SCIENTIFIC COLLECTIVE and ARTIFICIAL INTELLIGENCE
Big Questions
ABOUT SCIENTIFIC COLLECTIVE INTELLIGENCE and AI
The following questions are emerging from the discussion:
- How can scientific collective intelligence deal with the recent advances in artificial intelligence (AI)? How will it be transformed by these advances? Can AI motivate scientific collective intelligence by posing novel challenges? Can AI provide novel tools for collective intelligence?
- Which incentives can promote scientific collective intelligence?
- What can history and social science contribute to this discussion? How can scientists best communicate with the rest of society about this issue?
- What can we learn by comparing individual human intelligence, artificial intelligence and collective intelligence? Are there general principles of intelligence that might emerge from these comparisons? One example is the concept of attention, that seems to play a role in all these types of intelligence, with different modalities.
- Could the scientific community contribute to train AI systems dedicated to fundamental science and run in the public interest? Human interaction is currently used to train the largest AI models.
- Which important scientific problems could be solved by the synergistic efforts of individual, collective and artificial intelligence?
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ABOUT CELL-CELL COMMUNICATION
The following is a summary of the range of ideas that have originated from discussions with more than 40 biomedical scientists.
Some of these questions can only be answered by large, coordinated projects on cell-cell communication, showing why such collaborations are needed. These questions are connected and addressing them in parallel would provide a clearer picture. We would be able to shed light on a fundamental aspect of biology, with implications ranging from quorum sensing in bacteria to the evolution and development of multicellular organisms. The potential medical benefit is also very strong, given that many existing drugs already act on cellular receptors or ligands.
Important scientific questions:
- Integrating knowledge on functional cellular responses to signals. Decoding cell-cell communication implies associating signals to cells with functional responses. Mapping the detailed functional response of cells, organs and organisms to signals acting on receptors requires specific expertise present in hundreds, perhaps thousands of different labs. An evolutionary approach based on the study of multiple organisms might facilitate this effort.
- Study of signal combinations. Human cells in vivo are bathed in biological fluids containing hundreds of ligands for which the cells have specific receptors. Analyzing hundreds of signals is daunting and the number of possible combinations of signals is so high that an exhaustive experimental study is impossible. It is realistic, however, to identify the more manageable number of naturally occurring combinations of signaling molecules and to elucidate the functional effects of these combinations.
- Communication among tissues and organs. This includes investigating how cell types from different tissues signal to each other and defining the cell-cell communication network at different levels within the whole body.