This talk talk has a single objective: to advocate for machine learning infused with social purpose. Social purpose here is an invitation to deepen our inquiries as investigators and inventors into the relationships between machine learning, our planet, and each other. In this way, social purpose transforms our field of machine learning: into something that is both technical and social. And my belief is that machine learning with social purpose will provide the passion and momentum for the contributions that are needed in overcoming the myriad of global challenges and in achieving our global goals. To make this all concrete, the talk will have three parts: machine learning for the Earth systems, sociotechnical AI, and strengthening global communities. And we’ll cover topics on generative models; evaluations and experts; healthcare and climate; fairness, ethics and safety; and bias and global inclusion. By the end, I hope we’ll have set the scene for a rich discussion on our responsibility and agency as researchers, and new ways of driving machine learning with social purpose.