The issue is not that the column takes AI seriously; higher education should take AI seriously. The issue is that it mistakes machine-generated prescription for human judgment and acceleration for destiny.
"That requires a bunch of people to go take things that folks here are figuring out and [explain them] to the rest of the world," said Jeffrey Ladish, emphasizing the need for effective communication about AI risks.
Martschenko's argument is largely that genetic research and data have almost always been used thus far as a justification to further entrench extant social inequalities. But we know the solutions to many of the injustices in our world-trying to lift people out of poverty, for example-and we certainly don't need more genetic research to implement them. Trejo's point is largely that more information is generally better than less.
Biology is undergoing a transformation. After centuries of studying life as it evolves naturally, researchers are now using a combination of computation and genome engineering to intervene, generating new proteins and even whole bacteria from scratch. The use of artificial-intelligence tools to design biological components, an approach known as generative biology, is set to turbocharge this area of research. Just last year, scientists used AI-assisted design to produce artificial genes that can be expressed in mammalian cells.