Risks of Letting AI Experts Experiment with Healthcare

"We do not want schizophrenia researchers knowing a lot about software engineering," said Amy Winecoff, data scientist and Princeton's Centre for IT Policy. Research asserts that a basic understanding of machine learning and other software engineering principles might be a desirable trait for medical practitioners, but these skills should not come at the expense of expertise in domain knowledge. Many new startups and enterprises sell their products boasting about incorporating AI/ML techniques in the development. Though this is an issue in the developer and business market, the bigger worry is misapplied AI/ML algorithms in the field of science and healthcare as it causes real world consequences. Sayash Kapoor and Arvind Narayanan of Princeton University published a research paper--Leakage and the Reproducibility Crisis in ML-based Science, pointing out the problem of "data leakage" in various researches using pools of data to train and test their development's performance.