Data, Privacy, Security, and Regulation

In an era dominated by oceans of data, D^3 hosts a community of practice that offers a discerning perspective on the intricate tapestry of data governance, privacy, security, and regulatory compliance. Participants in this community engage in a comprehensive discourse amongst industry experts, exploring responsible AI and the dynamic realm of regulations, industry standards, and best practices. The community explores how to harness the immense potential of data for strategic business advancement while ensuring the safeguarding of sensitive information, upholding privacy rights, and establishing or integrating resilient and ethical frameworks that underpin success in data-driven endeavors.

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8 Questions About Using AI Responsibly, Answered

How to avoid pitfalls around data privacy, bias, misinformation, generative AI, and more. While the question of how organizations can (and should) use AI isn’t a new one, the stakes and urgency of finding answers have skyrocketed with the release of ChatGPT, Midjourney, and other generative AI tools. Everywhere, people are wondering: How can we use AI […]

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10x’ing DEI: a focus on product and communities

Drawing from her wide experiences across the UK Parliament, British media, YouTube, Google, and Snap Inc., Oona King shares how we can leverage tech’s problem-solving mindset to drive DEI progress, her vision for open-sourcing DEI, and the next big leap for DEI — more deeply understanding how product plays into the space.

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Mike Luca on the role experiments play in addressing discrimination

In this episode, we speak with Harvard Business School Professor Mike Luca about the role of platform design choices in reinforcing discrimination, how data experiments offer insights for managers, and what the future could hold if organizations continue to pay attention to these issues.

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Brandeis Marshall on the potential for data equity

In this episode, we speak with Dr. Brandeis Marshall from DataedX about the consequences of data inequity, the balancing act of qualitative and quantitative mindsets, and critical importance of humanizing data systems.

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