"The Data Diva" Talks Privacy Podcast The Data Diva E250 - Marianne Mazaud and Debbie Reynolds
In 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.
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