Despite the many benefits reported on the use of emerging technologies like artificial intelligence (AI) and machine learning, the adoption of machine-learning techniques has some researchers worried. This interesting topic came to us from Government CIO Journal in their article, “Machine Learning is Creating a Crisis in Science.”

AI, while powering a lot of scientific research, is also posing a threat. AI and machine learning’s methods have been judged frequently inscrutable, which is creating a “reproducibility crisis” in science because research conducted with AI and machine learning can’t be repeated.

“The question is, ‘Can we really trust the discoveries that are currently being made using machine-learning techniques applied to large data sets?’” asked Rice University statistician Genevera Allen, who recently addressed the crisis at the 2019 Annual Meeting of the American Association for the Advancement of Science (AAAS). Allen said findings generated by machine learning will have to be checked and rechecked until a new generation of AI and machine-learning systems can do it on their own.

Melody K. Smith

Sponsored by Access Innovations, the world leader in thesaurus, ontology, and taxonomy creation and metadata application.