The recent decision by OpenAI to release their latest model, GPT-4o, despite concerns from expert testers, highlights a fundamental challenge in the field of Artificial Intelligence: the need for a more multidisciplinary approach. OpenAI’s choice to prioritize speed in releasing their new model over addressing the testers’ concerns underscores a broader trend within the AI community. There is an increasing recognition that modern AI development demands insights and expertise from a diverse range of fields, far beyond just mathematics and computer science. Traditionally, the AI industry has been heavily dominated by these areas, relying on technical skills to drive innovations. However, as AI systems like GPT-4o play larger roles in our society, it is becoming evident that a narrow focus could lead to pitfalls, including ethical concerns, bias, and unforeseen social implications. Incorporating insights from social sciences, humanities, and other fields can equip AI developers with a broader perspective, enabling them to design systems that are not only technically sound but also socially responsible. For instance, the inclusion of ethics experts could help identify and mitigate biases within AI models, while insights from linguists could enhance natural language processing capabilities to account for cultural nuances and variations. By fostering collaboration across disciplines, AI developers can create more holistic systems that better serve their intended purposes. This approach not only benefits companies by potentially averting controversies and criticisms but also serves the public interest by producing AI technologies that truly align with societal needs and values. As we move further into an era where Artificial Intelligence pervades every aspect of life, it is crucial that we adopt development practices that draw from a diverse pool of knowledge. This will ensure that AI serves as a tool for improvement and equity rather than perpetuating existing divides.