Saturday, March 28, 2020

What data should AI be trained on to avoid bias? – JAXenter

Humans are introducing their own biases and prejudices into machine learning. As advanced as AI can be, having been built by humans, it can still share some of our own ethical shortcomings. The usage of proper databases during training is one of the ways to help prevent biases from developing within artificial intelligence.

As AI and machine learning permeate every sphere of our lives today, it gets easier to celebrate these technologies. From entertainment to customer support to law enforcement, they provide humans with considerable help. Certain things they are capable of are so amazing that they seem almost like magic to an outside observer.

However, it’s necessary to remember that as astonishing as machine learning-powered tech advancements are, they are still a product created by us, humans. And we can’t simply shed our personalities when developing anything, much less an AI – an algorithm that has to think on its own. While developers’ personal experiences and beliefs are an indispensable asset in creating ML algorithms, alas, they come at a cost sometimes.

SEE ALSO: The Limitations of Machine Learning

A brief overview of bias in AI

No AI, sadly,


Prakash is a tech freak, passionate about every new gadget and technology that comes his way. Always searching, always curios, he managed to gather an astounding experience that is very useful in his journalistic career.

You may also like

Don't Miss

More from Author