Towards FATE in AI for Social Media and Healthcare: A Systematic Review

• URL: http://arxiv.org/abs/2306.05372v1
• Date: Mon, 5 Jun 2023 17:25:42 GMT
• Title: Towards FATE in AI for Social Media and Healthcare: A Systematic Review
• Authors: Aditya Singhal, Hasnaat Tanveer, Vijay Mago
• Abstract summary: This survey focuses on the concepts of fairness, accountability, transparency, and ethics (FATE) within the context of AI. We found that statistical and intersectional fairness can support fairness in healthcare on social media platforms. While solutions like simulation, data analytics, and automated systems are widely used, their effectiveness can vary.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: As artificial intelligence (AI) systems become more prevalent, ensuring fairness in their design becomes increasingly important. This survey focuses on the subdomains of social media and healthcare, examining the concepts of fairness, accountability, transparency, and ethics (FATE) within the context of AI. We explore existing research on FATE in AI, highlighting the benefits and limitations of current solutions, and provide future research directions. We found that statistical and intersectional fairness can support fairness in healthcare on social media platforms, and transparency in AI is essential for accountability. While solutions like simulation, data analytics, and automated systems are widely used, their effectiveness can vary, and keeping up-to-date with the latest research is crucial.

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