Matt Abrams

🎙️ New Episode Alert! 🎙️ Navigating the AI hype cycle can be a challenge, especially in the public sector. On this episode of Human Signals, we sit down with Jason Frame, Chief Information Officer of the Southern Nevada Health District, to discuss his unique perspective on AI implementation in public health. Jason shares his firsthand experience tackling the tech landscape during the COVID-19 pandemic, the importance of finding the right use cases for AI, and his vision for a future where technology enhances both customer and employee experiences. 🎧 Tune in to hear Jason's insights on: - Balancing public safety and service delivery during COVID-19 🦠 - Addressing the digital divide and serving marginalized communities 🏥 - The need for tangible ROI to justify AI adoption 📈 - Using AI to improve back-office processes and employee experience ⚙️ - Shifting the conversation from talking tech to focusing on experience 🗣️ ➡️ Listen now: https://lnkd.in/gJRFuid4 #AI #publichealth #CX #podcast #technology #innovation #CCW2024 #BusinessInnovation #FutureOfWork #TechEthics #CustomerExperience #CustomerSupport #EthicalAI #CCW

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The Coalition for Health AI (CHAI) has released a draft framework for responsible #AI in #healthcare, open for a 60-day public review. Key Points: ▶ Framework - Includes standards guide and checklists for safe, secure, and equitable AI use. ▶ Purpose - Ensures AI benefits all populations, including underserved communities. ▶ Alignment - Based on guidelines from the National Academy of Medicine and The White House. #PublicHealth #Innovation #HealthEquity

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The recent release (August 14, 2024) of the Congressional Research Service report, "Oversight of Laboratory Biosafety and Biosecurity: Current Policies and Options for Congress" (https://lnkd.in/eY4z3U-v), highlights concerns that #artificialintelligence (AI) could be repurposed or misused in biological design, raising significant biosafety and biosecurity issues. Similarly, RAND has discussed the U.S. Department of Homeland Security proposed collaborative, whole-of-government strategy for developing and adopting AI initiatives, as outlined in their "2024 Artificial Intelligence (AI) Roadmap" (https://lnkd.in/eJQs9Xe2). Both CRS and RAND emphasize that the rapid pace of AI development and integration is fueling growing concerns around "cultural, ethical, and privacy issues." 📢 While the potential of AI #technology is vast, there’s a critical need to understand the 2nd and 3rd order impacts through modeling & simulation (M&S), and rigorous testing. By embracing AI responsibly, DHS and other federal organizations can not only drive innovation but also address the social concerns that these transformative technologies may bring like United States Department of Defense investing in data and AI structure outlined in their "DOD #Innovation Fact Sheet" ( https://lnkd.in/eJC7FtMq )

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For GenAI enthusiasts: How to Build AI Agents with LlamaIndex, MongoDB, and Claude 3.5 Sonnet. https://lnkd.in/gwcfbadD

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The #AI roadmap is a strategic plan to advance artificial intelligence research and development in the United States. It includes key initiatives like authorizing and funding the National AI Research Resource (NAIRR) to provide researchers with access to advanced tools and data. The roadmap aims to empower new AI leaders, expand opportunities beyond tech hubs, and maintain America's leadership in scientific development. Lawmakers emphasize the need for legislation to ensure its full implementation and funding, highlighting the roadmap's support for innovation and the potential to position the U.S. at the forefront of AI advancements.

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🤓 𝗟𝗲𝘁'𝘀 𝗴𝗲𝘁 𝗻𝗲𝗿𝗱𝘆! Take a look at this Amazon Web Services (AWS) blog about "Project Heal" – an AI-powered toolkit designed for the early detection and mitigation of medical misinformation. The blog does an excellent job of explaining some the technical components of the system. Here are some highlights: 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗻𝗴 𝗮𝗻𝗱 𝗖𝗹𝗮𝘀𝘀𝗶𝗳𝘆𝗶𝗻𝗴 𝗠𝗶𝘀𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻 “One of the key functionalities of Project Heal will be the ability to classify and detect emerging misinformation before it has an opportunity to proliferate.” “Ingested information will be evaluated using trained ML models, enabling the tool to classify the likelihood of a statement having misleading content and allowing for categorization based on the statement’s entities and context.” “Misleading statements will then be evaluated by a subsystem to help score the severity of the threat to human health.” “The detection engine will be built using graph neural networks, which will be supported by a large, scalable, fully managed graph database (Amazon Neptune). Amazon Comprehend will be used to support keyword and entity extraction from content.” “A human feedback loop will consistently audit and improve the model using Amazon Augmented AI (Amazon A2I).” “Both detection and scoring will be supported by Amazon SageMaker, a fully managed service to prepare data and build, train, and deploy ML models for any use.” “Additionally, generative AI will support the summarization and grouping of related misinformation content.” 𝗣𝗲𝗿𝘀𝗼𝗻𝗮𝗹𝗶𝘇𝗲𝗱 𝗖𝗼𝘂𝗻𝘁𝗲𝗿 𝗠𝗲𝘀𝘀𝗮𝗴𝗶𝗻𝗴 “One of the most innovative features of Project Heal will be the platform’s ability to generate tailored communication responses to misleading information.” “To achieve this, Project Heal will use generative AI foundation models (FMs) through Amazon Bedrock, such as Amazon Titan.” “Supporting evidence, built from trusted sources of information, will be available to users via Retrieval-Augmented Generation (RAG), an approach that reduces some of the shortcomings of large language model (LLM)-based queries.” “Through this technique, Amazon Bedrock is able to generate more personalized messaging by combining trusted information and user preferences.” 𝗧𝗵𝗲 𝗕𝗼𝘁𝘁𝗼𝗺 𝗟𝗶𝗻𝗲 This project illustrates the complexity of developing AI-driven solutions and the importance of integrating them thoughtfully to tackle real-world challenges such as medical misinformation. 🙂 With these insights, I hope I’ve satisfied your nerdy needs! https://lnkd.in/e3gzR7XG

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In a new post on the ALI Insights blog, Sara Schapiro is joined by Kate Tromble of the Data Quality Campaign to explain how the NEED Act would modernize Statewide Longitudinal Data Systems. Better data ➡ better outcomes for kids! https://lnkd.in/eP5G3znk

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Thanks to #genai360 for the shoutout here for Consilience AI and our AlphaIQ product. Davit Buniatyan Joseph Byrum, Ph.D., MBA

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As we face increasing global challenges, the intersection of AI in agriculture and defense security has never been more critical. By leveraging AI technologies, we can significantly enhance food production, ensuring food security for populations while simultaneously bolstering national defense strategies. AI is revolutionizing agriculture through: - Smart Irrigation Systems: Optimizing water use and improving crop yields. - Rapid Disease Diagnosis: Allowing for timely interventions that reduce crop failure and spoilage. - Data-Driven Insights: Helping farmers make informed decisions based on soil quality, climate conditions, and market demands. These advancements not only contribute to sustainable agriculture but also play a vital role in national security. A stable food supply reduces vulnerability to external threats and enhances resilience against crises. As we innovate in agricultural practices, let’s remember that food security is a cornerstone of defense security. Together, we can cultivate a more secure future! 🌱✨ #AI #Agriculture #FoodSecurity #Defense #Sustainability #Innovation

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5 questions with Marcello Cacciato (Metyis) on bringing Generative AI to life Marcello Cacciato, Director in the Data Science practice of Metyis, is an expert Generative AI, having advised multiple organisations on the development and implementation of their Generative AI stra https://lnkd.in/efSSGj3g to-life

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Elevating data quality in accumulation modeling is paramount for #cyber CAT modeling advancement. In part 3 of our cyber #knowledge series Timothy Marshall and Stephan Brunner call for enhanced exposure #data for improved cyber #accumulation modeling: https://ow.ly/2sc250REcmO #Insurance

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AI has the potential to dramatically impact historically underserved communities by improving healthcare access, providing educational resources, and transforming daily life. But transforming potential into reality takes experimentation, resources, exemplars, and communities of shared practice. The new Artificial Intelligence to Accelerate Inclusion Challenge, spearheaded by the Mastercard Center for Inclusive Growth and data.org, creates a powerful new opportunity to build and test these solutions at scale. Offering grant funding, technical expertise, and mentorship to organizations using AI for public good, this initiative supports the development of technologies that address unique challenges in these communities. The result: a more equitable tech landscape and real solutions that affect daily lives. Vilas Dhar will support this initiative as a judge, alongside a global team of visionaries and thought leaders. Read more about - and register for - the Artificial Intelligence to Accelerate Inclusion Challenge here: https://lnkd.in/eRaGep3e #AIDrivesImpact #InclusiveGrowth Vilas Dhar Raghu Dharmaraju Ivana Feldfeber Angela Oduor Lungati Anna Makanju Alondra Nelson Neera Nundy Navrina Singh Uyi (O.T.) Stewart Greg Ulrich Shamina Singh Jennifer Hauseman Danil Mikhailov Lindsey Gottschalk Jessica Jeng Emma Marty

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Another journal post from our Directors of AI & Data Emily L. Leventhal Michael Yao Lawrence Huang. This week’s post documents the types of bias that can exist in the EHR. These are important to consider when building algorithms with EHR data. Link: https://lnkd.in/g_jssZ5T TL;DR: Electronic health records (EHR) provide huge amounts of data to train AI and gain clinical insights. However, because they were originally intended for solely administrative use, they can be a poor source of data to gain real world information (RWE). This article provides an overview of the potential biases from EHR that limit the true causal relationships that can be determined from EHR. This can serve as a guide for considerations when building algorithms based off of EHR. Below are some interesting types of bias that can arise: - Berkson Bias: Patients with more than one condition are more likely to be hospitalized, which leads to the spurious correlation between diseases. - Informed Presence Bias: Healthier individuals are less likely to seek care. Under-reported diseases are more likely to be documented in those with other conditions because they are more closely monitored. - Immortal Time Bias: Bias from the time between study entry and exposure assignment requires participants to stay “immortal” or outcome-free until exposure/treatment assignment What other biases can arise? How can we mitigate these biases?

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In the recent PennAITech Collaboratory webinar, ""Accelerating Regional Readiness for Aging: Exploring Healthspan Innovation Hubs,"" George Demiris of the Penn Artificial Intelligence and Technology Collaboratory for Healthy Aging introduced speakers Brendan McEntee of MITRE Ingenuity and Meredith Benedict of the MITRE Corporation. McEntee and Benedict explored innovative approaches to enhancing the quality of life for aging populations through the development of Healthspan Innovation Hubs. The presentation detailed how these hubs aim to create ecosystems tailored to regional needs, facilitating collaborations that address the challenges posed by a rapidly aging society. They discussed the potential of these hubs to integrate technology and policy for underserved populations and the role of various stakeholders in achieving scalable solutions. Key takeaways included the importance of multi-sectoral collaboration and the ongoing need for strategic investment to meet the demands of the aging demographic. #ai #aging #healthyaging #geriatrics #ml #olderadults #pennaitechwebinar cc: The Penn AI and Tech Collaboratory for Healthy Aging University of Pennsylvania University of Pennsylvania School of NursingThe Penn AI and Tech Collaboratory for Healthy AgingtUniversity of Pennsylvania

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🔍 A recent publication in Nature explores the expanding role of large language models (LLMs) in healthcare, highlighting their potential to transform medical data analytics and decision-making processes. Despite these advancements, the study also underscores persistent challenges related to fairness, bias, and misinformation within the sector. 🏥 As the pace of AI innovation accelerates, led by developments like ChatGPT, the sector struggles with regulatory lag. Organizations such as the Coalition for Health AI (CHAI) and the Trustworthy & Responsible AI Network (TRAIN) are spearheading efforts to establish robust ethical frameworks to guide the responsible deployment of AI technologies in healthcare. #HealthcareAI #EthicalAI #MedicalInnovation #AIethics #TechnologyInHealthcare

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🌐 We've talked a lot about real-time intelligence requiring a #software-first mindset, but what does this mean in context? How is #AI fundamentally transforming the #geospatialintelligence industry? Get the primer on the shift to space-based #intelligence and why it's crucial for your organization to not just act fast, but first: https://lnkd.in/e7ViVUxS #spacebasedintelligence #artificialintelligence #GEOINT

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Check out this May 14 Webinar >> Complex #AI Agents — Use #GenAI to Automate Complex Tasks. Register now at: https://lnkd.in/eDiR5D5H -- presented by @Abacus.AI Join Abacus in this engaging 2-hour webinar on how to use advanced AI agents to automate and revolutionize your business operations. With the help of @Abacus.AI, you can develop agents capable of automating intricate tasks. These agents will formulate a strategy, which you can implement upon approval. These state-of-the-art AI Agents are designed with a planning feature that allows you to: 🟣Streamline complex business workflows: automate both routine and intricate business tasks. 🟣Achieve seamless integration and communication with other enterprise systems. 🟣Enhance automation across various departments including customer support, marketing, technical support, IT, sales, and content creation. Participants in any of the demonstrations will receive certificates. 🟣🟣🟣🟣 #GenerativeAI #DeepLearning #MachineLearning #LLMs #DataScience #DigitalTransformation #CDO #CTO

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