Machine-first FAIR: Realigning academic data for the AI research revolution
Mark Hahnel
The best way for humankind to benefit from research is to prioritize machines over people when sharing data. Here’s why.
We push out the lines that academic research needs to be Findable, Accessible, Interoperable and Re-usable (FAIR) for humans and machines. This suggests humans and machines should get equal priority when it comes to FAIR. This is not the case, we should prioritize the machines. Machine-generated new knowledge will accelerate knowledge discovery.
While humans can infer...