Volume 18, Issue 59 (4-2024)
MLJ 2024, 18(59): 217-235 |
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Solhchi S, Biglarbeigi K, Azizi S. Artificial Intelligence Bias against Women in the Field of Health. MLJ 2024; 18 (59) :217-235
URL: http://ijmedicallaw.ir/article-1-1753-en.html
URL: http://ijmedicallaw.ir/article-1-1753-en.html
1- Department of Private Law, Faculty of Law and Political Science, Allameh Tabataba'I University, Tehran, Iran.
2- Department of Public Law, Faculty of Law and Political Science, Tehran University, Tehran, Iran.
3- Department of Law, Faculty of Humanities, Bu-Ali Sina University, Hamedan, Iran.
2- Department of Public Law, Faculty of Law and Political Science, Tehran University, Tehran, Iran.
3- Department of Law, Faculty of Humanities, Bu-Ali Sina University, Hamedan, Iran.
Abstract:
Background and Aim: Artificial intelligence is one of the key players in the fourth industrial revolution. Today, it is impossible to ignore the many benefits that artificial intelligence provides for modern societies, where data has become the most valuable asset of our time. For example, it should be noted that the use of this technology, within the scope of existing laws, helps to protect women's rights. However, artificial intelligence also reveals a dark side; biases, among other risks embodied by artificial intelligence, can directly affect human rights and mainly, the rights of the most vulnerable groups, including women, especially in the area of health. The right to health is one of the fundamental human rights recognized by the international legal system and holds a special position. This right, approved by all countries, requires providing desirable health services and making them available to everyone under equal conditions. The main question of this research is whether artificial intelligence has a neutral or biased approach towards women in the field of health?
Method: The research method of this study is analytical-descriptive and the method of collecting information is the library-based.
Ethical Considerations: In all stages of writing the present research, the ethical aspects of library-based study Including the originality of the texts, honesty and trustworthiness have been observed.
Results: The authors hypothesize that there is a discriminatory bias against women in the field of health. In general, if artificial intelligence algorithms, which are biased and trained with datasets that ignore certain groups, are used for diagnosis or treatment, it may negatively impact the outcomes for entire patient groups, such as ethnic and gender minorities, immigrants, children, the elderly and people with disabilities. As a result, bias in healthcare causes some groups of patients to receive better medical treatment than others.
Conclusion: While there are many real and potential benefits of using artificial intelligence in healthcare, a significant risk is flawed or controversial decision-making due to human biases embedded in AI outputs, which can have significant implications for healthcare. As a result, such biases should be avoided. Here are some solutions that can be implemented to reduce and eliminate bias: use larger datasets with more diversity; transparency; Use gender-based design principles; regular auditing, use of ethical guidelines; Employing diverse research teams; legislation and supervision; education and awareness; Improvement and updating and finally cooperation of health care developers and activists to prevent bias can be effective solutions in this regard.
Please cite this article as:
Solhchi S, Biglarbeigi K, Azizi S. Artificial Intelligence Bias against Women in the Field of Health, Medical Law Journal. 2024; 18: e15.
Method: The research method of this study is analytical-descriptive and the method of collecting information is the library-based.
Ethical Considerations: In all stages of writing the present research, the ethical aspects of library-based study Including the originality of the texts, honesty and trustworthiness have been observed.
Results: The authors hypothesize that there is a discriminatory bias against women in the field of health. In general, if artificial intelligence algorithms, which are biased and trained with datasets that ignore certain groups, are used for diagnosis or treatment, it may negatively impact the outcomes for entire patient groups, such as ethnic and gender minorities, immigrants, children, the elderly and people with disabilities. As a result, bias in healthcare causes some groups of patients to receive better medical treatment than others.
Conclusion: While there are many real and potential benefits of using artificial intelligence in healthcare, a significant risk is flawed or controversial decision-making due to human biases embedded in AI outputs, which can have significant implications for healthcare. As a result, such biases should be avoided. Here are some solutions that can be implemented to reduce and eliminate bias: use larger datasets with more diversity; transparency; Use gender-based design principles; regular auditing, use of ethical guidelines; Employing diverse research teams; legislation and supervision; education and awareness; Improvement and updating and finally cooperation of health care developers and activists to prevent bias can be effective solutions in this regard.
Please cite this article as:
Solhchi S, Biglarbeigi K, Azizi S. Artificial Intelligence Bias against Women in the Field of Health, Medical Law Journal. 2024; 18: e15.
Subject:
Special
Received: 2023/12/17 | Accepted: 2024/03/2
Received: 2023/12/17 | Accepted: 2024/03/2
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