In Boston last week, the International Association of Privacy Professionals (IAPP) hosted a pioneering conference on AI Governance, drawing a full house of legal and technological experts, including tech policy advisors from across the globe. The conference delved into the evolving role of AI in the realms of law and technology, focusing on how current regulatory measures might adapt to the burgeoning presence of artificial intelligence.
Embracing Humanity in the Age of AI
A prevailing theme at the conference was the concern over AI’s potential to usurp human jobs, particularly in sectors characterized by intellectual labor. Keynote speaker Kevin Roose, a New York Times tech columnist, emphasized that despite these fears, certain inherently human job elements—labeled as Surprising, Social, and Scarce—are less likely to be overtaken by AI.
Roose elaborated that jobs involving unpredictable daily chaos, those centered around personal care or emotional engagement, and roles with little margin for error, such as emergency response, would remain predominantly human. He urged professionals to strengthen these aspects within their careers and advocated for organizations to “outsource chores to AI, not choices,” thereby reinforcing their uniquely human value.
Proactive Measures with Algorithmic Audits
The conference spotlighted the importance of algorithmic audits as a proactive step for businesses navigating AI compliance. Cathy O’Neil, CEO of O’Neil Risk Consulting & Algorithmic Auditing, likened the state of AI algorithms to “an airplane without a cockpit,” emphasizing the necessity for controls to prevent potential disasters. These audits, involving thorough data analysis and cross-departmental interviews, serve as a crucial process to identify biases and vulnerabilities within AI algorithms, preparing companies for both regulatory scrutiny and future litigation.
Ethics in AI: A Business Imperative
Ethical AI practices are rapidly becoming central to corporate strategy, as exemplified by companies like Mastercard and Pfizer. These businesses no longer see AI governance merely as a compliance hurdle but as an essential business function. Mastercard, for example, includes privacy and data experts in AI product design discussions from the outset, integrating ethical considerations into their operational workflow.
The ethical challenges are particularly pronounced in areas such as fraud detection, where transparency needs to be balanced against the risk of exposing AI systems to manipulation. Mastercard has responded by excluding potentially bias-inducing data, such as personal identifiers, from their algorithm training sets, raising complex questions about the trade-offs between data privacy, algorithmic efficacy, and ethical governance.
As AI continues to shape industries and redefine privacy boundaries, the insights from the IAPP AI Governance Global conference underscore the pressing need for a multidimensional approach to AI management—one that encompasses regulatory foresight, proactive auditing, and a deep-rooted commitment to ethics in innovation.
