Oni Blackstock, MD, MHS’ Post

Addressing race bias in AI through race-conscious algorithms is a complex issue. While important for promoting fairness, these algorithms must consider potential consequences. On one hand, race-conscious algorithms can address biases and promote equal opportunities in various domains, including healthcare. However, they may inadvertently perpetuate harm and widen health disparities. Focusing solely on race risks oversimplification and reinforcing stereotypes. Striking a balance is crucial, considering multiple dimensions of identity, such as socioeconomic status and education, in addition to race. By adopting a comprehensive approach, we can develop fair and inclusive AI systems that minimize harm and promote equitable health outcomes. #responsibleAI #healthequity #regulatoryaffairs #safeAI #equitableAI #healthinnovation #medicaladvancements #transparentAI Coalition for Health AI (CHAI) for Health AI (CHAI)

🌟 The Future of AI in Healthcare: Promise, Peril, and Progress 🌟 Had the privilege of attending an insightful talk by Laura Adams, Senior Advisor at the National Academy of Medicine (NAM), hosted by the Harvard T.H. Chan School of Public Health AI in Healthcare Student Organization. The discussion focused on the evolving landscape of AI in healthcare, its incredible potential, and the challenges we must navigate. Key Takeaways: Predictive AI: AI can forecast disease outbreaks, hospital readmission rates, and public health trends, allowing for more precise and timely interventions. Generative AI: Helping reduce clinician burnout by automating administrative tasks and enabling innovative patient communication through dynamic AI-generated content. Behavioral AI: Emerging applications like micro-expression analysis and voice AI are revolutionizing mental health care, detecting early signs of depression and Alzheimer’s. Ethical Challenges: Equity and data bias remain major concerns. Ensuring diverse datasets and transparency is crucial to prevent AI from perpetuating healthcare disparities. Trust and Collaboration: Building trust with communities and including diverse voices in the development of AI systems is essential for long-term success. AI holds immense promise, but we must remain diligent in addressing ethical concerns and ensuring human connection remains at the heart of healthcare. A big thank you to: Laura Adams, Maya Punjwani and Harvard T.H. Chan School of Public Health AI in Healthcare Student Organization for this engaging session! #AIinHealthcare #HealthcareInnovation #PredictiveAI #GenerativeAI #EthicalAI #BehavioralAI, #DigitalHealth, #AIFuture, #MedicalAI, #HealthTech, #EthicalAI, #InnovationInHealthcare, #HealthcareRevolution, and #AIandHealthcare

AI is not just a tech innovation. It’s a catalyst for reshaping foundational aspects of our lives, like housing and health. This post highlights how researchers are using AI to uncover hidden insights from patient records, helping us address challenges like housing instability before they escalate. Imagine the potential: targeted interventions, smarter resource allocation, and healthier communities built on the stability of a home. It’s inspiring to see technology being leveraged for such transformative work.

AI is reshaping how we understand and address social determinants of health. Researchers at the University of Illinois Cancer Center and University of Illinois Chicago are using AI to identify critical factors—like housing instability or transportation barriers—hidden within patient records. These insights help personalize care and improve outcomes. For housing, this technology could be transformative. By identifying trends in housing stability at scale, we can proactively address risks, allocate resources more effectively, and create stronger foundations for health and well-being. Stable housing isn’t just a need—it’s the cornerstone of healthier communities. How do you see AI driving change in housing and beyond? https://lnkd.in/eWHRPecE

The transformative potential of AI in healthcare is undeniable. From personalized treatment plans to early diagnosis, AI has revolutionized how we approach care. But with great power comes great responsibility. Ensuring that AI serves everyone equitably—minimizing bias and promoting fairness—is not just a technical challenge; it’s a moral imperative. One real-world example of AI addressing inequities is its role in 𝗱𝗶𝗮𝗯𝗲𝘁𝗶𝗰 𝗿𝗲𝘁𝗶𝗻𝗼𝗽𝗮𝘁𝗵𝘆 𝘀𝗰𝗿𝗲𝗲𝗻𝗶𝗻𝗴. In regions with limited access to ophthalmologists, AI-powered tools like Google Health’s algorithms have helped screen thousands of patients, detecting early signs of vision loss. This has made a critical difference in rural and underserved communities. Another example is 𝗣𝘂𝗹𝘀𝗲 𝗼𝘅𝗶𝗺𝗲𝘁𝗲𝗿𝘀, which historically struggled to deliver accurate readings for individuals with darker skin tones due to biased data in their development. Now, AI is being applied to recalibrate these devices to provide fair and accurate results across diverse populations. However, we’ve also seen what happens when biases in AI go unchecked. Algorithms used in predicting healthcare costs have, in some cases, disadvantaged Black patients, reflecting systemic inequities. Tackling these issues requires an intentional focus on diverse datasets, transparent methodologies, and ongoing accountability. Ethical AI isn't just a checkbox—it's the backbone of building trust in the systems meant to care for us. By prioritizing equity, healthcare professionals and technologists can collaborate to close the gaps in care delivery and outcomes. Let’s keep pushing for innovation that uplifts all. #AIinHealthcare #EthicalAI #HealthEquity #ResponsibleInnovation #HealthcareTransformation

🌎 Hospital participation in medical AI. Representation matters 🌎 As AI-driven tools continue to reshape medical research and patient care, ensuring that the data used to train these systems is diverse and representative is crucial. Here’s why: 🟠 AI models are only as good as the data they’re trained on. When training data reflects the diversity of real-world patients – across age, gender, ethnicity, and socioeconomic groups – it is able to predict, diagnose and prioritize more accurately. 🟠 AI can perpetuate bias. Without diverse datasets, AI systems can perpetuate biases, leading to poorer outcomes for underrepresented groups. This is particularly concerning for marginalized communities, who already face significant barriers to quality healthcare.   🏥 Healthcare systems can play a part in ensuring their patients are represented. By enabling their patients’ data to be included in research in a secure and de-identified manner, healthcare systems can directly contribute to the development of technology that is safer and more effective for their patient populations. 🤝 How do we help? We offer healthcare systems and hospitals the opportunity to contribute de-identified data to help researchers worldwide, ensuring their data is used for good, and their patients are at the heart of new AI developments. Learn more about becoming a data partner: https://lnkd.in/etc6yvQ2 #HealthcareAI #Data #AIForGood 

🌟 Exciting Opportunity! 🌟 The AIM-AHEAD 2024 Call for Proposals. This year, "Innovation for Equity in Low-Resource Settings," encourages cross partnerships with Federally Qualified Health Centers (FQHCs) and Community Health Centers (CHCs) in Medically Underserved Areas (MUAs) to develop AI/ML solutions that address health disparities in cancer, cardiometabolic, and mental/behavioral health. 🏥💡 👉 What’s this about? This initiative champions the development of AI/ML tools through cooperative research, targeting tech advancements for communities often overlooked. By nurturing partnerships that commit to community-engaged design and uphold ethical standards, they aim to boost healthcare accessibility and equity. 📢 Who can apply? Eligibility requires forming a cross-organizational partnership that includes at least one CHC. This call is open to a wide array of institutions—higher education, nonprofits, and for-profits—especially those prepared to collaborate with CHCs. Applications are encouraged to co-design and trial AI/ML interventions informed by and beneficial to the communities. 🤝 Collaborate with CHCs to drive changes in health equity. #AIMAHEAD #HealthTech #CommunityHealth #NACHC #AI #CommunityHealthCenters #CHC #DigitalHealth #HealthcareInnovation #SocialImpact #TechQuity Discover more->

🚀 Hey everyone! We’re back with some truly mind-boggling tech facts that push the boundaries of what’s possible! 💡 Did you know? Researchers at Stanford University have achieved something remarkable. They’ve developed a cutting-edge machine learning algorithm that can predict the likelihood of death with a staggering 90% accuracy. 🧠💻 🔍 How does it work? This groundbreaking algorithm analyzes vast amounts of patient data, identifying patterns and signals that even the most experienced doctors might miss. By leveraging the power of AI, it can provide incredibly accurate predictions, offering new insights into patient care and decision-making. 🌐 What does this mean for the future? This innovation is more than just a technological marvel—it’s a glimpse into the future of healthcare. Imagine a world where doctors can make more informed decisions, anticipate critical health events, and personalize treatments like never before. The potential to save lives and improve health outcomes is immense. 🚀 The Future of Medicine As AI continues to advance, we’re entering an era where technology and medicine intertwine in unprecedented ways. The Stanford algorithm is just the beginning, paving the way for more innovations that will redefine healthcare as we know it. #MachineLearning #HealthTech #StanfordUniversity #MedicalInnovation #HealthcareAI #TechInMedicine #FutureOfHealthcare #PredictiveAnalytics #MedTech #ArtificialIntelligence #MedicalBreakthrough #HealthInnovation #DigitalHealth #AIInMedicine #SmartHealthcare #HealthTechRevolution #AIAlgorithms #PatientCare #HealthcareRevolution #MedicalAI #AIandHealth #HealthcareInnovation #TechInHealth #MedicalTechnology #HealthPredictiveAnalytics #AIForGood #AIHealthcare #MedicalAdvancements #AIImpact #TechForHealth #FutureOfMedicine #HealthcareTech #AIinMedicine #StanfordResearch #HealthTechInnovation #PredictiveMedicine #MedicalAIInnovation #AIinAction #HealthcareTransformation #AIinHealthcare2024 #HealthTechTrends #AIinResearch #MedicalAIResearch #AIinMedicalField #HealthcareFuture #TechAndHealth #DigitalMedicine #AIInnovation #USITStaffing #ITRecruitment #BenchSales #TechStaffing #ITJobs #USRecruitment #TechTalent #StaffingSolutions #RecruitmentAgency #TalentAcquisition #TechCareers #ITConsulting #BenchSalesExperts #StaffingAgency #TechRecruitment #USITJobs #TalentSourcing #RecruitmentExperts #ITBenchSales #JobPlacement #ITStaffingSolutions #RecruitmentStrategy #TechHiring #ITProfessionals #StaffingServices #BenchSalesSpecialist #StaffingConsultants #TechResourcing #JobOpportunities #BenchSalesConsulting #RecruitmentPartners #ITJobPlacement #USITConsultants #TechTalentAcquisition #ITHiring #StaffingExperts #ITRecruiters #BenchSalesStrategy #TalentPipeline #USITSolutions #StaffingIndustry #TechPlacement #RecruitmentServices #ITBenchSalesExperts Ravindranath Konda Saini Vinod Shiva Kumar ✪ Harideep Reddy✔️ Nagarjuna G Sairaj Bandari Riya Khan Leenath Mandava Sreenath Kota Varsha Katkam Sri Ranga

After two years of AI hype, major questions about its use in healthcare remain unanswered, like how it has impacted health equity. At the 2024 AAMI eXchange, Erin Sparnon addressed how AI can improve HTM, where it falls short, and what humans need to do to use these tools effectively and ethically. #artificialintelligence #medicaldevices #healthequity https://lnkd.in/e_-6a6bT

🌟 New White Paper 🌟 How do caregivers view generative AI tools, and how are they shaping their role in their children’s lives? foundry10's new white paper, in collaboration with the STAR Lab and other collaborators at UC Irvine, fills this gap by exploring caregivers’ perceptions and expectations for AI’s future in family life. We examine how caregivers communicate about AI—what they share, the concerns they raise, and how they frame its potential and risks. Using these insights, we provide evidence-based recommendations and practical strategies to help families navigate AI responsibly. 📌 Key Findings at a Glance: 🔹 Educational Potential & Concerns: While some caregivers are optimistic about AI enhancing learning, they worry about its impact on critical thinking, academic integrity, and social development. 🔹 Best Ages for AI Conversations: Most caregivers feel ages 10–12 are the ideal time to introduce generative AI, leveraging adolescents' growing critical thinking and ethical reasoning skills. 🔹 Youth and AI: With AI increasingly integrated into education and online spaces, families are navigating new challenges around over-reliance, misinformation, and ethics. 👉 Download the full report here: https://lnkd.in/g_RC2dRj We’d love to hear your thoughts—how do you see AI shaping family life and education? A special thanks to the Jacobs Foundation and the National Science Foundation (NSF) for their continued support on this research. #AI #AIeducation #technology #families #research #foundry10 #UCI #chatgpt