Join our IOPD Privacy Engineering & Technology Education Discussion (PETed) Series! The format of the webinar will be a recorded 10-minute introduction followed by a 40-minute informal discussion and interaction with members of the IOPD. The goal will be a discussion on how to solve a specific privacy problem or privacy related resource topic and the latest implementation techniques for some of the biggest challenges like synthetic data, zero-knowledge proofs, homomorphic encryption, and translucent databases.

The participants will be asked to bring questions related to the topic. Come back the fourth Thursday of every month for a new discussion, new speaker, and new insights on the most cutting-edge privacy challenges!

Date & Time:

August 22, 2024 @ 12:00 PM EDT / 6:00 PM CEST

Topic:

Explainability by Design: Shaping the Future of AI Accountability and Digital Agency

Synopsis:

Shoshana advocates for the establishment and recognition of digital agency and understanding as a fundamental human right, serving as a reinforcement and guiding principle for the evolving legal frameworks working to keep pace with technological innovation. This right bridges the gaps between requirements around transparency and around mere transparency and the requisite layers of explainability, ensuring AI systems provide meaningful and accessible explanations of their decision-making processes.

She also advocates for the criticality of a time bound global mandate for new technology to be explainable by design by a specific date, and to have a lessened impact on the environment. This mandate would create an incentive for investment in furthering AI technology development to allow the systems to be mightier (to support explainability) and lighter (to facilitate the integration of standards to reduce environmental impact.)

Just as the integration of privacy notices became essential for compliance and trust, and accountability in business transactions, the inevitability of explainability notices and addenda in AI is undeniable. Both businesses and individuals require these notices ( and explainability attendant same) to operate effectively within an AI technology ecosystem. The evolution of privacy laws demonstrated that transparency and accountability are fundamental to building trust and meeting regulatory standards, and analogous mechanisms are needed to facilitate explainability and accountability in business and consumer interactions in the age of AI.

Problem Statement:

Despite current and evolving regulatory frameworks aiming to address transparency and accountability in AI, the rapid advancement of technology continues to expand the gaps between regulatory requirements, the needs of individuals and businesses, and the ability of AI technologies to provide the necessary levels of explainability. These gaps hinder effective oversight, erode the trust of users and impacted individuals, and compromise environmental sustainability. Mandating explainability by design is essential to bridge these gaps, ensuring that AI systems can be transparent, explained, and meet regulatory standards and societal and environmental expectations.

Pre-Discussion Resources:

• • HOME | I Statements (aideiprivacystatements.com) (Explainability by Design Resources are at the bottom of the page.)

• • Explainability Case Studies

• • Explainability Rubric

• • Advancing Explainability through AI Literacy and Design Resources

• • A Taxonomy of Explanations to Support Explainability by Design

• • One proposed approach: Explainability by Design: A Methodology to Support Explanations in Decision-Making Systems (arxiv.org)

• • Explainable Convolutional Neural Networks

Speaker:

Shoshana Rosenberg

Shoshana Rosenberg is a thought leader at the intersection of privacy law and DEI, a seasoned corporate attorney and business executive with a broad global purview and over 16 years in international data protection law. She is also the co-founder of Women in AI Governance and the founder of SafePorter, a PICCASO EU award-winning B Corp enabling privacy-by-design DEI and engagement programs and true data minimization that protects individuals and eliminates organizational data risk around DEI. Shoshana is a founding member and strategic programs advisor at Logical AI Governance, where she developed the PRISM Framework and the AI Governance training programs to enable privacy and compliance professionals to build, operationalize, and refine AI Governance programs. A U.S. Navy veteran, data ethics and emerging technology fanatic, and a member of the IAPP Diversity in Privacy Advisory Board, Shoshana is a passionate advocate for social entrepreneurship and inclusion by design.

Moderator:

Nicole Nguyen

Nicole Nguyen is an enthusiastic privacy professional, deftly bridging technology, business, and law. Beginning in intellectual property and patent prosecution, she gained practical legal insights and technical acumen, which she later applied to data privacy across various regulated industries. She honed her skills across operations, regulatory analysis, and engineering, to streamline data handling, shape privacy policies, and drive privacy-by-design principles. Recognized for her leadership and technical prowess, Nicole guides strategic decisions, resolves complex issues, and bolsters business resilience. Her passion lies in crafting comprehensive data governance programs, weaving security, privacy, and risk disciplines into robust frameworks that safeguard business value and promote a future-ready, privacy-conscious culture. B.S. Chemical and Electrical Engineering and M.S. Information Systems, Cybersecurity and Business Intelligence.

The IOPD Privacy Engineering & Technology Education Discussion (PETed) Series is a members-only event. Join as an Ambassador before the 1st of each month to get invited to this month’s event! Please reach out to a current member to be invited as a guest. If you are already a member, subscribe to our PETed Mailing List for announcements and monthly invitations!