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In episode 247 of “The Data Diva” Talks Privacy Podcast, Debbie Reynolds talks to Michael Robbins, Social Entrepreneur and Civic Builder, and a visionary in building human-plus-digital learning ecosystems. We discuss his decades-long journey at the intersection of education, technology, and community, from grassroots innovation to White House policy. Michael shares a compelling vision for the future of AI in education, centered on empowering individuals to create and control their own AI narratives. He introduces his data model, called DOTES (Do, Observe, Tell, Explore, Show), which captures real-world learning experiences and enables the training of personalized AI agents grounded in data integrity and digital personhood.
Our conversation explores the concept of implication models, AI systems that learn from and work for people, rather than exploiting their data. Michael draws parallels between decentralized data governance and the design of AI trusts, where individuals have full control over their digital identities and contributions. We also explore the limitations of current large language models and discuss new frameworks that could rebuild AI from the ground up, centering privacy, consent, and community.
Together, we envision a future where youth and adults alike use AI not as a replacement for human intelligence but as a tool for self-expression, empowerment, and democratic participation. This episode is a masterclass in AI ethics, digital sovereignty, and the urgent need to shift from extractive technologies to human-first ecosystems. We hope for a future where data privacy is not just a legal checkbox, but a fundamental principle of technological design and societal infrastructure.
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Send us a text
In episode 247 of “The Data Diva” Talks Privacy Podcast, Debbie Reynolds talks to Michael Robbins, Social Entrepreneur and Civic Builder, and a visionary in building human-plus-digital learning ecosystems. We discuss his decades-long journey at the intersection of education, technology, and community, from grassroots innovation to White House policy. Michael shares a compelling vision for the future of AI in education, centered on empowering individuals to create and control their own AI narratives. He introduces his data model, called DOTES (Do, Observe, Tell, Explore, Show), which captures real-world learning experiences and enables the training of personalized AI agents grounded in data integrity and digital personhood.
Our conversation explores the concept of implication models, AI systems that learn from and work for people, rather than exploiting their data. Michael draws parallels between decentralized data governance and the design of AI trusts, where individuals have full control over their digital identities and contributions. We also explore the limitations of current large language models and discuss new frameworks that could rebuild AI from the ground up, centering privacy, consent, and community.
Together, we envision a future where youth and adults alike use AI not as a replacement for human intelligence but as a tool for self-expression, empowerment, and democratic participation. This episode is a masterclass in AI ethics, digital sovereignty, and the urgent need to shift from extractive technologies to human-first ecosystems. We hope for a future where data privacy is not just a legal checkbox, but a fundamental principle of technological design and societal infrastructure.
Support the show
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