Mark Zuckerberg’s latest ambition—building artificial general intelligence (AGI)—has sparked both excitement and concern.
At the heart of this initiative is Meta Superintelligence Labs (MSL), a newly formed division tasked with developing AI systems that could one day surpass human intelligence in reasoning, creativity, and emotional understanding.
But while the technical goals are lofty, the composition of the team behind them has raised serious questions.
Zuckerberg has assembled what many in the tech world are calling a “dream team”: 18 elite researchers and engineers, many of whom hail from OpenAI, Google, Anthropic, and Apple.
These individuals are undeniably brilliant, with impressive credentials and experience at the forefront of AI innovation.
However, the team’s makeup reveals a troubling lack of diversity. Of the 18 confirmed members, only one is a woman. There are no Black or Latino researchers. Most of the team members share similar educational backgrounds, professional networks, and cultural perspectives.
This homogeneity is not just a matter of optics—it’s a structural concern. When building a system as powerful and influential as superintelligence, the values, assumptions, and lived experiences of its creators inevitably shape the algorithms.
A narrow worldview embedded in AI design can lead to biased outcomes, reinforcing existing inequalities rather than dismantling them.
History offers cautionary tales. Facial recognition systems have struggled to accurately identify people with darker skin tones. Chatbots have produced racist or sexist responses.
These failures stem from blind spots in the development process—blind spots that diverse teams are better equipped to identify and correct.
Zuckerberg’s silence on the diversity issue has been notable. In an era where discussions about inclusion are often dismissed as distractions, many tech leaders avoid addressing the topic altogether.
But ignoring it doesn’t make the problem go away. If Meta’s superintelligence is to serve all of humanity, it must be built by a team that reflects humanity’s full spectrum.
The stakes are high. Superintelligent AI could revolutionize medicine, education, climate science, and more.
But it could also deepen surveillance, automate discrimination, and reshape labor markets in ways that disproportionately harm marginalized communities. Ensuring that these systems are inclusive by design is not just ethical—it’s essential.
Meta claims to be building AI “for everyone.” Yet its staffing choices suggest otherwise. The future of intelligence shouldn’t be shaped by a select few.
It should be a collective endeavor, informed by a rich tapestry of perspectives. Otherwise, we risk creating machines that understand only a fraction of what it means to be human.