DataFramed

• #335 Rebuilding Trust in the Digital Age with Jimmy Wales, Founder at Wikipedia

  The internet has transformed how we access information, but it's also created unprecedented challenges around trust and reliability. How do we build digital spaces where collaboration thrives and quality information prevails? What separates toxic online environments from productive ones? The principles of neutrality, transparency, and assuming good faith have proven essential in creating sustainable knowledge communities. But these same principles extend far beyond the digital realm—they're fundamental to effective leadership, successful business relationships, and even political discourse. When trust breaks down, everything becomes more difficult. So what practical steps can we take to foster trust in our organizations and communities?Jimmy Wales is an American-British internet entrepreneur best known as the founder of Wikipedia and co-founder of Fandom. Trained in finance at Auburn University and the University of Alabama, he began his career in quantitative finance before moving into early web ventures, including Bomis and the free encyclopedia project Nupedia. In 2001, he launched Wikipedia, which quickly became one of the most visited websites in the world. To support its growth, he established the Wikimedia Foundation in 2003, where he continues to serve on the Board of Trustees and act as a public spokesperson. He later co-founded Fandom in 2004, expanding the wiki model to entertainment, gaming, and niche communities. Wales has also pursued experiments in collaborative journalism, including WikiTribune and its successor WT Social. His work in open knowledge has earned recognition from organizations such as the World Economic Forum, Time magazine, UNESCO, and the Electronic Frontier Foundation. He has held fellowships and board roles at institutions including Harvard’s Berkman Center and Creative Commons.In the episode, Richie and Jimmy explore the early challenges of Wikipedia, the importance of trust and neutrality, the role of AI in content creation, and much more.Links Mentioned in the Show:WikipediaJimmy’s New Book: The Seven Rules of TrustTrust CaféConnect with JimmyBlog: The Trust Triangle of LeadershipAI-Native Course: Intro to AI for WorkRelated Episode: How to Build AI Your Users Can Trust with David Colwell, VP of AI & ML at TricentisExplore AI-Native Learning on DataCampNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

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• #334 The State of Data & AI with Tom Tunguz, VC at Theory Ventures

  The AI landscape is evolving at breakneck speed, with new capabilities emerging quarterly that redefine what's possible. For professionals across industries, this creates a constant need to reassess workflows and skills. How do you stay relevant when the technology keeps leapfrogging itself? What happens to traditional roles when AI can increasingly handle complex tasks that once required specialized expertise? With product-market fit becoming a moving target and new positions like forward-deployed engineers emerging, understanding how to navigate this shifting terrain is crucial. The winners won't just be those who adopt AI—but those who can continuously adapt as it evolves.Tomasz Tunguz is a General Partner at Theory Ventures, a $235m early-stage venture capital firm. He blogs at tomtunguz.com & co-authored Winning with Data. He has worked or works with Looker, Kustomer, Monte Carlo, Dremio, Omni, Hex, Spot, Arbitrum, Sui & many others. He was previously the product manager for Google's social media monetization team, including the Google-MySpace partnership, and managed the launches of AdSense into six new markets in Europe and Asia. Before Google, Tunguz developed systems for the Department of Homeland Security at Appian Corporation.In the episode, Richie and Tom explore the rapid investment in AI, the evolution of AI models like Gemini 3, the role of AI agents in productivity, the shifting job market, the impact of AI on customer success and product management, and much more.Links Mentioned in the Show:Theory VenturesConnect with TomTom’s BlogGavin Baker on MediumAI-Native Course: Intro to AI for WorkRelated Episode: Data & AI Trends in 2024, with Tom Tunguz, General Partner at Theory VenturesRewatch RADAR AI New to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

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• #333 Creating an AI-First Data Team with Bilal Zia, Head of Data Science & Analytics at DuoLingo

  Data science leadership is about more than just technical expertise—it’s about building trust, embracing AI, and delivering real business impact. As organizations evolve toward AI-first strategies, data teams have an unprecedented opportunity to lead that transformation. But how do you turn a traditional analytics function into an AI-driven powerhouse that drives decision-making across the business? What’s the right structure to balance deep technical specialization with seamless business integration? From building credibility through high-impact forecasting to creating psychological safety around AI adoption, effective data leadership today requires both technical rigor and visionary communication. The landscape is shifting fast, but with the right approach, data science can stand as a true pillar of innovation alongside engineering, product, and design.Bilal Zia is currently the Head of Data Science & Analytics at Duolingo, an EdTech company whose mission is to develop the best education in the world and make it universally available. Previously, he spent two years helping to build and lead an interdisciplinary Central Science team at Amazon, comprising economists, data and applied scientists, survey specialists, user researchers, and engineers. Before that, he spent fifteen years in the Research Department of the World Bank in Washington, D.C., pursuing an applied academic career. He holds a Ph.D. in Economics from the Massachusetts Institute of Technology, and his interests span economics, data science, machine learning/AI, psychology, and user research.In the episode, Richie and Bilal explore rebuilding an underperforming data team, fostering trust with leadership, embedding data scientists within product teams, leveraging AI for productivity, the future of synthetic A/B testing, and much more.Links Mentioned in the Show:DuolingoDuolingo Blog: How machine learning supercharged our revenue by millions of dollarsConnect with BilalAI-Native Course: Intro to AI for WorkRelated Episode: The Future of Data & AI Education Just Arrived with Jonathan Cornelissen & Yusuf SaberRewatch RADAR AI New to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

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• #332 How to Build AI Your Users Can Trust with David Colwell, VP of AI & ML at Tricentis

  The relationship between data governance and AI quality is more critical than ever. As organizations rush to implement AI solutions, many are discovering that without proper data hygiene and testing protocols, they're building on shaky foundations. How do you ensure your AI systems are making decisions based on accurate, appropriate information? What benchmarking strategies can help you measure real improvement rather than just increased output? With AI now touching everything from code generation to legal documents, the consequences of poor quality control extend far beyond simple errors—they can damage reputation, violate regulations, or even put licenses at risk.David Colwell is the Vice President of Artificial Intelligence and Machine Learning at Tricentis, a global leader in continuous testing and quality engineering. He founded the company’s AI division in 2018 with a mission to make quality assurance more effective and engaging through applied AI innovation. With over 15 years of experience in AI, software testing, and automation, David has played a key role in shaping Tricentis’ intelligent testing strategy. His team developed Vision AI, a patented computer vision–based automation capability within Tosca, and continues to pioneer work in large language model agents and AI-driven quality engineering. Before joining Tricentis, David led testing and innovation initiatives at DX Solutions and OnePath, building automation frameworks and leading teams to deliver scalable, AI-enabled testing solutions. Based in Sydney, he remains focused on advancing practical, trustworthy applications of AI in enterprise software development.In the episode, Richie and David explore AI disasters in legal settings, the balance between AI productivity and quality, the evolving role of data scientists, and the importance of benchmarks and data governance in AI development, and much more.Links Mentioned in the Show:Tricentis 2025 Quality Transformation ReportConnect with DavidCourse: Artificial Intelligence (AI) LeadershipRelated Episode: Building & Managing Human+Agent Hybrid Teams with Karen Ng, Head of Product at HubSpotRewatch RADAR AI New to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

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• #331 The Future of Data & AI Education Just Arrived with Jonathan Cornelissen & Yusuf Saber

  The future of education is being reshaped by AI-powered personalization. Traditional online learning platforms offer static content that doesn't adapt to individual needs, but new technologies are creating truly interactive experiences that respond to each learner's context, pace, and goals. How can personalized AI tutoring bridge the gap between mass education and the gold standard of one-on-one human tutoring? What if every professional could have a private tutor that understands their industry, role, and specific challenges? As organizations invest in upskilling their workforce, the question becomes: how can we leverage AI to make learning more engaging, effective, and accessible for everyone?As the Co-Founder & CEO of DataCamp, Jonathan Cornelissen has helped grow DataCamp to upskill over 10M+ learners and 2800+ teams and enterprise clients. He is interested in everything related to data science, education, and entrepreneurship. He holds a Ph.D. in financial econometrics and was the original author of an R package for quantitative finance.Yusuf Saber is a technology leader and entrepreneur with extensive experience building and scaling data-driven organizations across the Middle East. He is the Founder of Optima and a Venture Partner at COTU Ventures, with previous leadership roles at talabat, including VP of Data and Senior Director of Data Science and Engineering. Earlier in his career, he co-founded BulkWhiz and Trustious, and led data science initiatives at Careem. Yusuf holds research experience from ETH Zurich and began his career as an engineering intern at Mentor Graphics.In the episode, Richie, Jo and Yusuf explore the innovative AI-driven learning platform Optima, its unique approach to personalized education, the potential for AI to enhance learning experiences, the future of AI in education, the challenges and opportunities in creating dynamic, context-aware learning environments, and much more.Links Mentioned in the Show:Read more about the announcementTry the AI-Native Courses:Intro to SQLIntro to AI for WorkNew to DataCamp?Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for busines

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