Ten questions to AI regarding the present and future of proteomics - Stransky, Stephanie; Sun, Yan; Shi, Xuyan; Sidoli, Simone (Frontiers in Molecular Biosciences, 2023)
The role of a scientist is at first not so different from a philosopher. They both need to question common thinking and evaluate whether reality is not as we always thought. Based on this, we need to design hypotheses, experiments, and analyses to prove our alternative vision. Artificial Intelligence (AI) is rapidly moving from an “assistant” into a proper “colleague” for literature mining, data analysis and interpretation, and literally having (almost) real scientific conversations. However, being AI based on existing information, if we rely on it excessively will we still be able to question the status quo? In this article, we are particularly interested in discussing the future of proteomics and mass spectrometry with our new electronic collaborator. We leave to the reader the judgement whether the answers we received are satisfactory or superficial. What we were mostly interested in was laying down what we think are critical questions that the proteomics community should occasionally ask to itself. Proteomics has been around for more than 30 years, but it is still missing a few critical steps to fully address its promises as being the new genomics for clinical diagnostics and fundamental science, while becoming a user-friendly tool for every lab. Will we get there with the help of AI? And will these answers change in a short period, as AI continues to advance?