Jane Sarasohn-Kahn’s Post

Excellent piece by friend, trend weaver, and health economist, Jane Sarasohn-Kahn, on the importance of "trust" as the foundation for a framework on health equity. As Jane points out, this is especially important for vulnerable health care populations. Jane outlines the key issues of how the use of AI in healthcare can address health equity issues and the risks if we do not focus on this as a critical piece of the AI puzzle. As the Federation of American Scientist essay, Improving Health Equity Through AI, states, "AI has the potential to revolutionize healthcare, but its misuse and unequal access can lead to unintended dire consequences. For instance, algorithms may inadvertently favor certain demographic groups, allocating resources disproportionately and deepening disparities." Jane highlights in her piece that "[t]he FAS notes that the Medicare and Medicaid programs in the U.S. cover about 40% of Americans [in West Virginia, in Appalachia, and other rural areas in the U.S. that number rises to 70%+] and therefor have the opportunity to design and scale responsible AI to patients in these plans." As we all continue to confront what AI means professionally and personally, I was not surprised to see that the Federation of American Scientists is now focusing attention on the impact of AI. As I continue to read, learn, and use AI -- this is an atomic bomb moment that deserves thoughtful attention consistent with the Federation of American Scientists' mission of working toward a safer, more equitable, and more peaceful world. #healthequity #AI

What does it take to unleash #AI in the NHS? Expert Robin Carpenter assesses strengths and weaknesses ahead of #Digital Health's AI and Data event next week in London. 🇬🇧 🤓 💻 🏥 Aida Kundrotaite Dillan Yogendra Guido Gebhardt #digitalhealth #UK #artificialintelligence #data #healthcare #AIDATA2023

A huge thank you to Women In Bio - Engage. Educate. Empower. , GirlUp Entrepreneurs, and Sage Bionetworks for hosting such an engaging and thought provoking conversation on the future of Generative AI and Healthcare. Here were a couple of key takeaways that got me thinking about potential impacts to our clients, and how we can better protect them against some of the challenges GenAI poses to the industry: Consent, Consent, Consent: In the traditional healthcare model, a patient is informed of their prospective treatment plan, or a participant is given informed consent protocols in a clinical trial setting. With the addition of AI, questions such as whether a patient should be informed that their treatment plan was derived using machine learning arise. If they should be informed, then how can the complexities of AI be explained in a clear and concise way across different demographics and generations? Can consent truly be obtained without clear understanding? This will have widespread implications for contractual risk transfer in the healthcare space. AI Regulation: The EU's Artificial Intelligence Act is set to be finalized in 2024, which is the newest in a string of acts such as the CCPA and GDPR to protect personal data and right to privacy, but will be the first to specifically address AI users and AI system providers. The act separates AI systems into risk level "buckets" and organizations should plan to evaluate the systems they use and develop an action plan based off of their risk categories, as similar regulation is likely to crop-up stateside in the near future. Our #RiskManagement resources are here to help you navigate these ever evolving issues through expert #ContractualReview, #GlobalInsuranceComplaince, and #LegalServices.

#AIInHealthcare comes with pros and cons. It offers significant potential for improving patient outcomes, enhancing the efficiency of healthcare system, and accelerating medical research. However, it also poses concerns over data privacy, the risk of #AI systems perpetuating existing biases, and the ethical implications of AI-assisted decision-making in healthcare. World Health Organization recommends regulating AI in healthcare and conduct mandatory independent audits on AI systems. Are these sufficient to mitigate the risks? Individuals need to do their part to have a healthier AI ecosystem in healthcare for a healthier population. #ethicalai #responsibleai #futureofai https://lnkd.in/gJERGCp3

The WHO has taken a pivotal step in guiding the ethical and responsible integration of AI in healthcare, particularly focusing on large multi-modal models (LMMs). Their recently released guidance underscores the importance of transparency, accountability, and inclusivity in AI systems to uphold patient autonomy and ensure equitable healthcare outcomes. Key aspects highlighted include the ethical use of AI, the potential of LMMs in diagnostics and research, and the need to balance benefits with risks such as data privacy and bias. The WHO emphasizes the role of governments in establishing regulatory frameworks and calls for independent audits and inclusive stakeholder engagement to address these challenges. As AI continues to reshape healthcare, how can stakeholders collaborate to ensure that AI technologies are leveraged ethically and responsibly for the betterment of global health? #AI #healthcare #who

Artificial intelligence is rapidly advancing, with large multi-modal models (LMMs) offering exciting new capabilities. On January 18th, 2024, The World Health Organization (WHO) released new recommendations on the ethics and governance of LMMs in healthcare. This guidance is a major starting point for anyone involved in healthcare AI and also an opportunity to proactively shape the future of this powerful technology. Here are my takeaways from the recent guidance: 📖 Show me the code! >> LMMs should be designed to explain their reasoning and decisions, fostering trust and understanding among healthcare professionals and patients. 🤝 Diversity is our superpower! >>Training data for LMMs must be diverse and representative to avoid perpetuating societal biases in algorithms. 🔏 Privacy ain't optional! >>Protecting patient data is vital, Robust safeguards should be in place. 🩺 AI Dream team for healthcare >> Multi-stakeholder engagement from Governments, tech companies, healthcare providers, and to patients is needed. #healthcareai #responsibleai #lmm #futureofmedicine

🩺Did you know? The WHO is redefining healthcare AI with new ethical guidelines. What are these guidelines about?🤔 💡The World Health Organization (WHO) recently issued new ethical guidelines focusing on AI in healthcare, especially large multi-modal models. The WHO initiative paves the way for more responsible and ethical use of AI technology to improve global health outcomes. Check out the complete here. 👇 And to stay updated with such revolutionary news in AI, don't forget to subscribe to our weekly newsletter. Get insights, news, and more right in your inbox! 👉 https://attri.ai/ #generatieveai #ethicalai #healthcare #llmops #didyouknow https://lnkd.in/eGeeYtgs

Ethical Issues Loom as Artificial Intelligence Shows Promise for Health Information Artificial intelligence (AI) holds plenty of potential in healthcare. The AI market is expected to grow at a compound annual growth rate of 36.4 percent from 2024 to 2030, according to Grand View Research. Clinical decision support, surgical assistance, personalized medicine, patient monitoring, and operations are just a handful of possible applications that healthcare professionals could embrace. At the same time, administrative uses, such as automated coding and other applications could benefit health information (HI) professionals. Click the link below to read the complete story.