Measuring the (Data) Culture of Medicine with Dr. Bapu Jena, Joseph P. Newhouse Professor at Harvard Medical School

The transformative potential of AI is going to affect all of us, regardless of what industry you’re in. While AI has the capability to democratize high-demand professions through specialized copilots, it also presents potential positive and negative societal impacts, including misinformation and political discourse manipulation. Today, we’re taking an in-depth look at the evolution of AI copilots tailored for specific professional fields and the need for critical thinking and transparent AI systems to ensure ethical deployment and improved outcomes in sectors like healthcare and finance.There’s a growing need for federal guidelines to prevent fragmented AI governance (think the EU AI Act). However, differing approaches to regulations across regions can lead to unbalanced directives. Politics are also influencing this new AI landscape. From potential deregulatory pushes under a Trump administration to sustained regulatory efforts under a Harris-led government, AI regulation will look different depending on who wins the US election. And it’s not just politics, total war is a significant worry when it comes to the use of AI. From military strategies to disrupting democracy, AI has the power to impact innovation, ethics, politics, and society. Satyen sits down with Jeremy to discuss his book Mastering AI, the importance of AI regulations, and the impact of AI on the job market.--------“In the US, we have this issue where the states are starting to take action because of the lack of action by the federal government and I think that's problematic. I don't think you want a system where you have every state with its own AI act and different laws to comply with in every state. I do think we need to have some action at the federal level. When we're going to see that happen, I don't know, because there has been a lot of lack of will. Even though there was some bipartisan efforts in Congress that looked like they were maybe going to pay off last year. I think there's some agreement on both sides of the aisle that there should be some rules and regulation passed around AI.” – Jeremy Kahn--------Time Stamps*(02:37): The future of AI: A boon for the middle class, a threat to democracy*(12:18): The case for federal AI regulation in the US*(20:11): The impact of the US election on AI regulations*(30:29): What is the Pigouvian or robot tax? *(36:39): What is total war? How will AI play a role?*(46:35): Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksConnect with Jeremy on LinkedInOrder Jeremy’s book, Mastering AILearn more about SB-1047Learn more about Anthropic’s AI ConstitutionLearn more about the FASTER Act

Legacy systems in the financial services industry are notorious for being slower to adapt to big data. But for good reason. Because banks are complicated and intersect across networks, it’s difficult to implement new processes without disturbing the rest of the system. Yet, GXS Bank is proving it doesn’t have to be this way. The digital bank is leveraging data to drive financial inclusion and innovation. Their strategic use of data from parent companies and partnerships, helps create financial products for underserved communities in Singapore.Not only is GXS Bank driving inclusion, but they’re also exploring the impact of generative AI on customer service, fraud detection, and operational efficiency. The technology is transforming the financial sector by offering valuable insights for improving data quality, governance, and stakeholder engagement. Satyen and Geraldine discuss the importance of creating better products and credit risk profiles, the intricacies of data sharing agreements and operational challenges, and strategies for leveraging AI to enhance customer service and fraud detection.--------“If you think about AI being part of a product manager, product creation, so you go to different segments of your consumers, see what their pain points are, do the summarization, and then say, ‘Hey, AI, can you create a new product that would match the needs of 50% of my segments in the consumer business?’ The AI quickly generates some AI product, a banking product for you with such features and you iterate and iterate and iterate. These are some of the tools that a product manager could really leverage on to create a new product from scratch.” – Gerladine Wong--------Time Stamps*(01:24): About GXS Bank*(10:04): Gen AI at GXS*(15:35): Supporting financial inclusion with alternative data sources*(31:34): Playing data offense vs defense at GXS*(40:51): Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksConnect with Geraldine on LinkedIn

The Data Radicals podcast returns on October 23rd! This season, we're exploring how trusted data drives value, whether that’s building game-changing AI or transforming data into dollars – and business results. You’ll hear from data leaders, journalists, and AI trailblazers like Dr. Geraldine Wong, CDO of GXS Bank, New York Times Chief Data Scientist, Chris Wiggins, and Jeremy Kahn, AI Editor at Fortune Magazine. And so many more! Get ready to discover groundbreaking strategies from some of the most innovative minds in data today. Welcome to season three of Data Radicals! Powered by the team here at Alation.--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/

Saul Alinsky's book Rules for Radicals held significant lessons for grassroots movements and political activism when it was published in 1971. It also inspired the title and theme of this podcast. In his book, Saul outlines approaches for unifying people and motivating them to work toward a common goal. Today, these same strategies can be used for data culture change management, triggering transformative action within organizations. Saul was an American activist and political theorist who lived from 1909 to 1972. His work organized impoverished communities and gave them tools to drive social change, and won him national attention and notability. In the final episode of the season, Satyen sits down with a ChatGPT-infused version of Saul to discuss the role of data in driving social change, the application of community organization tactics in corporate settings, and the key principles from Rules for Radicals.--------“On the global stage, data analytics and humanitarian efforts is akin to having a crystal ball. It's not about predicting the future, but about making informed, timely decisions that can save lives. The possibilities are indeed limitless. With data and analytics, we're not just changing the game. We're rewriting the rules and designing a better playbook for humanity.” – Saul GP Talinsky--------Episode Timestamps:*(03:57): Bridging community organizing with data science*(12:46): Empowering teams: Upskilling organizational agility*(14:35): Democratizing data and crafting a culture of insight and empowerment*(17:17): The timeless role of data in driving social change*(20:54): How to unlock societal transformation with data and analytics*(26:26): The evolution of radical change--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksRead Rules for Radicals

The rapid progress in AI technology has fueled the evolution of new tools and platforms. One such tool is a vector search. If the function of AI is to reason and think, the key to achieving this is not just in processing data, but also in understanding the relationships among data. Vector databases provide AI systems with the ability to explore these relationships, draw similarities, and make logical conclusions. Understanding and harnessing the power of vector databases will have a transformative impact on the future of AI.Edo Liberty is optimistic about the future where knowledge can be accessed at any time. Edo is the CEO and Founder of Pinecone, the managed database for large-scale vector search. Previously, he was a Director of Research at AWS and Head of Amazon AI Labs, where he built groundbreaking machine learning algorithms, systems, and services. He also served as Yahoo's Senior Research Director and led the research lab building horizontal ML platforms and improving applications. Satyen and Edo give a crash course on vector databases: what they are, who needs them, how they will evolve, and what role AI plays.--------“We as a community need to learn how to reason and think. We need to teach our machines how to reason and think and talk and read. This is the intelligence and we need to teach them how to know and remember and recall relevant stuff. Which is the capacity of knowing and remembering. The question is, what does it mean to know something? To know something is to be able to digest it, somehow to make the connections. When I ask you something about it, to figure out, ‘Oh, what's relevant? And I know how to bring the right information to bear so that I can reason about it.’ This ping pong between reasoning and retrieving the right knowledge is what we need to get good at.” – Edo Liberty--------Time Stamps*(03:13): How vector databases revolutionize AI*(14:13): Transforming the digital landscape with semantic search and LLM integration*(28:10): Exploring AI’s black box: The challenge of understanding complex systems *(37:02): Striking a balance between AI innovation and thoughtful regulation*(40:01): Satyen’s Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksConnect with Edo on LinkedInWatch Edo’s TED Talk

Folks in the data space are familiar with the concept of data literacy. However, a new idea is on the rise: business literacy. Whether folks sit in product, marketing, or commercial, there needs to be a productive balance between understanding business context and technical expertise of each department. This shared comprehension means ideas are more likely to be deployed and productionalized because everyone has deeper domain knowledge and business understanding.Sanjeevan Bala is making business literacy a top priority at his organization. He is the Group Chief Data and AI Officer at ITV, an Alation customer. There, he is responsible for driving the digital data and AI transformation and leading an offensive growth strategy that enhances how they produce, promote, distribute, and monetize content. Sanjeevan is an international thought leader, has won numerous awards for his work, and was named the most influential person in data by DataIQ. Satyen and Sanjeevan discuss the idea of a Data Product Manager, the importance of business literacy, and the power of experimentation.--------“I think because we went down the data as a product notion, that leadership role was a Data Product Manager. Incorporate product thinking in the way in which data is developed, designed, and used. I think what's beautiful about product thinking is it's very well adapted and equipped for understanding competing objectives and competing needs. Creating methods by which you're trying to either align or prioritize those needs. But, critically allows you to prioritize around the right things because you're constantly looking at how do you make sure you can productionize and scale and realize the full value? What does it take to do that? That goes way beyond what you're doing in data. That gets into organizational change, that gets into last mile technologies that you may not have thought about.” – Sanjeevan Bala--------Time Stamps*(05:16): How to define your organizational identity*(07:26): The art of storytelling and data-driven leadership*(18:20): Harnessing experimentation to drive organizational change*(25:10): Data literacy versus business literacy*(42:17): Balancing innovation and regulation in AI*(44:41): Satyen’s Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksConnect with Sanjeevan on LinkedIn

Whether you work in retail, healthcare, or CPG, data analytics is key to making your business stand out. You’re able to find new sources of data, synthesize them, and then work with business folks to get better and better insights. Even with all of the advantages analytics offers us, sometimes there’s hesitancy to invest in data. In sports, it’s the exact opposite. The use of data is felt immediately in game wins, player selection, and gate revenue.Known as “The Real Moneyball guy,” Ari Kaplan has revolutionized sports through analytics and is a leading influencer in the area, as well as in AI and data. He helped create analytics departments for the Chicago Cubs, Los Angeles Dodgers, and Baltimore Orioles. Ari is now Head of Evangelism at Databricks where his team helped the Texas Rangers clinch their first World Series title. Satyen and Ari discuss data analytics in sports, how data intelligence platforms are shifting the landscape, and the concept of generation AI.--------“Even if we change nothing else, to be able to make better predictions of player development, finding what skills are better in the draft, predicting injuries and so on, that's part of the competitive advantages. How can we ingest this data? It's a ton of data. Terabytes of data every game, multiply that by dozens and dozens of teams at all levels around the world. Right now, teams are struggling to store it, process it on a daily basis. Teams that could do that faster will be an advantage. For listeners, if you're not in the baseball world, same idea. If you're in retail, CPG, healthcare, it's finding new sources of data, proprietary, nonproprietary. How could you synthesize it? Then, how can you start working with the business people to get better and better and better insights?” – Ari Kaplan--------Time Stamps:*(03:00): The birth of Moneyball*(10:11): How the Texas Rangers hit a data home run*(15:49): The next evolution: data intelligence*(27:17): Partnering for success in the ecosystem*(38:54): The role of AI in building the future*(41:29): Satyen’s Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksLearn more about Raoul Wallenberg’s fateConnect with Ari on LinkedInFollow Ari on X

When it comes to our relationship with technology, be like philosopher Friedrich Nietzsche and practice mindfulness. We usually think mindfulness means setting boundaries like screen time limits. However, we should think about the goals and values we want from technology, like greater human connection, improving efficiency, or driving knowledge. This introspective thinking enables us to be intentional about how and why we’re using technology. Without mindfulness, instead of you driving the tech, the tech may be driving you. Nate Anderson lives by and continues to share Nietzsche’s philosophies today. Nate is the Deputy Editor at Ars Technica, where he covers technology law, politics, and culture. He combined his high-tech background with a love of writing to freelance at publications like The Economist and Foreign Policy. Nate is also the author of In Emergency, Break Glass: What Nietzsche Can Teach Us About Joyful Living in a Tech-Saturated World. Satyen and Nate discuss forming positive connections with technology, saying “yes” to life, and what Nietzsche would have to say about tech.--------“Connection to other people is important. We use technology to create that connection. That might mean a Friday night game group over Zoom or Twitch or multiplayer with your friends. As long as you have the goal in mind, that's where it requires your creativity. That's where you're using the tools creatively to produce outcomes that you want in life. The problem with not thinking in a goal-directed way is that technology itself is not completely neutral. Technology has no goals of its own. It was created by people and companies who have plenty of goals and some of those don't necessarily take you to places where you would choose to go. That's why if you don't have a goal-driven approach to technology, you may find technology is actually driving you.” – Nate Anderson--------Time Stamps:*(04:25): Why Nietzsche? Why now?*(15:07): Offer agency, not just prescriptive rules*(24:17): The loneliness of technology*(27:51): Seeking that goal-driven place*(35:44): Producing actual value*(38:35): Satyen’s Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksRead In Emergency, Break GlassConnect with Nate on LinkedIn

Thanks to GenAI, we have an overabundance of tools, models, and capabilities. However, the use and impact of these advancements is yet to be known. That’s why in the age of technological innovation, traditional skills like fact-checking are more important than ever to ensure that the technology and predictions are correct. Guy Scriven, U.S. Technology Editor at The Economist, is on the frontlines of the AI explosion. In his tenure at the publication, he has served as a researcher and climate risk correspondent, and has grown his affinity for telling data-driven stories. Satyen and Guy discuss the role of data in journalism, instilling a culture of debate, and the unsexy – but critical – side of AI.--------“We've had this long period of experimentation and excitement. That's been basically marked by the supply side of AI just really ramping up. You've had loads of model makers releasing new models. You've had the cloud players buying enormous amounts of specialized AI chips. You've had thousands of AI application startups who are going to build on top of the model makers, who then use the AI chips from the cloud providers. You've had this boom in the supply side of AI. Now, the big question is whether the enterprise demand meets that and what shape it takes. I think we don't really have a good sense of that until at least the first couple of quarters of next year.” – Guy Scriven--------Time Stamps:*(02:22): Less reporting, more commentary *(13:32): Dataset discovery *(22:34): ChatGPT’s hallucination problem *(34:38): AI headlines on the rise *(41:48): What’s the next big AI story? *(46:10): Satyen’s Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksConnect with Guy on LinkedIn

The best kind of data radical is one who knows how to balance their technical expertise with their fuzzy side. Skills like storytelling, empathy, and ethics are becoming invaluable in the tech space. The ability to balance both enables data folks to recognize patterns where others might miss them. This type of integrative thinking can guide people on their next investment, whether they’re investing time, money, or resources. Scott Hartley is a global early-stage investor and author of The Fuzzy and the Techie: Why the Liberal Arts Will Rule the Digital World. His passion lies in emerging markets and big ideas that improve lives, particularly in financial services, health, supply chain, and logistics. Scott has served as a Presidential Innovation Fellow at the White House and has co-founded two venture capital firms: Everywhere Ventures and Two Culture Capital. Satyen and Scott discuss the techie and fuzzy sides of Silicon Valley, the advancement of tech, and how Scott chooses his next investment.--------“I love this thought around data collection and big data is one thing, it's collecting information. But, then turning that information into knowledge and into wisdom. In one part, can be done through unstructured to structured data, through things like LLMs that are enabling us to move out of the information noise into a bit more knowledge noise, and then maybe into wisdom specificity. I still think that there's a leap there that's going to be human-driven. Whether it's a person sitting there interpreting or it's a team of engineers thinking about the sensitivities, the data tagging. There are human decisions in the mix somewhere along that chain, as we're taking on structured data and turning it into structured knowledge and wisdom. All these things to say, that even these deeply technical infrastructure-level technologies, have elements of humanity in them.” – Scott Hartley--------Time Stamps:*(10:55): The genesis behind The Fuzzy and the Techie*(18:11): Subjectivity, structure, and bias*(20:17): Scott’s investment focus*(30:09): The “tables-stakes economy” *(38:11): AI and public policy *(47:43): Satyen’s Takeaways--------SponsorThis podcast is presented by Alation.Learn more:* Subscribe to the newsletter: https://www.alation.com/podcast/* Alation’s LinkedIn Profile: https://www.linkedin.com/company/alation/* Satyen’s LinkedIn Profile: https://www.linkedin.com/in/ssangani/--------LinksRead The Fuzzy and the TechieVisit Scott’s websiteConnect with Scott on LinkedIn