Scientists Press AI Researchers for Transparency #Sciencefather #professors #researchawards

An international group of scientists is demanding scientific journals demand more transparency from researchers in computer-related areas when accepting their reports for publication.

They also want computational researchers to include information about their code, models, and computational environments in published reports.

Their call, published in Nature Magazine in October, was in response to the results of research conducted by Google Health that was published in Nature last January.

The research claimed an artificial intelligence system was faster and more accurate at screening for breast cancer than human radiologists.

Google funded the study, which was led by Google Scholar Scott McKinney and other Google employees.

   


Criticisms of the Google Study

“In their study, McKinney et al. showed the high potential of artificial intelligence for breast cancer screening,” the international group of scientists, led by Benjamin Haibe-Kains, of the University of Toronto, stated.

“However, the lack of detailed methods and computer code undermines its scientific value. This shortcoming limits the evidence required for others to prospectively validate and clinically implement such technologies.”Scientific progress depends on the ability of independent researchers to scrutinize the results of a research study, reproduce its main results using its materials, and build upon them in future studies, the scientists said, citing Nature Magazine’s policies.

McKinney and his co-authors stated that it was not feasible to release the code used for training the models because it has a large number of dependencies on internal tooling, infrastructure, and hardware, Haibe-Kains’ group noted.

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