Speaking at the “Generative AI: Shaping the Future” symposium on Nov. 28, the kickoff event of MIT’s Generative AI Week, keynote speaker and iRobot co-founder Rodney Brooks warned against overestimating the capabilities of this emerging technology. Generative AI refers to machine-learning models that learn to generate new material that looks like the data they were trained on. These models have exhibited some incredible capabilities, such as producing human-like creative writing, translating languages, generating functional computer code, and crafting realistic images from text prompts.
In her opening remarks to launch the symposium, MIT President Sally Kornbluth highlighted several projects faculty and students have undertaken to use generative AI to make a positive impact in the world. The Institute also recently announced seed grants for 27 interdisciplinary faculty research projects centered on how AI will transform people’s lives across society.
While generative AI holds the potential to help solve some of the planet’s most pressing problems, the emergence of these powerful machine learning models has blurred the distinction between science fiction and reality, said CSAIL Director Daniela Rus in her opening remarks. MIT hopes to not only showcase this type of innovation, but also generate “collaborative collisions” among attendees.
In his keynote remarks, Brooks sought to unpack some of the deep, scientific questions surrounding generative AI, as well as explore what the technology can tell us about ourselves. While researchers still don’t fully understand exactly how these models work, the seemingly incredible capabilities of generative AI are not magic, and it doesn’t mean these models can do anything. His biggest fears about generative AI don’t revolve around models that could someday surpass human intelligence. Rather, he is most worried about researchers who may throw away decades of excellent work that was nearing a breakthrough.
Following Brooks’ presentation, a group of MIT faculty spoke about their work using generative AI and participated in a panel discussion about future advances, important but underexplored research topics, and the challenges of AI regulation and policy.
In conclusion, the symposium emphasized the importance of engaging with policymakers and the public to ensure generative AI tools are produced and deployed responsibly.