Paper Type
Complete
Abstract
As Artificial Intelligence (AI) becomes more integrated into healthcare, it is essential to understand what concerns people have about its ethical use. To understand this, our study analyzed public conversations about AI in healthcare across major social media platforms from Jan 2015 through Nov 2025. Using data analysis techniques and generative AI, we examined what ethical issues people were discussing and how they felt about them. Our findings identified several major themes in public discussions related to privacy and data protection, transparency and explainability, bias and fairness, safety and risk management, trust and adoption, regulatory compliance, accountability and liability, and governance and oversight. These findings help developers, healthcare organizations, and policymakers better align AI systems with public expectations by incorporating real-world perspectives into ethical decision-making.
Paper Number
1400
Recommended Citation
Wahbeh, Abdullah; El-Gayar, Omar; Al-Ramahi, Mohammad; Elnoshokaty, Ahmed Said; and Nasralah, Tareq, "Ethical Concerns in AI-Driven Healthcare: A Social Media Discourse Analysis" (2026). AMCIS 2026 Proceedings. 4.
https://aisel.aisnet.org/amcis2026/sig_odis/sig_odis/4
Ethical Concerns in AI-Driven Healthcare: A Social Media Discourse Analysis
As Artificial Intelligence (AI) becomes more integrated into healthcare, it is essential to understand what concerns people have about its ethical use. To understand this, our study analyzed public conversations about AI in healthcare across major social media platforms from Jan 2015 through Nov 2025. Using data analysis techniques and generative AI, we examined what ethical issues people were discussing and how they felt about them. Our findings identified several major themes in public discussions related to privacy and data protection, transparency and explainability, bias and fairness, safety and risk management, trust and adoption, regulatory compliance, accountability and liability, and governance and oversight. These findings help developers, healthcare organizations, and policymakers better align AI systems with public expectations by incorporating real-world perspectives into ethical decision-making.
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