Researcher Proposes Collectivist Approach to AI Development

• Michael I. Jordan challenges the individualistic focus of AI development.
• His research proposes a collectivist, economic perspective prioritizing social welfare.
• The research was submitted on July 8, 2025, via arXiv.
• Jordan critiques Silicon Valley’s AI approach for neglecting social aspects.
• New economic mechanisms for marketing systems could reshape digital advertising.

Jordan’s Research Proposes a New Framework for AI Development

A new perspective on artificial intelligence development is shaking up the foundations of how it’s approached. Leading researcher Michael I. Jordan at UC Berkeley and Inria Paris is proposing a shift from the prevailing individualistic mindset to a more collectivist approach that places social welfare at its center. In his recently submitted research paper dated July 8, 2025, he lays out an extensive critique of the Silicon Valley paradigm that has dominated recent AI advances, insisting that social aspects should be foundational, rather than treated as an afterthought.

Critique of Individualism in Silicon Valley AI

In this 11-page work published on arXiv, which received support from the European Union’s ERC-2022-SYG-OCEAN initiative, Jordan argues that humans are inherently social beings. He asserts that today’s AI systems overlook this fundamental aspect of humanity, with a narrow focus on technology devoid of social context. “Humans are social animals, and much of our intelligence is social and cultural in origin,” the paper argues, pushing back against ongoing trends in marketing and technology that emphasize individual gains over community benefits.

Designing Fair Economies in Digital Marketing

Jordan’s critique comes at a time when marketing professionals are rapidly adopting artificial intelligence—Mediaocean reports show a dramatic increase from 55% in 2023 to 75% in 2024 for generative AI use among marketers. But, Jordan warns, these advancements may be missing critical social elements that truly connect technology with users. His work focuses on multi-way market models, suggesting a new structure where musicians, listeners, and brands interact directly. For example, in his proposed three-way market for music, brands seeking songs would directly compensate artists through machine learning recommendations, a stark departure from the traditional streaming platforms where artists are often left scrambling for visibility amidst systemized profit mechanisms. This could foster a more equitable environment for content creators while shaping the future of digital advertising.

Michael I. Jordan’s ambitious research lays out a foundational rethinking of AI development that prioritizes social welfare over individualistic pursuits. By emphasizing the inherently social nature of human intelligence, he critiques the prevailing Silicon Valley norms and suggests a framework for integrating economic principles in digital marketing. His proposals could not only address current challenges in consumer trust and creator economies but also reshape the very fabric of AI systems that continue to evolve at a startling pace.