# Algorithm Biases * **Definition:** Algorithm biases refer to systematic and unfair discrimination that can occur in healthcare algorithms due to flawed data, design choices, or assumptions, leading to unequal treatment outcomes for different patient populations. * **Taxonomy:** CTO Topics / Algorithm Biases ## News * Selected news on the topic of **Algorithm Biases**, for healthcare technology leaders * 757 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]] | | 3/20/2025 | [**Why strategy beats speed in introducing AI for healthcare - The World Economic Forum**](https://www.weforum.org/stories/2025/03/ai-healthcare-strategy-speed/) | [[World Economic Forum]] | | 3/4/2025 | [**Transforming healthcare through just, equitable and quality driven artificial intelligence ... - Nature**](https://www.nature.com/articles/s41746-025-01534-0) | [[Nature]] | | 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]] | | 2/24/2025 | [**AI-Driven Platforms: Revolutionizing Business Operations and Decision-Making**](https://www.cioreview.com/news/aidriven-platforms-revolutionizing-business-operations-and-decisionmaking-nid-40796-cid-175.html) | [[CIO Review]] | | 2/11/2025 | [**AI-Powered Healthcare: Breakthroughs, Policies & Future Trends - Raouf Hajji, MD, PhD.**](https://www.linkedin.com/pulse/ai-powered-healthcare-breakthroughs-policies-future-hajji-md-phd--oaanf) | [[Linkedin]] | | 2/4/2025 | [**Artificial Intelligence (AI) Market to grow by USD 237.4 Billion (2024-2028), Fraud ... - PR Newswire**](https://www.prnewswire.com/news-releases/artificial-intelligence-ai-market-to-grow-by-usd-237-4-billion-2024-2028-fraud-prevention-and-malicious-attacks-drives-growth-report-explores-market-evolution-powered-by-ai---technavio-302366124.html) | [[PR Newswire]] | | 2/3/2025 | [**Artificial Intelligence (AI) Market to Grow by USD 237.4 Billion from 2024-2028 ... - PR Newswire**](https://www.prnewswire.com/news-releases/artificial-intelligence-ai-market-to-grow-by-usd-237-4-billion-from-2024-2028--driven-by-fraud-prevention-and-malicious-attack-mitigation-report-on-ais-market-transformation---technavio-302365986.html) | [[PR Newswire]] | | 2/3/2025 | [**AI Agents: New Frontier for Transforming Healthcare - Alex G. Lee, Ph.D. Esq. CLP**](https://www.linkedin.com/pulse/ai-agents-new-frontier-transforming-healthcare-lee-ph-d-esq-clp-5yfbe) | [[Linkedin]] | | 2/1/2025 | [**Artificial Intelligence Solutions: Transforming Telehealth - LinkedIn**](https://www.linkedin.com/pulse/artificial-intelligence-solutions-transforming-telehealth-d0dhe) | [[Linkedin]] | | 1/30/2025 | [**Healthcare AI Agents: New Opportunities for the High-Tech Industry - Medium**](https://medium.com/@alexglee/healthcare-ai-agents-new-opportunities-for-the-high-tech-industry-f19c6c41c232) | [[Medium]] | | 1/25/2025 | [**Environment scan of generative AI infrastructure for clinical and translational science**](https://www.nature.com/articles/s44401-024-00009-w) | [[Nature]] | | 12/31/2024 | [**AI in Healthcare: Accountability a Key Focus in 2025 - MedPage Today**](https://www.medpagetoday.com/special-reports/features/113596) | [[Medpage Today]] | | 12/20/2024 | [**The Download: Digital Twins, AI Data, and the Future of Healthcare - Medium**](https://medium.com/vanguard-industry-foresight/the-download-digital-twins-ai-data-and-the-future-of-healthcare-64cb675dfb58) | [[Medium]] | | 12/9/2024 | [**Medical Billing Challenges: How Healthcare AI Helps Navigate Claim Denials**](https://www.healthitanswers.net/medical-billing-challenges-how-healthcare-ai-helps-navigate-claim-denials/) | [[Health IT Answers]] | | 12/2/2024 | [**2024 Tech And IT Recap: Transformations, Trials, And Triumphs - Forbes**](https://www.forbes.com/sites/emilsayegh/2024/12/02/2024-tech-and-it-recap-transformations-trials-and-triumphs/) | [[Forbes]] | | 11/22/2024 | [**Health Boards Of Directors Must Drive AI Governance And Accountability - Forbes**](https://www.forbes.com/councils/forbestechcouncil/2024/11/22/health-boards-of-directors-must-drive-ai-governance-and-accountability/) | [[Forbes]] | | 10/27/2024 | [**Civitas 2024: Advancing Health Data Exchange through Local Partnerships and Data Integration**](https://www.healthitanswers.net/civitas-2024-advancing-health-data-exchange-through-local-partnerships-and-data-integration/) | [[Health IT Answers]] | | 9/25/2024 | [**How AI is shaping the future of medicine - Fast Company**](https://www.fastcompany.com/91196757/how-ai-is-shaping-the-future-of-medicine) | [[Fast Company]] | | 9/2/2024 | [**Revolutionising healthcare: Big data analytics and AI at the forefront of medical innovation**](https://gulfnews.com/uae/health/revolutionising-healthcare-big-data-analytics-and-ai-at-the-forefront-of-medical-innovation-1.1725260556563) | gulfnews.com | | 7/22/2024 | [**Data Science in Healthcare: Innovations and Challenges**](https://www.thequint.com/brandstudio/partner-data-science-healthcare) | thequint.com | | 7/17/2024 | [**Seneca Polytechnic Leads Seminar on AI In Healthcare, Announces New Programs And Industry Collaborations**](https://www.bignewsnetwork.com/news/274460794/seneca-polytechnic-leads-seminar-on-ai-in-healthcare-announces-new-programs-and-industry-collaborations) | bignewsnetwork.com | | 7/16/2024 | [**Ethical Considerations in the Use of Artificial Intelligence and Machine Learning in Health Care**](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11249277/) | [[NCBI - NIH]] | | 7/11/2024 | [**Seven Important Actions to Manage Cyber Risk While Benefiting from AI**](https://www.healthitanswers.net/seven-important-actions-to-manage-cyber-risk-while-benefiting-from-ai/) | [[Health IT Answers]] | | 7/3/2024 | [**Transformative AI Applications in Healthcare: Enhancing Diagnostics, Treatment, and Efficiency**](https://www.techtimes.com/articles/306332/20240703/transformative-ai-applications-in-healthcare-enhancing-diagnostics-treatment-and-efficiency.htm) | techtimes.com | ## Topic Overview (Some LLM-derived content — please confirm with above primary sources) ### Key Players - **OpenAI**: Developed AI technologies like ChatGPT, raising concerns about algorithmic bias. - **ECRI**: An organization that assesses health technology risks, including the potential biases in AI systems. - **California Government**: Enacted laws regulating algorithm use in healthcare to ensure human oversight and transparency. - **Brookings Center for Technology Innovation**: Established The AI Equity Lab to promote responsible AI design across sectors, including healthcare. - **Dr. Sonya Makhni**: Panelist discussing clinician skepticism towards AI and the importance of governance. - **American College of Physicians (ACP)**: An organization shaping policies for ethical AI use in healthcare. - **Brian Anderson**: CEO of the Coalition for Health AI, promoting collaboration for best practices in AI. - **DeepSeek**: A company developing specialized AI solutions for specific industries, including healthcare. - **Dr. Antoine Keller**: Utilizes AI tool Heart Sense to enhance community health interventions. - **Dr. Patrick Thomas**: Advocate for revamping clinical training to prepare healthcare professionals for AI integration. - **DLA Piper**: A multinational law firm integrating data scientists into their teams to enhance AI compliance practices. - **Proprio**: A healthcare technology company focusing on AI applications to enhance diagnostics and treatment planning. - **World Health Organization**: Emphasizes international collaboration and governance frameworks for equitable AI technologies. - **Faegre Drinker**: A law firm that established Tritura, employing data scientists to advise clients on AI and machine learning. - **Mpathic**: Develops generative AI tools to improve cultural attunement in mental health care for underserved populations. - **Microsoft**: A major technology company developing AI-powered healthcare solutions to improve patient care and operational efficiency. - **Gong Rujing**: Chairman of Yidu Tech, emphasizing the integration of specialized knowledge with data for AI advancements. - **Dr. Tim O'Connell**: CEO of emtelligent, advocating for safe and transparent AI applications in healthcare. ### Partnerships and Collaborations - **U.S. Department of Defense and Humane Intelligence**: Collaborated on a red-teaming pilot program to evaluate large language models for military medical services, identifying vulnerabilities and biases. - **Health and AI Working Group**: A group of experts focusing on inclusive AI applications in healthcare for underrepresented communities. - **Coalition for Health AI**: Working with various organizations to create standardized approaches for AI development and implementation. - **Avant Technologies, Inc. and Ainnova Tech, Inc.**: A joint venture aimed at advancing early disease detection using AI technologies. - **Ochsner Health**: Utilizing AI tools to enhance healthcare access in underserved areas. - **Mayo Clinic and Nvidia**: Collaborated on a Digital Pathology system utilizing AI for improved diagnostics. - **Mpathic and Wave**: Collaborating to analyze conversational data to enhance cultural responsiveness in mental health care. - **Florida State University**: Establishing an AI Innovation Consortium to enhance nursing education and prepare future healthcare workers. ### Innovations, Trends, and Initiatives - **AI Equity Lab**: Promotes inclusive AI design in healthcare to address algorithmic biases affecting vulnerable populations. - **AI Ethics Framework by NIH**: An initiative to develop guidelines addressing biases in AI applications within healthcare. - **Digital Health Technologies**: Generate data that can train AI algorithms, impacting healthcare delivery and highlighting the need to address biases. - **Human-in-the-loop Systems**: An approach advocating for human oversight in AI decision-making to minimize biases and errors. - **California's AI Legislation**: Aims to ensure responsible AI use in healthcare, addressing algorithmic bias. - **Generative AI Applications**: Technologies that create synthetic datasets for research while protecting patient privacy. - **AI Task Force by Peterson Health Technology Institute**: Evaluating AI's impact on healthcare costs and efficiency. - **Generative AI (GenAI)**: Transforming healthcare by enhancing diagnostic accuracy and operational efficiencies. - **Generative AI in Femtech**: Utilizes AI to analyze data for improving female health outcomes, addressing historical biases in medical research. - **Retrieval-Augmented Generation (RAG)**: A method enhancing AI models by allowing access to domain-specific data for improved accuracy. - **AI-Driven Drug Discovery**: Platforms like DeepSeek and Qwen democratizing access to drug development. - **Generative AI**: Transforming healthcare delivery by enhancing diagnostics, treatment, and operational efficiencies. - **AI-Enhanced Universal Health and Prevention Act of 2024**: Proposed legislation aimed at providing equitable access to AI-enhanced preventive health services, including the establishment of an AI Fairness Board. - **ISO/IEC 42001**: An emerging international standard aimed at regulating the responsible use of AI, promoting security, privacy, and ethical practices. - **AI in Nursing Education**: Florida State University introduces the first AI-focused Master of Science in Nursing program. ### Challenges and Concerns - **Algorithmic Bias**: Bias in AI algorithms can lead to misdiagnoses and inappropriate treatment recommendations, particularly affecting marginalized groups. - **Clinician Trust**: Skepticism among healthcare professionals regarding AI's reliability and effectiveness. - **Data Privacy and Security**: Concerns regarding data integrity and privacy in AI applications, especially in healthcare settings. - **Data Privacy**: Risks associated with the use of sensitive patient data in AI applications. - **Transparency and Accountability**: The need for clear understanding of AI decision-making processes to ensure reliability. - **Equity in AI Governance**: A lack of consistent equity consideration in the governance of predictive technologies, necessitating health systems to prioritize equity literacy. - **Nursing Concerns**: Nurses express fears that AI may undermine clinical judgment and patient safety. - **Digital Divide**: The disparity in access to AI technologies between different healthcare institutions, particularly those serving marginalized populations. - **Regulatory Gaps**: The differences in approval processes for AI medical devices compared to drugs, leading to potential safety concerns. - **Regulatory Compliance**: The need for clear definitions and compliance with regulations to ensure fairness and accountability in AI decision-making. - **Regulatory Barriers**: Need for robust regulatory frameworks to ensure responsible integration of AI in healthcare. ## Related Topics [[Algorithm Bias]]; [[Algorithmic Bias]]; [[Bias in AI Algorithms]]