To expand the cellcomm.org AI discussion and encourage participation of early career scientists, Zinia Charlotte Dsouza and Cristiana Dondi, the chairs of the SPB-Science Network (the society of postdocs and students), along with Guy Salvesen and Giovanni Paternostro have hosted a Roundtable on the AI Revolution in Science at Sanford Burnham Prebys in La Jolla, on October 22, 2024. Invited speakers were Giorgio Quer (Scripps), Talmo Pereira (Salk), Sanjeev Ranade (SBP), Karen Mei (UCSD), Ani Deshpande (SBP), Will Wang (SBP) and Sanju Sinha (SBP).
The following question, emerged from previous discussions and surveys, has been addressed by recent Interviews and by the roundtable participants:
What could be achieved if there was a public or nonprofit AI effort with the same scale and level of funding as the current large private efforts? What would be the benefits for society?
This question can only be answered by a wide and open sharing and integration of ideas by the scientific community.
The in-person roundtable presentations and Q & A can be read on this page.
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Thank you very much for this very stimulating event!
Even as a humanistic researcher without any training in “dry” or “wet” science, I learned so much from this discussion about the capacity of AI to analyze large data sets and the amazing breakthrough discoveries that can come from this capacity.
I also appreciated very much that all of you are concerned about relations of research in the world of AI and about how communication habits might change with AI.
My questions have to do with the ways in which I hope communication habits might change in the direction of broadening the community of researchers:
In the building and training of large language models and algorithms for analyzing large data sets, are we masking the artisanal work of scientists (i.e., what they make) and their relations of research?
When scientists no longer affect the behavior of animals (as in the case of unbiased imaging) but still continue to quantify the animals' movements and behavior, do we lose an understanding of social interaction?
Once scientists are able to accelerate classifications (based on larger data sets), will it become more difficult to discover new categories? or to make unexpected connections (an important component of breakthrough science)?
As I listened to you all expressing yourselves in the “hottest coding language – English,” I wondered how different modes of thinking and discovery might come to the fore from scientists thinking in other verbal languages besides English, as every verbal language is grounded in a different culture and history.
So, my biggest question and challenge would be:
As you use AI to “look beyond,” are you able to imagine a role for researchers who are neither “dry” or “wet” scientists, but researchers in language and culture? To me, imagining and creating such a role would truly revolutionize research! And the imagining could begin quite simply by inviting interested language researchers into the conversation (like you did on Oct. 22), thereby widening the circle of relevant phenomena.