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.

Realizing Healthcare’s AI Potential

The following insights are derived from a recent session on GenAI in Healthcare. On November 15th, the D^3 Institute’s Generative AI Observatory hosted the first session in its GenAI in Healthcare series, produced in collaboration with the Responsible AI Institute. Speakers Satish Tadikonda (HBS), Nikhil Bhojwani (Recon Strategy), Var Shankar (Responsible AI Institute), and Alyssa […]

Data Contracts: Data Quality for AI

The following insights are derived from a recent Insights from the Field event featuring Chad Sanderson, covering the topic of Data Contracts for achieving high-quality data for Artificial Intelligence (AI). Overview Chad began this session by demystifying some hyperbolic claims in the world of Artificial Intelligence (AI), including the idea that AI models could replace […]

Using Analytics to Find Value in Education Data

The following insights are derived from a recent Assembly talk featuring Hywel Benbow, regarding applying data analytics to enhance the performance of educational institutions. We presented a few question to Hywel during this talk, and what follows is a summary of his responses. Could you speak to some overarching and generalizable ways educational organizations could […]

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Is AI Racist?

AI itself is not inherently racist since it is merely a tool. However, depending on the data and rules it is trained on—both created by humans—it can be used in a racist manner.

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