# Trust in AI * **Definition:** Trust in AI refers to the confidence that healthcare professionals, patients, and stakeholders have in the reliability, accuracy, and ethical use of artificial intelligence systems in clinical decision-making, diagnostics, and patient care, ensuring that these systems are transparent, explainable, and aligned with human values. * **Taxonomy:** Healthcare Topics / Trust in AI ## News * Selected news on the topic of **Trust in AI**, for healthcare technology leaders * 13.4K 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]] | | 5/25/2025 | [**Action Framework for AI Agents in Healthcare - by Alex G. Lee - May, 2025 - Medium**](https://medium.com/@alexglee/action-framework-for-ai-agents-in-healthcare-f4801f8dcaa6) | [[Medium]] | | 5/19/2025 | [**TruBridge Integrates Microsoft Dragon Copilot into EHR**](https://hitconsultant.net/2025/05/19/trubridge-integrates-microsoft-dragon-copilot-into-ehr/) | [[HIT Consultant]] | | 5/12/2025 | [**Should health systems disclose when they're using AI?**](https://www.beckershospitalreview.com/healthcare-information-technology/ai/should-health-systems-disclose-when-theyre-using-ai/) | [[Beckers Hospital Review]] | | 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]] | | 3/26/2025 | [**New Jersey Innovation Institute and Cognome Announce Strategic Partnership to Advance AI-Powered Healthcare Solutions**](https://www.prnewswire.com/news-releases/new-jersey-innovation-institute-and-cognome-announce-strategic-partnership-to-advance-ai-powered-healthcare-solutions-302412169.html) | [[PR Newswire]] | | 3/26/2025 | [**New Jersey Innovation Institute and Cognome Announce Strategic Partnership to Advance ...**](https://finance.yahoo.com/news/jersey-innovation-institute-cognome-announce-152800473.html) | [[Yahoo Finance]] | | 3/22/2025 | [**Weekly Roundup - March 22, 2025**](https://www.healthcareittoday.com/2025/03/22/weekly-roundup-march-22-2025/) | [[Healthcare IT Today]] | | 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]] | | 3/6/2025 | [**#aiinhealthcare #digitalhealth #smarthospitals #healthcareinnovation… - Hatim Khan**](https://www.linkedin.com/posts/hatim-khan-global-growth_aiinhealthcare-digitalhealth-smarthospitals-activity-7303122748128550913-2mOk) | [[Linkedin]] | | 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]] | | 1/30/2025 | [**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]] | | 1/29/2025 | [**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]] | | 1/29/2025 | [**The Evolution Of Proof Of Human Uniqueness: Building Trust In AI Age**](https://www.forbes.com/sites/taarinikaurdang/2025/01/29/the-evolution-of-proof-of-human-uniqueness-building-trust-in-ai-age/) | [[Forbes]] | | 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]] | | 12/27/2024 | [**Middle East Healthcare Transformation Fuels New Opportunities for Technology Developers ...**](https://finance.yahoo.com/news/middle-east-healthcare-transformation-fuels-130000345.html) | [[Yahoo Finance]] | | 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]] | | 12/12/2024 | [**Health IT Business News - December 12, 2024**](https://www.healthitanswers.net/health-it-business-news-december-12-2024/) | [[Health IT Answers]] | | 7/17/2024 | [**Data Privacy in Healthcare: Balancing Innovation with Patient Security**](https://www.healthcareittoday.com/2024/07/17/data-privacy-in-healthcare-balancing-innovation-with-patient-security/) | [[Healthcare IT Today]] | ## Topic Overview (Some LLM-derived content — please confirm with above primary sources) ### Key Players - **Trustworthy and Responsible AI Network (TRAIN)**: A consortium aimed at promoting safe and effective adoption of AI in various sectors, including healthcare, by fostering collaboration among stakeholders. - **UC San Diego Health**: Implemented policies to enhance transparency in AI usage, emphasizing the importance of trust in AI-assisted communication. - **ECRI**: An organization that provides guidance on healthcare technology hazards, including AI. - **Cognome**: A company offering ethical AI tools developed in collaboration with leading academic healthcare systems. - **Traliant**: A company offering compliance training focused on AI ethics and HIPAA regulations. - **Royal Philips**: Collaborating with Mayo Clinic to enhance cardiac MRI exams using AI. - **FDA**: The U.S. Food and Drug Administration, responsible for regulating medical devices and ensuring the safety and effectiveness of AI technologies in healthcare. - **Counterpart Health**: Deploying AI technology to enhance decision support for primary care physicians. - **Censinet**: A company focused on ensuring the security and compliance of AI technologies in healthcare. - **Hyro**: A leading platform for AI-powered solutions in healthcare, focusing on responsible voice and chat AI agents. - **PointClickCare**: A provider of healthcare IT solutions focusing on building trustworthy AI models that are transparent and validated. - **Netsmart**: A provider of healthcare IT solutions that emphasizes responsible AI use to improve clinical outcomes. - **Mass General Brigham**: A leading healthcare institution adopting AI to enhance patient care and clinician efficiency. - **Microsoft**: A technology company collaborating with healthcare institutions to improve AI applications in medical imaging. - **Microsoft Research**: Partnering with Mayo Clinic to integrate AI in radiology for improved diagnostic accuracy and clinician workflows. - **Andy Ball**: Chief Executive at Cedars-Sinai Beverly Hills ASC Venture, emphasizes responsible AI use to optimize healthcare delivery. - **Synergist Technology**: A technology company providing advanced AI security tools, collaborating with PCG to enhance AI compliance frameworks. - **Jennifer Stoll**: Chief External Affairs Officer at OCHIN, involved in promoting responsible AI practices in healthcare. - **TruBridge, Inc.**: Integrated Microsoft Dragon Copilot into its EHR solution to enhance care delivery and operational efficiency, aligning with responsible AI practices. - **DeepHealth**: A subsidiary of RadNet focused on enhancing AI-powered health informatics solutions. ### Partnerships and Collaborations - **TRAIN and Microsoft**: Collaboration to promote responsible AI practices in healthcare, focusing on ethical considerations and transparency. - **Stanford Biodesign and TTIC**: Partnership emphasizing the importance of trustworthy AI and governance in healthcare innovations. - **Cognome and NJII**: A strategic partnership aimed at enhancing patient care through AI and machine learning solutions, focusing on trustworthiness and transparency. - **ALIGNMT AI and HFMA**: Launching a micro-credentialing program to enhance AI governance skills among healthcare professionals. - **Hyro and Healthier Capital**: Funding to enhance AI solutions addressing patient expectations and resource constraints. - **NTU Singapore and NHG**: Launch of the Centre of AI in Medicine to integrate AI technologies into healthcare. - **PCG and Synergist Technology**: A strategic partnership aimed at enhancing AI governance and compliance solutions. - **Royal Philips and Mayo Clinic**: Utilizing AI to shorten cardiac MRI exams and improve patient experiences. - **Kipu Health and AWS**: Partnership to create AI tools for improving clinical workflows in behavioral health. - **Microsoft and Mass General Brigham**: Collaborating to enhance the use of generative AI in medical imaging. - **Mayo Clinic and Microsoft Research**: Developing AI models that integrate text and images in radiology to streamline clinician workflows. - **Ketryx and DeepHealth**: Partnering to improve AI-powered health informatics solutions. - **Viz.ai and Microsoft**: Partnership to integrate AI diagnostic imaging models into clinical workflows, enhancing care coordination. - **OpenNotes and Abridge**: Collaborating to develop AI-powered clinical documentation tools to enhance patient-clinician communication. - **Commure and Tenet Healthcare**: Implementing Commure's ambient AI platform to improve clinician efficiency and patient care. - **HEALWELL and Mutuo Health Solutions**: Acquisition to enhance AI-driven healthcare technologies, focusing on clinical efficiency. - **Ellipsis Health and Ceras Health**: Collaboration to provide real-time severity scores for mental health conditions using AI. - **Aspira Women's Health and ARPA-H**: Funding for developing AI-driven diagnostics for endometriosis. - **Centific and Premier, Inc.**: National group purchasing agreement for AI chatbots and scribes, aimed at improving patient experiences and reducing physician burnout. ### Innovations, Trends, and Initiatives - **AI in Mental Health**: Research indicates that attachment styles influence trust in AI counseling tools, with higher trust correlating to increased adoption rates. - **HITRUST Framework**: A framework that healthcare organizations can adopt to build trust in AI through ethical implementation and transparency. - **Trustworthy Responsible AI Network (TRAIN)**: Established to promote responsible AI practices in healthcare, focusing on underserved communities. - **EU AI Act**: A regulatory framework aimed at ensuring ethical AI deployment in healthcare. - **Philips' Human-Centered AI Approach**: Focuses on ensuring AI enhances healthcare professionals' capabilities while adhering to ethical principles. - **HHS Strategic Plan**: Outlines goals for trustworthy AI development, external validation, and enhancing healthcare delivery. - **Healthcare Agentic AI**: A modular framework for AI agents in healthcare that enhances patient care through perception, cognition, interaction, coordination, learning, and trust. - **AI-Driven Automation**: Healthcare organizations are increasingly adopting AI to streamline workflows and improve operational efficiency amid workforce shortages. - **Generative AI**: Has the potential to reduce clinician workloads significantly, but raises ethical concerns regarding data security and algorithmic bias. - **Kipu's AI Innovation Program (KIP)**: Utilizes AWS's AI services to create ethical AI solutions for behavioral health. - **AI in Diagnostics**: AI platforms like Google's DeepMind are redefining diagnostics by improving disease detection and treatment personalization. - **AI in Healthcare**: AI is expected to enhance predictive analytics, personalized medicine, and clinical decision support by 2025. - **Ambient AI Technologies**: Gaining traction for reducing administrative tasks and improving clinician-patient interactions. - **AI in Clinical Documentation**: Health systems are implementing AI tools to alleviate physician burnout and improve patient interactions. - **Generative AI Tools**: Being integrated into clinical settings to reduce administrative burdens and enhance patient care. - **Generative AI in Healthcare**: Emerging as a transformative technology for enhancing diagnostic accuracy and operational efficiencies. - **Responsible AI-Powered Communications Platform**: Hyro's platform designed to automate patient interactions while ensuring compliance and security. - **AI in Clinical Trials**: Lindus Health's platform aims to streamline clinical trials, making them faster and more efficient. - **Health Bank One**: A digital health bank allowing patients to manage their medical records and utilize AI for personalized health insights. ### Challenges and Concerns - **Trust in AI**: A major concern in healthcare, with 60% of healthcare respondents citing risk concerns as a challenge to AI adoption. - **Transparency and Trust**: The need for transparency in AI-generated communications to maintain trust between patients and providers, highlighted by California's law requiring disclosure of AI usage. - **Trust in AI Solutions**: Healthcare providers express skepticism about unverified AI technologies, emphasizing the need for clinical validation. - **Interoperability and Reliability**: The need for standards and interoperability in AI systems to ensure trust and effectiveness. - **Ethical Considerations**: The need for ethical AI development and transparency is critical to maintaining trust in AI applications. - **Consumer Trust**: Concerns about the use of personal health data for AI analysis may undermine consumer trust. - **Trust in AI Models**: Importance of local validation and representative data to ensure AI tools meet the specific health needs of diverse populations. - **Data Privacy**: Concerns regarding the protection of sensitive patient information in the context of AI adoption. - **Ethical Implementation**: The challenge of balancing rapid AI innovation with ethical oversight to prevent biases and ensure equitable benefits across demographic groups. - **Regulatory Oversight**: Lack of regulatory frameworks raises concerns about patient safety and the reliability of AI algorithms. - **Algorithmic Bias**: AI models can reinforce existing healthcare disparities, complicating trust and accountability. - **Cybersecurity Threats**: Increased risks from cyberattacks necessitating robust security measures for AI systems. - **Cybersecurity Risks**: Rapid AI adoption raises concerns about increased cybersecurity threats and the need for robust governance structures. - **Regulatory Uncertainty**: Challenges in navigating the regulatory landscape for AI technologies in healthcare. - **Ethical Concerns**: Issues related to privacy and algorithmic bias in AI applications across healthcare. - **Data Bias and Privacy**: AI deployment risks include data bias leading to inequitable care and privacy concerns regarding personal data. - **Regulatory Compliance**: Organizations must navigate evolving AI regulations to ensure compliance and security. - **Implementation Hurdles**: Healthcare organizations face challenges in AI adoption, including legacy system integration and data quality issues. - **Algorithm Bias**: The potential for biases in AI algorithms that could affect patient care and outcomes. ## Related Topics [[Ethical AI]]; [[Ethical Use of AI]]; [[Skepticism Towards AI]]; [[Ethical Considerations in AI]]; [[Ethical Concerns with AI]]; [[Responsible AI]]; [[Ethical Implications of AI]]; [[Ethical Concerns in AI]]; [[Clinical AI]]