John Larson

This California Management Review article explores the ROI of AI ethics and governance investments through two lenses: loss aversion and value generation. While many companies focus on minimizing risks like legal penalties and reputational harm, the article argues that a value generation approach—using ethics to build trust, foster innovation, and create competitive advantages—offers greater long-term benefits. By integrating ethics into strategic planning, organizations can both mitigate risks and enhance overall growth.

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A compelling read from McKinsey & Company on the importance of a robust infrastructure for integrating and launching AI. #ChartingthepathtodataandAI emphasizes the need for seamless integration and interoperability to drive AI initiatives. #MicrosoftAzureHealthDataServicesFHIR and #MicrosoftFabric serve as the pivotal platform for this endeavor. Explore more at the link: https://lnkd.in/dNhrDz5B.

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Kannan Raman of Amazon Web Services (AWS) sits down with Amar Drawid, Ph.D. to discuss the role of AI in transforming life sciences and the importance of data strategy being tied to business outcomes. They explore the challenges of data strategy, the importance of cultural shifts within organizations, and the monetization of data as a product.

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NEWS - Validation and Evaluation for Trustworthy Artificial Intelligence (VET AI) Act Introduced U.S. Senators John Hickenlooper and Shelley Moore Capito introduced the bipartisan Validation and Evaluation for Trustworthy Artificial Intelligence (VET AI) Act (details below). I'm excited about this bill because it builds on recommendations we--as the IEEE USA AI Policy committee--made in a position statement released last February (https://lnkd.in/e9sETwNM). It was a pleasure to co-lead this effort with Dr. Cari Miller. I'd also like to thank Sen. Hickenlooper's staff for being receptive to feedback that I, and colleagues, provided on this bill. Details: ➡ Directs NIST, in coordination with the Department of Energy and National Science Foundation, to develop voluntary specifications and guidelines for developers and deployers of AI systems to conduct internal assurance and work with third parties on external assurance regarding the verification and red-teaming of AI systems. ➡ Such specifications require considerations for data privacy protections, mitigations against potential harms to individuals from an AI system, dataset quality, and governance and communications processes of a developer or deployer throughout the AI systems’ development lifecycles. ➡ Establish a collaborative Advisory Committee to review and recommend criteria for individuals or organizations seeking to obtain certification of their ability to conduct internal or external assurance for AI systems. ➡ Require NIST to conduct a study examining various aspects of the ecosystem of AI assurance, including the current capabilities and methodologies used, facilities or resources needed, and overall market demand for internal and external AI assurance.

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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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In case you missed it.... We published a great H:F guest episode with Joel Portice, CEO of egnite - delving into the transformative role of data and AI in revolutionizing cardiovascular care. Joel shares his journey of leading five successful healthcare data companies, including the genesis and rapid growth of egnite, which was spun out from Edwards Life Sciences. egnite's flagship platform, Cardio Care, uses advanced analytics, machine learning, and AI to identify and manage cardiovascular patients, saving lives daily. This episode is a strong addition to our Heart Health Series on Health:Further. Please check it out: https://bit.ly/4fKmzCH

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The future of enterprise AI isn't generic chatbots - it's purpose-built, networked agents solving industry problems Real-world implementations of networked vertical AI applications are emerging across industries. Leading enterprises are already showing what's possible: Johnson & Johnson is accelerating chemical synthesis in drug discovery, Moody's is generating diverse research perspectives to enhance financial analysis, eBay is reimagining buyer-seller interactions through linked AI agents, and Cosentino is optimizing customer service by shifting human resources to higher-value tasks, as reported in the Wall Street Journal. These early moves underscore a crucial insight about enterprise AI adoption: success comes from building purposeful frameworks of custom tools that deliver immediate value while maintaining adaptability. This approach addresses both the rapid evolution of LLM capabilities and the pressing need for ROI justification. As these networked AI systems mature and companies gain implementation experience, they're positioned to fundamentally transform operational efficiency and establish new productivity benchmarks across sectors. The question isn't whether to pursue this strategy, but how quickly to scale it.

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Best practices in AI governance. Panel discussion by Keerthika Melissa Subramanian and Matt DeVoe. l Thank you to Keerthika Melissa Subramanian, partner at.Winston & Strawn LLP, and Matt DeVoe, Chief Information security officer at Zoetis, for sharing their insights and learnings with the students at the #CDAIO program at Executive Education at Carnegie Mellon University’s Heinz College. In a wide ranging discussion, these leaders shared their perspectives on - The need for AI governance - How to integrate AI governance into a broader digital and data risk management - Emerging AI regulations - Achieving the balance between unlocking value from innovation while minimizing risk - The ways to improve the legal.and compliance fluency of AI and Data leaders https://lnkd.in/eUWq83EY

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OpenAI is undergoing significant restructuring and internal changes related to status and sparking an exodus of high-profile executives. #datascience #AI #artificialintelligence https://hubs.li/Q02ShsZy0 If you enjoyed this post, follow me for more insights on AI and data science!

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Anthony Scriffignano, Ph.D., Thought leader in AI and seasoned data scientist on rapidly evolving landscape of artificial intelligence (AI)... "The situation gets more and more curious by the day. With the degree to which GenAI is now used in so many aspects of the production and synthesis of language, we can almost presume that somewhere in the stack of words there is machine generated output that was used as input. In addition to copyright, intellectual property, and just basic evolution of human creativity, we also have a darker side to consider that includes misinformation, disinformation, and introduction of bias" As AI-generated content grows, so does the potential for false or misleading information to proliferate. An efficient and reliable global site verification processes ensure that the sources we rely on are legitimate and credible, protecting businesses from harmful or inaccurate content. In a world where the boundaries between human and AI-driven information are increasingly blurred, site verification serves as a safeguard, providing vital trust in the digital ecosystem. Van Nguyen Putri Alysa Larasati Mohan Ramaswamy Kaushal Sampat Michelle C. Quynh Trang Dinh Trang V. Giulietta Sabrina Branduardi Rafi Puspa Sayekti Mai Ta Mutiara Nibras Sakinah Daylan Solidum Jeffri Shahul Hamid Blake Sitney Gurdip S. Sidhu Lamont Wilson Valerie Tan Astejada Kyaw Zin Thein Adha Faubya Fadya Syahira Saputra Indri A.

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Faster, more accurate, less data needed = BaseModel.AI

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🚀 Data and AI Growth Highlights in 2025: 📊 Data Explosion: Global data volumes are set to hit 181 zettabytes, driven by IoT and digital transformation. 💡 AI Market Boom: The AI market is projected to grow from $196B (2023) to $279B (2024) and can reach $3.68T by 2034, transforming industries with automation, predictive analytics, and real-time decision-making. 🌐 Data Science Growth: The data science market could surge to $178B by 2025, fueled by advanced #nocode platforms and tools managing complex pipelines. 🔍 Key Trends: • AI is reshaping workflows with hybrid models and real-time analytics. • Sustainable AI practices aim to minimize environmental impact. • Security and privacy challenges need ethical guardrails. The future is data-driven—are you ready to adapt ? 🌟 #AI #DataScience #DataPrivacy #DigitalTransformation #Innovation Salesforce Data Cloud ⛅️ Cloudely, Inc

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This is the bottom line, where the rubber meets the road… the shizzle. Stop thinking about what AI to buy, and start thinking about your organization- its values, its ethics. Whatever AI you decide to embrace has to first meet your values. I know it sounds strange, AI to meet your values, but that is what AI is supposed to be - the reflection of the humans who use it. Can’t do that? Don’t use AI. #ethicalAI #humancentered

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Take a look at this new paper about machine intelligence and event-driven transactions https://lnkd.in/g2uKp3gp

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In conjunction with Biden’s AI Executive Order from last fall, the President's Council of Advisors on Science and Technology (PCAST) just released a study and report exploring the implications of AI for scientific research. A key focus is on how a well-designed, equitably shared, and responsibly used data and AI infrastructure could empower scientists and others to tackle some of our greatest societal and global challenges. Executive summary is below.  Special thanks to Eric Horvitz, Chief Scientific Officer at Microsoft for his work on this committee. #ai #responsibleAI #aiinresearch

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