00:00Z |
| dc.identifier.none.fl_str_mv | 10.3389/frai.2023.1189914 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Humanizing_AI_in_medical_training_ethical_framework_for_responsible_design/31444255 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biomedical and clinical sciences Clinical sciences Education Education systems Health sciences Health services and systems Information and computing sciences Artificial intelligence Philosophy and religious studies Applied ethics human-AI interaction Human-Computer Interaction digital health, XAI artificial intelligence |
| dc.title.none.fl_str_mv | Humanizing AI in medical training: ethical framework for responsible design |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">The increasing use of artificial intelligence (AI) in healthcare has brought about numerous ethical considerations that push for reflection. Humanizing AI in medical training is crucial to ensure that the design and deployment of its algorithms align with ethical principles and promote equitable healthcare outcomes for both medical practitioners trainees and patients. This perspective article provides an ethical framework for responsibly designing AI systems in medical training, drawing on our own past research in the fields of electrocardiogram interpretation training and e-health wearable devices. The article proposes five pillars of responsible design: transparency, fairness and justice, safety and wellbeing, accountability, and collaboration. The transparency pillar highlights the crucial role of maintaining the explainabilty of AI algorithms, while the fairness and justice pillar emphasizes on addressing biases in healthcare data and designing models that prioritize equitable medical training outcomes. The safety and wellbeing pillar however, emphasizes on the need to prioritize patient safety and wellbeing in AI model design whether it is for training or simulation purposes, and the accountability pillar calls for establishing clear lines of responsibility and liability for AI-derived decisions. Finally, the collaboration pillar emphasizes interdisciplinary collaboration among stakeholders, including physicians, data scientists, patients, and educators. The proposed framework thus provides a practical guide for designing and deploying AI in medicine generally, and in medical training specifically in a responsible and ethical manner.</p><h2 dir="ltr">Other Information</h2><p dir="ltr">Published in: Frontiers in Artificial Intelligence<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3389/frai.2023.1189914" target="_blank">https://dx.doi.org/10.3389/frai.2023.1189914</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_09aa043405eb330ff19dcd4f87d21959 |
| identifier_str_mv | 10.3389/frai.2023.1189914 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/31444255 |
| publishDate | 2023 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Humanizing AI in medical training: ethical framework for responsible designMohammed Tahri Sqalli (18420840)Begali Aslonov (23275483)Mukhammadjon Gafurov (23275486)Shokhrukhbek Nurmatov (23275507)Biomedical and clinical sciencesClinical sciencesEducationEducation systemsHealth sciencesHealth services and systemsInformation and computing sciencesArtificial intelligencePhilosophy and religious studiesApplied ethicshuman-AI interactionHuman-Computer Interactiondigital health, XAIartificial intelligence<p dir="ltr">The increasing use of artificial intelligence (AI) in healthcare has brought about numerous ethical considerations that push for reflection. Humanizing AI in medical training is crucial to ensure that the design and deployment of its algorithms align with ethical principles and promote equitable healthcare outcomes for both medical practitioners trainees and patients. This perspective article provides an ethical framework for responsibly designing AI systems in medical training, drawing on our own past research in the fields of electrocardiogram interpretation training and e-health wearable devices. The article proposes five pillars of responsible design: transparency, fairness and justice, safety and wellbeing, accountability, and collaboration. The transparency pillar highlights the crucial role of maintaining the explainabilty of AI algorithms, while the fairness and justice pillar emphasizes on addressing biases in healthcare data and designing models that prioritize equitable medical training outcomes. The safety and wellbeing pillar however, emphasizes on the need to prioritize patient safety and wellbeing in AI model design whether it is for training or simulation purposes, and the accountability pillar calls for establishing clear lines of responsibility and liability for AI-derived decisions. Finally, the collaboration pillar emphasizes interdisciplinary collaboration among stakeholders, including physicians, data scientists, patients, and educators. The proposed framework thus provides a practical guide for designing and deploying AI in medicine generally, and in medical training specifically in a responsible and ethical manner.</p><h2 dir="ltr">Other Information</h2><p dir="ltr">Published in: Frontiers in Artificial Intelligence<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3389/frai.2023.1189914" target="_blank">https://dx.doi.org/10.3389/frai.2023.1189914</a></p>2023-05-16T09:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.3389/frai.2023.1189914https://figshare.com/articles/journal_contribution/Humanizing_AI_in_medical_training_ethical_framework_for_responsible_design/31444255CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/314442552023-05-16T09:00:00Z |
| spellingShingle | Humanizing AI in medical training: ethical framework for responsible design Mohammed Tahri Sqalli (18420840) Biomedical and clinical sciences Clinical sciences Education Education systems Health sciences Health services and systems Information and computing sciences Artificial intelligence Philosophy and religious studies Applied ethics human-AI interaction Human-Computer Interaction digital health, XAI artificial intelligence |
| status_str | publishedVersion |
| title | Humanizing AI in medical training: ethical framework for responsible design |
| title_full | Humanizing AI in medical training: ethical framework for responsible design |
| title_fullStr | Humanizing AI in medical training: ethical framework for responsible design |
| title_full_unstemmed | Humanizing AI in medical training: ethical framework for responsible design |
| title_short | Humanizing AI in medical training: ethical framework for responsible design |
| title_sort | Humanizing AI in medical training: ethical framework for responsible design |
| topic | Biomedical and clinical sciences Clinical sciences Education Education systems Health sciences Health services and systems Information and computing sciences Artificial intelligence Philosophy and religious studies Applied ethics human-AI interaction Human-Computer Interaction digital health, XAI artificial intelligence |