ENSURING FAIRNESS AND TRANSPARENCY IN AI SYSTEMS FOR HEALTHCARE AND CRIMINAL JUSTICE APPLICATIONS

October 2024
Vol-10, Issue-5
Paper ID: 25139
ISSN: 2395-4396
Downloads: 0

Abstract & Details

Research Area
Computer Engineering
Keywords
Artificial Intelligence (AI) Healthcare Criminal Justice Ethical Guidelines Biased Decision-Making Demographic Inequalities Fairness Metrics Data Collection Methods Transparency Mechanisms Human Oversight Bias Mitigation Techniques Regulatory Frameworks Equity in AI Algorithmic Interventions.
Abstract
Artificial intelligence (AI) has revolutionized sensitive domains such as healthcare and criminal justice, offering improved accuracy and efficiency in decision-making processes. However, the integration of AI in these areas also presents significant risks, particularly concerning biased outcomes that may disproportionately affect certain demographic groups and exacerbate existing inequalities. This study explores the importance of implementing ethical guidelines to prevent biased decision-making in AI systems within healthcare and criminal justice. We hypothesize that while AI has the potential to enhance decision-making processes, significant ethical considerations and potential biases must be addressed to ensure fair and equitable outcomes. To mitigate bias, we propose a comprehensive framework that encompasses diverse data collection methods, fairness metrics, transparency mechanisms, human oversight, bias mitigation techniques, and supportive regulatory frameworks. By ensuring diversity in data collection and preprocessing, developing fairness metrics and evaluation protocols, incorporating explain ability and transparency, mandating human oversight, employing algorithmic interventions for bias mitigation, and establishing legal and regulatory frameworks, AI systems can be designed to operate in an ethical, fair, and transparent manner. The implementation of these guidelines is crucial to unlock the full potential of AI in healthcare and criminal justice while safeguarding against the perpetuation of social and institutional biases.

Author Information

# Name Institute / Affiliation
1 Manu Gowda CMR University
2 Lavanya V CMR University

How to Cite

Use the following formats to cite this article in your research.

APA Style
Gowda, Manu & V, Lavanya (2024). ENSURING FAIRNESS AND TRANSPARENCY IN AI SYSTEMS FOR HEALTHCARE AND CRIMINAL JUSTICE APPLICATIONS. International Journal of Advance Research and Innovative Ideas In Education, 10(5), 1669-1673.
MLA Style
Gowda, Manu, and Lavanya V. "ENSURING FAIRNESS AND TRANSPARENCY IN AI SYSTEMS FOR HEALTHCARE AND CRIMINAL JUSTICE APPLICATIONS." International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 5, 2024, pp. 1669-1673.
IEEE Style
Manu Gowda and Lavanya V, "ENSURING FAIRNESS AND TRANSPARENCY IN AI SYSTEMS FOR HEALTHCARE AND CRIMINAL JUSTICE APPLICATIONS," International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 5, pp. 1669-1673, 2024.
Vancouver Style
Gowda Manu, V Lavanya. ENSURING FAIRNESS AND TRANSPARENCY IN AI SYSTEMS FOR HEALTHCARE AND CRIMINAL JUSTICE APPLICATIONS. International Journal of Advance Research and Innovative Ideas In Education. 2024;10(5):1669-1673.
Harvard Style
Gowda, Manu & V, Lavanya (2024) 'ENSURING FAIRNESS AND TRANSPARENCY IN AI SYSTEMS FOR HEALTHCARE AND CRIMINAL JUSTICE APPLICATIONS', International Journal of Advance Research and Innovative Ideas In Education, 10(5), pp. 1669-1673.
Chicago Style
Gowda, Manu and Lavanya V. "ENSURING FAIRNESS AND TRANSPARENCY IN AI SYSTEMS FOR HEALTHCARE AND CRIMINAL JUSTICE APPLICATIONS." International Journal of Advance Research and Innovative Ideas In Education 10, no. 5 (2024): 1669-1673.
Turabian Style
Gowda, Manu and Lavanya V. "ENSURING FAIRNESS AND TRANSPARENCY IN AI SYSTEMS FOR HEALTHCARE AND CRIMINAL JUSTICE APPLICATIONS." International Journal of Advance Research and Innovative Ideas In Education 10, no. 5 (2024): 1669-1673.

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