There’s been a lot of talk recently about how IBM is busy attempting to monetise its Watson supercomputer by finding practical and real-world areas in which it can deploy its ‘learning abilities’, and IBM believes one of these areas is the medical field, specifically by helping doctors with their diagnoses. The company sees Watson especially adding value in low-income areas where access to collaborative medicine is restricted.
However, not everybody is convinced it seems.
Whilst the Wall Street Journal reports that the company is having difficulty making money off Watson, with income falling well below projected estimates, are researchers are now starting to doubt Watson’s efficacy outside of the Jeopardy gameshow?
Klaus-Peter Adlassnig is a computer scientist at the Medical University of Vienna and the editor-in-chief of the journal Artificial Intelligence in Medicine. The problem with Watson, as he sees it, is that it’s essentially a really good search engine that can answer questions posed in natural language. Over time, Watson does learn from its mistakes, but Adlassnig suspects that the sort of knowledge Watson acquires from medical texts and case studies is “very flat and very broad.” In a clinical setting, the computer would make for a very thorough but cripplingly literal-minded doctor—not necessarily the most valuable addition to a medical staff.
To be useful in real-world medicine today, Adlassnig suggests, IBM would be better served designing tools to help inform doctors’ own clinical evaluations. Watson’s competition in that niche would be the database PubMed and, of course, Google.
– This blog post is adapted from a Bloomberg Businessweek article.