Analysis: Examining AI Regulation Implementation at Mastercard
Mastercard's AI Governance Strategy: Mitigating Bias and Ensuring Transparency
In the ever-evolving landscape of artificial intelligence (AI), Mastercard has been at the forefront of ensuring responsible AI design and governance. John Hearty, Vice President and Head of AI Governance at Mastercard, is leading this charge, recognised as an expert in the field.
Hearty's team at Mastercard has been instrumental in mitigating bias, ensuring efficacy, and enabling transparency in AI. Over the years, the number of AI systems that the team needs to assess, guide, and monitor has been on a steady upward trajectory. Remarkably, the number has doubled every year until 2024, when it increased by an additional 60%.
To manage this growth, Hearty implemented an AI governance strategy in early 2022. The strategy focuses on building internal sources of influence and making compliance easy. A key aspect of this strategy is the requirement for a product owner to complete a scorecard before a system is built or a contract is signed. This scorecard helps identify potential risks.
Mastercard's small team of five specialists covers a lot of ground in AI governance. They work closely with major banks to understand how their models perform and address model risk management teams' concerns. In partnership with a data science team, they have developed a model documentation template for customers.
The team has also collaborated with developer peers to review its proposed AI governance framework and worked together on bias testing an API to distribute to the company. They have created an API for bias testing and mitigation requirements for large language models.
However, the journey in AI governance is not without its challenges. The International Association of Privacy Professionals (IAPP) finds that one significant challenge is access to qualified AI governance talent and skills in the workforce. Hearty emphasises the importance of hiring for specific behaviours, such as curiosity and self-awareness, to build a cohesive and effective team.
Despite the challenges, the efforts of Mastercard's AI governance team are not going unnoticed. Nearly 90% of organisations using AI are working on AI governance, according to IAPP. The best partnerships, according to Hearty, are structured to provide value to both parties and address others' pain points.
In conclusion, the lynchpin of AI governance is issuing guidance regarding risks associated with a given AI project. With the right resources, even a small team can have an outsized impact in AI governance, as demonstrated by Mastercard's success in this area.
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