# Ethical Concerns in AI * **Definition:** Ethical concerns in AI within healthcare refer to the moral implications and responsibilities associated with the development, deployment, and use of artificial intelligence technologies in medical settings. This includes issues related to patient privacy, data security, algorithmic bias, informed consent, accountability for decisions made by AI systems, and the potential impact on healthcare equity and access. * **Taxonomy:** Healthcare Topics / Ethical Concerns in AI ## News * Selected news on the topic of **Ethical Concerns in AI**, for healthcare technology leaders * 6.1K news items are in the system for this topic * Posts have been filtered for tech and healthcare-related keywords | Date | Title | Source | | --- | --- | --- | | 5/30/2025 | [**The Growing Importance Of AI In Provider Data Management**](https://www.forbes.com/councils/forbestechcouncil/2025/05/30/the-growing-importance-of-ai-in-provider-data-management/) | [[Forbes]] | | 5/26/2025 | [**AI can solve many gaps in healthcare, but only with ethical implementation - Viewpoint**](https://www.chiefhealthcareexecutive.com/view/ai-can-solve-many-gaps-in-healthcare-but-only-with-ethical-implementation-viewpoint) | [[Chief Healthcare Executive]] | | 5/26/2025 | [**Privacy & Security - Healthcare IT News**](https://www.healthcareitnews.com/taxonomy/term/6156/news/deep-dive-exploring-one-most-advanced-telemedicine-programs-us?page=29) | [[Healthcare IT News]] | | 5/12/2025 | [**Ethical Implementation of AI in Mental Healthcare: A Practical Guide**](https://hitconsultant.net/2025/05/12/ethical-implementation-of-ai-in-mental-healthcare-a-practical-guide/) | [[HIT Consultant]] | | 4/29/2025 | [**Why Healthcare Organizations Must Prioritize AI Governance**](https://healthtechmagazine.net/article/2025/04/why-healthcare-organizations-must-prioritize-ai-governance) | [[HealthTech Magazine]] | | 4/10/2025 | [**Google Cloud healthcare agentic AI and AI transformation solutions - PwC**](https://www.pwc.com/us/en/technology/alliances/google-cloud/healthcare-ai-agents-solutions.html) | [[PWC]] | | 3/21/2025 | [**AI Governance & Compliance Framework for LLMs in Healthcare - Medium**](https://medium.com/@dr.davuluri/ai-governance-compliance-framework-for-llms-in-healthcare-52ec6d7bffef) | [[Medium]] | | 3/20/2025 | [**Sasikiran Vepanambattu Subramanyam Honored with 2025 Noble Business Awards for ...**](https://markets.businessinsider.com/news/stocks/sasikiran-vepanambattu-subramanyam-honored-with-2025-noble-business-awards-for-excellence-in-healthcare-automation-and-financial-systems-innovation-1034495958) | [[Business Insider Markets]] | | 3/10/2025 | [**Headways and hurdles: How AI is shaping the future of medicine - Medical Xpress**](https://medicalxpress.com/news/2025-03-headways-hurdles-ai-future-medicine.html) | [[MedicalXpress]] | | 3/9/2025 | [**AI in Healthcare: Minimum Requirements to Enter the Field - Medium**](https://medium.com/@hiya31/ai-in-healthcare-minimum-requirements-to-enter-the-field-eb76bf824895) | [[Medium]] | | 3/2/2025 | [**Can AI Outperform Doctors in Diagnosing Infectious Diseases?**](https://www.news-medical.net/health/Can-AI-Outperform-Doctors-in-Diagnosing-Infectious-Diseases.aspx) | [[News Medical Net]] | | 2/14/2025 | [**Engineering a Healthcare Analytics Center of Excellence (ACoE): A Strategic Framework for ...**](https://blogs.perficient.com/2025/02/14/engineering-a-healthcare-analytics-center-of-excellence-acoe-a-strategic-framework-for-innovation/) | [[Perficient Healthcare]] | | 2/10/2025 | [**Launching the Trustworthy and Responsible AI Network (TRAIN) A Consortium to Facilitate ...**](https://jamanetwork.com/journals/jama/articlepdf/2830340/jama_emb_2025_vp_250019_1738942291.693.pdf) | [[JAMA Network]] | | 1/31/2025 | [**Deloitte Earns Top Recognition in Healthcare IT for AI, Cloud, and Digital Innovation, Black ...**](https://finance.yahoo.com/news/deloitte-earns-top-recognition-healthcare-194500093.html) | [[Yahoo Finance]] | | 1/29/2025 | [**Healthcare AI Agents: New Opportunities for the High-Tech Industry - Alex G. Lee, Ph.D. Esq. CLP**](https://www.linkedin.com/pulse/healthcare-ai-agents-new-opportunities-high-tech-lee-ph-d-esq-clp-hkl2e) | [[Linkedin]] | | 1/25/2025 | [**Environment scan of generative AI infrastructure for clinical and translational science**](https://www.nature.com/articles/s44401-024-00009-w) | [[Nature]] | | 1/12/2025 | [**Hyperautomation in Healthcare: Transforming IT with Benefits and Risks**](https://hitconsultant.net/2025/01/13/hyperautomation-in-healthcare-transforming-it-with-benefits-and-risks/) | [[HIT Consultant]] | | 1/6/2025 | [**The AI Revolution in Healthcare. Authors: Tim Hulsen, Senior Data & AI… - Philips Technology Blog**](https://medium.com/philips-technology-blog/the-ai-revolution-in-healthcare-2fe341229ac2) | [[Medium]] | | 12/16/2024 | [**How GSIs Help Healthcare Providers Improve Patient Care With GenAI**](https://www.forbes.com/sites/stevemcdowell/2024/12/16/how-gsis-help-healthcare-providers-improve-patient-care-with-genai/) | [[Forbes]] | | 12/14/2024 | [**The Future of Production: Scaling Innovation with Hybrid Computing, AI, and Automation**](https://www.cioreview.com/news/the-future-of-production-scaling-innovation-with-hybrid-computing-ai-and-automation-nid-40640-cid-175.html) | [[CIO Review]] | | 12/13/2024 | [**Title: Navigating the Generative AI Journey: A Strategic Roadmap for Healthcare Organizations**](https://blogs.perficient.com/2024/12/13/title-navigating-the-generative-ai-journey-a-strategic-roadmap-for-healthcare-organizations/) | [[Perficient Healthcare]] | | 11/8/2024 | [**AI-driven precision healthcare is here - what you need to know**](https://www.healthcareitnews.com/news/ai-driven-precision-healthcare-here-what-you-need-know) | [[Healthcare IT News]] | | 11/7/2024 | [**Healthcare Compliance Professionals Grapple with Mounting Risks and Limited Resources**](https://hitconsultant.net/2024/11/08/healthcare-compliance-professionals-grapple-with-mounting-risks/) | [[HIT Consultant]] | | 11/4/2024 | [**Ready to transform healthcare? Get ready for AI**](https://www.healthcaredive.com/spons/ready-to-transform-healthcare-get-ready-for-ai/731163/) | [[Healthcare Dive]] | | 1/22/2024 | [**AI risks in healthcare: Misdiagnosis, inequality, and ethical concerns**](https://www.news-medical.net/news/20240123/AI-risks-in-healthcare-Misdiagnosis-inequality-and-ethical-concerns.aspx) | [[News Medical Net]] | ## Topic Overview (Some LLM-derived content — please confirm with above primary sources) ### Key Players - **AI Trust Foundation**: An organization focused on enhancing the safe and beneficial use of AI through collaboration and innovation. - **IBM**: A technology company collaborating with various organizations to enhance AI governance and ethical practices. - **Antoine Tesnière**: A professor advocating for global collaboration to ensure ethical AI use and patient privacy. - **Hippocratic AI**: A company focused on creating AI solutions for healthcare, emphasizing safety and ethical practices. - **ECRI**: An organization that highlights health technology risks and emphasizes the importance of assessing AI systems for patient safety. - **Coalition for Health AI**: A collaborative organization focused on establishing best practices and standards for AI in healthcare. - **Department of Health and Human Services (HHS)**: Government body outlining strategic goals for AI integration in healthcare, emphasizing ethical standards and risk identification. - **OpenAI**: A leading AI research organization known for developing advanced AI models, including those used in healthcare applications. - **Kipu Health**: A behavioral health technology leader collaborating with AWS to implement ethical AI solutions. - **Talkspace**: A mental health service provider focusing on ethical AI usage to enhance provider efficiency. - **Microsoft**: Partnering with healthcare institutions to enhance AI applications in medical imaging and ensure responsible AI development. - **ALIGNMT AI**: Collaborating with HFMA to enhance AI governance skills among healthcare professionals. - **Dr. Becky Upton**: A representative from The Pistoia Alliance, discussing the implications of AI in life sciences and healthcare. - **Amazon**: A significant contributor to AI advancements, particularly in cloud computing and healthcare applications. - **Trustworthy and Responsible AI Network (TRAIN)**: A consortium aimed at promoting safe and effective AI adoption across sectors, including healthcare, by fostering collaboration among stakeholders. - **FDA's Digital Health Advisory Committee**: Regulatory body discussing guidelines for generative AI-enabled medical devices. - **Google**: A key innovator in AI technologies, including applications in healthcare. - **Providence**: A health system implementing a comprehensive AI governance strategy prioritizing patient safety and data security. - **Gwynedd Mercy University**: An educational institution focusing on the ethical use of technology, including AI, in healthcare education. ### Partnerships and Collaborations - **IBM and e&**: Implementing a comprehensive AI governance solution to enhance compliance and ethical practices. - **Gardner Law and Mitchell Hamline School of Law**: Co-hosted an event focusing on the regulatory and ethical implications of AI in healthcare. - **Peterson Health Technology Institute**: Initiated an AI task force to evaluate AI's impact on healthcare costs and efficiency. - **International Collaboration**: The WHO advocates for global partnerships to ensure AI technologies meet the diverse needs of populations, particularly in low- and middle-income countries (LMICs). - **Coalition for Health AI and Health Systems**: Working together to create standardized approaches for AI tool development and implementation. - **ALIGNMT AI and HFMA**: Launching a micro-credentialing program to enhance AI governance skills in healthcare. - **Talkspace and Iliff Innovation Lab**: Exploring AI's potential to enhance mental health services and reduce administrative burdens. - **Hippocratic AI and Nurses on Boards Coalition**: A strategic partnership aimed at enhancing nurses' influence in healthcare technology and promoting their active participation in shaping future innovations. - **Healthcare Institutions and Governments**: Proactive collaboration is essential for addressing challenges and creating localized datasets for effective AI deployment in LMICs. - **Nanyang Technological University and National Healthcare Group**: Launched the Centre of AI in Medicine to integrate AI technologies into practical medical applications. - **PCG and Synergist Technology**: Enhancing AI governance, security, and compliance solutions across various industries. - **Kipu Health and AWS**: Partnering to develop AI tools aimed at improving clinical workflows and patient care in behavioral health. - **MDIC and Manufacturers**: Partnerships aimed at enhancing genomic testing reliability and developing frameworks for AI validation. - **Microsoft and Mass General Brigham**: Working together to improve generative AI applications in radiology. - **CareMessage and Google Gemini**: Utilizing Google's AI for enhancing patient communication and addressing healthcare disparities. - **Gwynedd Mercy University and Healthcare Innovation Center**: Aiming to focus on the ethical use of technology in healthcare education. - **Viz.ai and Microsoft**: Collaborated to integrate AI diagnostic imaging models into clinical workflows. - **Microsoft and Providence**: Collaborating to develop multimodal medical imaging foundation models for healthcare data analysis. ### Innovations, Trends, and Initiatives - **EU AI Act**: A framework established to ensure ethical development and deployment of AI in healthcare. - **AI Governance Programs**: The establishment of robust AI governance frameworks to ensure ethical AI development and deployment in healthcare. - **AI Governance Frameworks**: Organizations are encouraged to adopt robust governance frameworks to ensure ethical AI use and compliance. - **AI Governance**: Healthcare organizations are increasingly recognizing the need for AI governance frameworks to address ethical concerns and ensure compliance with regulations. - **AI Governance Initiatives**: Organizations are increasingly establishing AI governance frameworks to ensure ethical AI use and compliance with regulations. - **AI in Nursing Informatics**: AI is expected to enhance nursing practices while emphasizing the need for ethical considerations. - **Generative AI**: Emerging as a significant disruptor in healthcare, generative AI has the potential to enhance drug discovery and personalize patient engagement, but raises ethical concerns. - **ECRI's Annual Report**: Identifying AI as a top health technology hazard and emphasizing the need for careful risk assessment. - **AI task force by Peterson Health Technology Institute**: Evaluating AI's impact on healthcare efficiency and costs. - **Trustworthy Responsible AI Network (TRAIN)**: Established to promote responsible AI practices in healthcare, focusing on underserved communities. - **AI in Healthcare**: AI is being integrated into healthcare for improved patient outcomes, operational efficiency, and enhanced decision-making. - **HHS Strategic Plan**: Outlines goals for trustworthy AI development, external validation, and workforce empowerment in healthcare. - **Generative AI Adoption**: Nearly half of U.S. health systems are adopting generative AI, indicating a significant shift towards digital innovation despite existing trust issues. - **AI in Clinical Trials**: Decentralized clinical trials (DCTs) are being enhanced by AI, allowing participants to engage remotely, which addresses traditional barriers and improves accessibility. - **Generative AI in Healthcare**: A focus on leveraging generative AI to alleviate administrative burdens on healthcare professionals and improve patient care. - **AI in Clinical Decision Support**: Personalized systems analyzing patient data to improve outcomes and reduce clinician burnout. - **Generative AI (GenAI)**: Emerging as a significant trend in healthcare, focusing on enhancing care delivery and patient outcomes. ### Challenges and Concerns - **Data Privacy and Security**: Critical issues that need to be addressed to ensure the ethical use of AI technologies. - **Transparency in AI Decision-Making**: Concerns about the lack of transparency in how AI systems make decisions. - **Ethical AI Practices**: There is a pressing need for ethical AI practices to prevent biases and ensure equitable healthcare delivery. - **Data Quality and Bias**: Concerns regarding the reliability of data used in AI applications, leading to biased decision-making. - **Bias in AI Algorithms**: Concerns about biased algorithms affecting patient care and outcomes, necessitating robust governance measures. - **Data Privacy**: Concerns regarding the use of unconsented data in AI applications, particularly in healthcare settings. - **Algorithmic Bias**: Concerns about biases in AI systems that could perpetuate healthcare disparities and impact patient care. - **Regulatory Oversight**: The lack of established frameworks for the integration of AI into healthcare raises significant ethical and safety concerns. - **Bias and Inequitable Care**: Risks associated with AI systems that may lead to biased outcomes and inequitable healthcare delivery. - **Lack of Human Oversight**: A significant concern among the public regarding the increasing use of AI in healthcare. - **Privacy and Security**: Ongoing issues related to patient data privacy and the security of AI systems in healthcare. - **Equity in AI Governance**: Risks of marginalized patients being excluded from AI governance discussions, necessitating inclusive practices. - **Accountability and Transparency**: The need for clear accountability in AI decision-making processes, especially in sensitive areas like healthcare. - **Need for Human Oversight**: Despite the benefits of AI, there is a critical need for human oversight to ensure ethical and effective implementation in healthcare settings. - **Bias and Equity**: AI governance is essential to minimize risks associated with bias and ensure equitable care delivery. - **Transparency in Decision-Making**: The need for clear understanding of AI decision-making processes to build trust and accountability. - **Transparency and Accountability**: The 'black box' nature of AI models raises concerns about understanding their decision-making processes and ensuring accountability. ## Related Topics [[Ethical Concerns with AI]]; [[Ethical Considerations in AI]]; [[Ethical Implications of AI]]; [[Ethical AI]]; [[Ethical Use of AI]]; [[Ethical Concerns]]; [[Responsible AI]]; [[Trust in AI]]; [[Skepticism Towards AI]]