"The Data Diva" Talks Privacy Podcast

Send us a textEpisode 258 – Terry Bollinger: Understanding the Limits of Artificial IntelligenceIn this episode of The Data Diva Talks Privacy Podcast, Debbie Reynolds, The Data Diva, speaks with Terry Bollinger, retired technology analyst at MITRE, about the limits of artificial intelligence and the growing risks of relying on systems that only mimic human understanding. They discuss how large language models operate as mimicry machines, imitating intelligence rather than achieving it, and how this design choice leads to fundamental weaknesses in trust, accuracy, and accountability. Terry explains that AI models based on probability and pattern replication erase uniqueness, creating false confidence in their results. He warns that by averaging data rather than analyzing meaning, these systems blur important distinctions, making it difficult to detect errors, anomalies, or malicious activity. Debbie and Terry explore why true privacy and security depend on identifying outliers —the small deviations that reveal hidden threats, rather than relying on average trends.Terry describes how traditional security systems are built on clearly defined boundaries, data paths, and verification processes, while modern AI systems often remove those controls. He emphasizes that when data is distributed, reweighted, and stored probabilistically, it becomes nearly impossible to verify what has been learned, lost, or leaked. The conversation examines the risks of utilizing LLMs in sensitive environments, where transmitting confidential data to remote commercial systems can compromise containment and integrity. Terry discusses how interpolation, or the act of filling in the blanks when data is missing, leads AI to generate convincing but incorrect answers, what he calls “random noise masquerading as insight.” Debbie and Terry also examine why intelligence, wisdom, and comprehension cannot be replicated through scale or speed. The episode concludes with a reflection on the importance of human judgment, accountability, and boundary control in an era where automation is expanding faster than understanding.Support the show

Send us a textThe Data Diva Talks Privacy Podcast – Episode 257 with Gina King, Cyber vCISO and Communications Consultant, King and Company CapitalStruggling to bridge the gap between business and technology teams? In this episode, Gina King shares how building trust and understanding unlocks stronger security outcomes. She also explains why companies rushing into AI without cleaning up their data first are putting their organizations at serious risk.Gina and I discuss how she bridges communication between technical teams and business leadership, and why understanding motivations and emotions drives better collaboration. We explore how overlooked “folklore processes” create hidden risks, how insider threats and employee churn accelerate knowledge loss during the AI rush, and why privacy and cybersecurity must work symbiotically. Gina explains why data problems almost always precede privacy problems, the dangers of AI drift and misapplied answers, and the legal risks created by unclear contracts, consent gaps, and ambiguous rights to use AI.We also examine the growing problem of fake AI companies, data-siphoning tools, and the risk they pose to small businesses, and why business leaders must align their data story before adopting AI.This podcast reaches listeners in 140+ countries and 3,000+ cities and features leaders shaping global privacy, AI, and emerging technology strategy. If you are a business leader, CISO, or privacy professional, this episode will help you prevent AI chaos by fixing your data story and building trust between teams.Subscribe to The Data Diva Talks Privacy Podcast for more conversations with global leaders shaping the future of privacy, data, and emerging technology.#dataprivacy #datadiva #privacy #cybersecurity #AI #datagovernance #businessriskSupport the show

Send us a textEpisode 256 – Jennifer Wondracek, Director of the Law Library and Professor of Legal Research and Writing, Capital University Law School, ABA Women of Legal Tech HonoreeWhat happens when courts rely on fake cases created by AI? Jennifer Wondracek examines the risks associated with AI in legal research and education.On The Data Diva Talks Privacy Podcast, Debbie Reynolds, “The Data Diva,” speaks with Jennifer Wondracek, Director of the Law Library and Professor of Legal Research and Writing at Capital University Law School, and ABA Women of Legal Tech Honoree, about the risks of AI in legal research and the responsibility of lawyers and educators to ensure its proper use. Wondracek highlights how courts have already faced real-world consequences when AI systems generated fabricated cases, exposing serious risks to professional practice.She shares her perspective as a leader in law librarianship and legal technology, describing the epidemic of misattributed citations in legal filings and the dangers of allowing AI to revise legal writing without proper oversight. Wondracek explains why lawyers must verify sources rather than rely blindly on AI outputs, and why technology competency is now a critical requirement in the profession. She traces the shift from print to digital research and considers how AI represents the next stage of transformation. The discussion also addresses how legal education must adapt to prepare students for AI-driven research and practice, ensuring the next generation is ready to use these tools responsibly.This episode offers valuable insights not only to lawyers and educators but also to anyone curious about how AI is reshaping trust, accountability, and knowledge in fields that impact society as a whole.Hosted by Debbie Reynolds, “The Data Diva,” bringing global leaders together on privacy, cybersecurity, and emerging technology.  Support the show

Send us a textEpisode 255 – Don Morron, Founder and CEO of Highland Tech, AI Agents for EnterpriseWhat does it take to build resilience in a world of constant cyber threats? Don Morron shares strategies for adapting without losing control.On The Data Diva Talks Privacy Podcast, Debbie Reynolds, “The Data Diva,” interviews Don Morron, Founder and CEO of Highland Tech, AI Agents for Enterprise, about how executives can build resilience into their organizations in the face of a constantly evolving cyber threat landscape. Morron shares lessons from his leadership journey in cybersecurity and explains why resilience cannot be bolted on after the fact but must be embedded into enterprise systems from the very beginning.The conversation covers how AI is reshaping cybersecurity, both by enabling attackers with new tools and by empowering defenders with advanced capabilities. Morron provides practical insights into managing enterprise security operations in rapidly changing conditions without compromising organizational control. He stresses the importance of communication and collaboration across teams, highlighting how siloed approaches undermine resilience. The episode also explains why proactive governance and long-term planning are far more effective than reactive firefighting.These insights are useful not only for executives and security leaders but also for anyone interested in how organizations adapt to technology-driven risks and build strength in uncertain times.Hosted by Debbie Reynolds, “The Data Diva,” bringing global leaders together on privacy, cybersecurity, and emerging technology.Support the show

Send us a textEpisode 254 – Bryan Lee, Founder and General Partner, Privatus ConsultingWhy do privacy programs fail even when companies want to succeed? Bryan Lee explains why communication is the missing piece.On The Data Diva Talks Privacy Podcast, Debbie Reynolds, “The Data Diva,” welcomes Bryan Lee, Founder and General Partner at Privatus Consulting, to discuss why effective privacy programs succeed through strong communication rather than technical jargon. Lee explains how privacy engineering serves as a critical link between policy, compliance, and technical teams, and why clear communication is often the deciding factor in whether organizations achieve their privacy goals.He explains why many companies fail at privacy, despite genuine intent, often because coordination among stakeholders breaks down. Lee reflects on his own career path, transitioning from intelligence work to privacy consulting, and shares insights into how organizations can overcome communication barriers to develop programs that are both compliant and effective. The conversation also covers the risks of misjudging AI, particularly the mistake of treating systems as if they were human, and how this misunderstanding creates governance and operational problems.This episode offers strategies for bridging gaps, enhancing collaboration, and addressing complex issues, resonating with privacy leaders, compliance professionals, and anyone seeking to understand how effective communication drives successful outcomes in organizations.Hosted by Debbie Reynolds, “The Data Diva,” bringing global leaders together on privacy, cybersecurity, and emerging technology.Thanks to our Data Diva Talks Privacy Podcast Privacy Ambassador Sponsor, Piwik PRO. Piwik PRO is a privacy-first analytics and customer data platform that helps organizations to make informed decisions across their websites, apps, and ad campaigns. They bring an unprecedented level of data transparency, so you know exactly how your data is collected, used, and protected. It is very cool. Marketers gain valuable insights, while legal teams rest assured knowing that your client data remains protected, even as the privacy landscape evolves.  Learn more at piwik.pro. Enjoy the show.Support the show

Send us a textEpisode 253 – Priya Gnanasekaran, Senior Security Engineer at LAB3 (Australia)Can AI be both a risk and a defense? In this episode, Priya Gnanasekaran shares how organizations can manage today’s most pressing cybersecurity challenges.On The Data Diva Talks Privacy Podcast, Debbie Reynolds, “The Data Diva,” speaks with Priya Gnanasekaran, Senior Security Engineer at LAB3 (Australia), about the complex challenges cybersecurity leaders face with AI, IoT, and cloud security. Drawing on her decade-long career spanning DevSecOps, engineering, and operations, Gnanasekaran explains why cybersecurity cannot be reduced to a single field but must be understood as an amalgamation of multiple interconnected disciplines. She highlights the distinction between IT and cybersecurity and explains why this distinction is crucial for executives making risk and investment decisions.The conversation examines AI’s dual role in cybersecurity, acting both as a new attack vector and as a defensive tool that, when used responsibly, can strengthen organizational security. Gnanasekaran also details the risks of shadow AI and unmonitored enterprise use, exposing businesses to unmanaged vulnerabilities. She addresses weaknesses in IoT ecosystems, including outdated devices and hardware flaws, and argues that these cannot be solved through patchwork responses. Instead, she emphasizes the importance of “shifting left” by embedding security earlier in DevSecOps processes. Gnanasekaran stresses that cybersecurity cannot be treated like a fire department that responds only after damage has been done.This discussion offers valuable lessons on resilience, innovation, and proactive strategy, applicable not only to security professionals but also to anyone interested in understanding how digital systems can be better protected and managed.Hosted by Debbie Reynolds, “The Data Diva,” bringing global leaders together on privacy, cybersecurity, and emerging technology.Support the show

Send us a text🎙️ Episode 252 of The Data Diva Talks Privacy Podcast – J. Mark Bishop and Debbie Reynolds, The Data Diva, on AI myths, GDPR safeguards, and energy costs of large modelsIn this episode, I speak with J. Mark Bishop, Professor of Cognitive Computing Emeritus at Goldsmiths, University of London, and Scientific Advisor to Fact360, about the myths and realities of artificial intelligence.Our discussion begins with how we describe AI itself. Mark challenges the language we use, terms like “learning” in machine learning, and argues that much of what is happening is, in fact, just optimization. We examine how anthropomorphic language about AI can create misplaced expectations, shaping how the public and policymakers perceive these technologies.We examine the tension between AI and privacy, particularly in relation to transparency. Mark reflects on the protections built into frameworks like the GDPR, which explicitly address how personal data may be used when AI makes or informs significant decisions. We examine how these rules strike a balance between individual rights and the need to utilize AI systems in business and government.Another major theme is metadata analysis. Mark shares insights from his work at Fact360, where analyzing patterns of communication without even looking at message content can reveal signals of organizational change, insider threats, or misconduct. This approach has roots in traffic analysis techniques dating back to World War II, showing how metadata continues to play a powerful role in intelligence and security.We also discuss the scaling laws of AI and whether building increasingly larger data centers will ultimately lead to artificial general intelligence. Mark strongly critiques this idea, raising concerns about the energy demands of massive AI models. He points out the environmental and ethical costs of data centers, which consume energy on the scale of entire nations, especially when many communities still live in energy poverty.This episode brings together philosophy, technology, governance, and ethics, a conversation that questions not just what AI is, but what it should be.Subscribe to “The Data Diva” Talks Privacy Podcast, now available on all major podcast directories, including Apple Podcasts, Spotify, Stitcher, iHeart Radio, and more.Hosted by Data Diva MediaDebbie Reynolds Consulting, LLC#AI #ethics #metadata #GDPR #datagovernance #sustainability#dataprivacy #datadiva #privacy #cybersecurity🎙️ 🎙️ Episode 258 of The Data Diva Talks Privacy Podcast – Jennifer Wondracek and Debbie Reynolds, The Data Diva, on legal tech, privacy risks, redaction failures, and AI detectorsIn this episode, I speak with Jennifer Wondracek, Director of the Law Library and Professor of Legal Research at St. Mary’s University School of Law, about the intersection of law, technology, and privacy in an AI-driven world.Our conversation explores the digital transformation of law practice, starting with the shift from paper-based systems to electronic filing and research tools, and how today’s wave of AI adoption parallels that earlier revolution. Jennifer explains how lawyers once resisted computers as unnecessary, only to later realize that digital tools were essential for efficiency and productivity. We draw parallels to AI today, where professionals must learn how to integrate new tools responsibly.We discuss the privacy risks of oversharing data with companies and platforms, and how easy it has become for people to give up personal information without realizing the consequences. Jennifer highlights the duty of lawyers to understand both client confidenSupport the show

Send us a textIn episode 251 of The Data Diva Talks Privacy Podcast, host Debbie Reynolds, “The Data Diva,” welcomes Ilia Dubovtsev, Founder of Dub Consulting, joining from Moscow, Russia. he discussion centers on the complexities of privacy in the workplace and how emerging technologies, especially AI, are reshaping the boundaries of personal data and institutional responsibility. Ilia shares his framework for operationalizing privacy—built on the principles of accountability, fairness, and balancing interests, and explains why this model is essential when managing employee data in digitally driven environments.Ilia shares his belief that privacy is the maximum expression of individual liberty. He developed a three-pillar framework for privacy programs: accountability, balance of interest, and fairness. He explains how these principles can be applied across jurisdictions, whether in Russia, Europe, or the United States. Despite the United States’ lack of a comprehensive federal privacy law, Ilia notes that core principles like non-discrimination and transparency often serve as common ground for workplace privacy protections.Debbie and Ilia dive deep into the complexities of employee privacy, comparing regulatory and cultural variations. They acknowledge that workplace data, often governed by contract law, labor law, and surveillance practices, is uniquely sensitive because employees have fewer choices about whether and how their data is collected. The conversation shifts to the influence of AI in the workplace. Ilia envisions AI empowering employees by reducing dependency on traditional corporate structures, potentially shifting employer-employee dynamics to a more equitable “peer” relationship. He proposes a new privacy policy model that includes (1) transparent data practices, (2) distinct policy boundaries across employment stages, and (3) accessible remedies for challenging data misuse. Ilia stresses the need for literacy, both technical and legal, to protect workers and hold employers accountable.The episode concludes with a thoughtful exchange on liberty, trust, and the potential of fair AI governance. Ilia emphasizes that privacy must be preserved through principled regulation and public education, rather than a proliferation of fragmented, burdensome rules. He cites the U.S. scholarly conversation around the “duty of loyalty” and calls for frameworks that ensure both data accountability and empowerment for individuals.#EmployeePrivacy #GlobalPrivacyFramework #AIinWorkplace #DubConsulting #PrivacyRights #DigitalGovernance #DataLiberty #WorkplaceEthics #AIandHR #PrivacyLiteracySupport the show

Send us a textIn episode 250 of The Data Diva Talks Privacy Podcast, host Debbie Reynolds, “The Data Diva,” welcomes Marianne Mazaud, Co-Founder of AI ON US, an International Executive Summit Focused on Responsible Artificial Intelligence, co-created with Thomas Lozopone. They explore the powerful relationship between AI, privacy, and trust, emphasizing how leaders can take actionable steps to create inclusive and ethically grounded AI systems.Marianne shares insights from her extensive experience in creative performance marketing and brand protection, including how generative AI technologies have created both opportunities and new risks. She stresses the importance of privacy and inclusion in AI governance, especially in high-risk sectors like healthcare and education.The conversation moves to public trust in AI. Marianne references a study revealing widespread distrust in AI systems due to cybersecurity concerns, algorithmic bias, and lack of transparency. She highlights the need to involve more diverse voices, including individuals with disabilities and children, in the development of emerging technologies. Marianne and Debbie also examine the role of data privacy in consumer trust, citing a PricewaterhouseCoopers report showing that 83% of consumers believe data protection is essential to building trust with businesses.They compare AI regulatory landscapes across the European Union and the United States. Marianne outlines how the EU AI Act places joint responsibility on AI developers and providers, which can introduce compliance complexities, especially for small businesses. She explains how these regulations can be difficult to implement retroactively and may impact innovation when not considered early in the development process.Marianne closes by introducing the AI On Us initiative and the International Summit on Responsible AI for Executives. These efforts are designed to support leaders navigating AI governance through immersive workshops, best practices, and applied exercises. She also describes the Arborus Charter, a commitment to gender equality and inclusion in AI that has been adopted by 150 companies globally.They discuss the erosion of public trust in AI and the contributing role of biased algorithms, black-box decision-making, and regulatory fragmentation across regions. Marianne describes the uneven distribution of protections for vulnerable populations, such as children and persons with disabilities, and the failure of many AI systems to account for culturally or biologically diverse user bases. She emphasizes that privacy harms are not only about data collection but also about downstream effects and misuse, especially in sectors like healthcare, hiring, and public policy.Debbie and Marianne contrast the emerging regulatory models in the United States and the European Union, noting that the U.S. often lacks forward-looking obligations for AI developers, whereas the EU imposes preemptive risk requirements. Despite these differences, both agree that building AI systems that are trustworthy, explainable, and fair must become a global imperative. Marianne closes by describing how AI on Us was founded to help global executives take practical, values-driven steps toward responsible AI. Through events, tools, and shared ethical commitments, the initiative encourages leaders to treat AI responsibility as a competitive advantage, not just a compliance obligation.#AIandPrivacy #ResponsibleAI #Governance #SyntheticContent #TrustworthyAI #InclusiveTech #AlgorithmicAccountability #PrivacyHarms #EtSupport the show

Send us a textIn episode 249 of The Data Diva Talks Privacy Podcast, host Debbie Reynolds, “The Data Diva,” welcomes Marlyse McQuillen, Vice President of Regulatory Compliance, Privacy, and AI at IntegraConnect LLC. Their conversation offers a multidimensional exploration of privacy, from professional ethics and emerging legal conflicts to education policy and AI governance.Marlyse shares her journey into privacy law, which began during her work as a corporate attorney and expanded through roles in sectors such as health care, finance, and security. She reflects on her professional evolution and her aspirations to bring her cross-industry expertise to companies, especially as organizations increasingly confront regulatory pressure in the areas of consumer data and artificial intelligence.The conversation dives into privacy issues in healthcare, where Marlyse emphasizes the risks of digital health data in a landscape that continues to shift toward value-based care. She highlights how HIPAA and HIPAA adjacent laws or obligations create complexities in addressing data outside of traditional clinical systems. This becomes especially urgent when companies face financial instability. Marlyse details the example of 23AndMe, a major bankruptcy involving genetic data, in which states raised objections to the sale of consumer health information, and the court ultimately appointed a consumer privacy ombudsman. She and Debbie underscore the long-term damage to trust when sensitive personal data is treated as a transferable asset during bankruptcy proceedings.The discussion also touches on public digital exposure through the lens of the “Coldplaygate” incident, where a viral Kiss Cam moment led to the resignation of a company CEO. Marlyse and Debbie reflect on how these seemingly lighthearted digital moments can carry real consequences, especially in an era of high surveillance and online amplification. They emphasize the importance of discretion and privacy boundaries, even in public settings.Marlyse brings a strong policy perspective, advocating for legislative updates to genetic privacy laws and more comprehensive protection for children in schools. She is actively working with the Plunk Foundation to build a digital literacy curriculum that educates young people on safe AI use and privacy rights. She envisions federal mandates for consumer data protection education as a way to create foundational awareness early in life.The episode closes with personal reflections on the rewarding yet difficult work of privacy leadership, the importance of soft skills development, and Marlyse’s creative approach to privacy education, including a song she wrote to raise awareness about data rights. Throughout, she champions practical reforms, better breach responses, and a cultural shift toward accountability in both public and private uses of technology.#DigitalHealthPrivacy #GeneticData #AIinEducation #ConsumerTrust #Coldplaygate #PrivacyEducation #PlunkFoundation #PrivacyBankruptcy #PrivacyLeadership #DigitalLiteracy #DataRightsThanks to our Data Diva Talks Privacy Podcast Privacy Ambassador Sponsor, Piwik PRO. Piwik PRO is a privacy-first analytics and customer data platform that helps organizations to make informed decisions across their websites, apps, and ad campaigns. They bring an unprecedented level of data transparency, so you know exactly how your data is collected, used, and protected. It is very cool. Marketers gain valuable insights, while legal teams rest assured knowing that your client data remains protected, even as the privacy landscape evolves.  Learn more at piwik.pro. Enjoy the show.Support the show