The Truth about Machine Learning: What It Is And Isn’t, What It Can And Can’t Do
AI Business featured several quotes from Franz’s CEO Jans Aasman:
Machine learning is regarded in a variety of ways: the enterprise-wide savior of horizontal business problems, the synonym for artificial intelligence, and even the pathway to a future of intelligent machines rivaling humans.
In reality, however, machine learning is a statistical methodology for determining patterns based on previous and current data, which it learns from to provide future results in the form of predictions. It’s a single branch of AI and, as useful as this technology is, it has its share of flaws. Machine learning models show an undue propensity towards bias.Complicated models struggle with issues of explainability, and in several instances these issues are exacerbated by deep learning applications.
According to Franz CEO Jans Aasman, many of these shortcomings are aggravated by people being quick to accept machine learning’s results without necessarily understanding why they were given. “The why part is the thing with explainability,” says Aasman. “Explainability is about why [models produce their particular results].”
Read the full article at AI Business.