No-code, low-code (horizontal) machine learning platforms are useful at scaling data science in an enterprise. Still, as many organizations are now finding out, there are so many ways that data science can go wrong in solving new problems. Zillow experienced billions of dollars in losses buying houses using a flawed data-driven home valuation model. Data-driven human resources technology, especially when based off facial recognition software, has been shown to bias hiring decisions against protected classes. While automation is a great tool to have in your arsenal, you need to consider the challenges before utilizing a horizontal ML platform.
Full story : No-Code, Low-Code Machine Learning Platforms Still Require People.
