Global Data Science Forum

An Epidemic of ML Misinformation

By Michael Mansour posted Mon January 06, 2020 02:54 AM


An Epidemic of ML Misinformation



Covering the news and developments in AI is hard. People are quick to trumpet technological advances as the next great discovery, and slow to understand the limitations that may prevent that from being true. Check out our Spotlight where Gary Marcus discusses the epidemic.


Sobering up AI hype in the ML industry is sorely needed, and this article brings up very good points about the misaligned incentives behind suggesting that an ML algorithm’s impact is more remarkable than reality.  However, Marcus’s unique brand of AI criticism deserves a healthy dose of skepticism in turn. From his “AI can’t fix fake news” op-ed last year to his Rebooting AI book, Marcus leaves industry experts with the impression that unless a Machine Learning algorithm generates results that are bulletproof (e.g. detect all fake news with perfect F1, or leave no room for a Turning tester to doubt they are talking to a machine) as opposed to results that are merely statistically significant, then it’s not a worthwhile result.  The truth likely lies somewhere between the poles of AI hype and Marcus’s hyper-cynicism.