Responsible AI / Panelist

Jeremy King


United States

Jeremy King is senior vice president of technology at Pinterest, where he leads the company’s technical vision and the engineering organization responsible for building and scaling a visual discovery engine.

Before joining Pinterest, he was CTO and senior vice president at Walmart, where he led the team responsible for the technology behind U.S. retail stores and e-commerce for Walmart and Jet, and oversaw customer, merchant and supply chain technologies across cloud and data platforms. King has also held executive-level technology roles at Walmart Labs, LiveOps, and eBay.

Voting History

Statement Response
Most RAI programs are unprepared to address the risks of new generative AI tools. Agree “Most responsible AI programs are still very new and focused on building inclusive teams to address ethical AI practices. The innovation of generative AI is moving rapidly, and while there is much optimism for how this new technology can contribute to critical breakthroughs, there is still much testing to do. Clearly marking developments with “beta” or “demo” will help manage the ambiguity through testing periods.

Further, basic testing and tools must be set to validate whether innovations are ready for the wider public. This new technology is powerful; therefore, we must be thoughtful in our approach to using it to ensure that we’re taking the most strategic and responsible approach to harnessing its power and capabilities.”
Mature RAI programs minimize AI system failures. Agree “Building responsible AI programs gives us an opportunity to bring new innovation to our platforms. A big reason why RAI programs help minimize any system failures is because of the inclusive data set that we are pulling from to build these programs. With RAI, it’s important that we are building them in a way that best serves all groups and communities that will be using them. The data is key here; when we are collecting data correctly, we are able to build more personalized programs that we know will serve the audiences we are building them for, ultimately minimizing the margin for system failures.”
RAI constrains AI-related innovation. Strongly disagree “We’re building artificial intelligence technology for the benefit of mankind, so AI constraints need to be part of the design. RAI allows us to pose more interesting research questions and learn how to collect data correctly while also ensuring that we are not marginalizing groups and communities. It doesn’t limit innovation; rather, it creates more, which requires additional expertise.”