Artificial Intelligence is already playing a huge role across the financial services sector, the medical profession, the world of recruitment and many other important areas. However, current AI only works well if the right information is used to train it. But when humans are the ones collecting that information, it opens the door to bias. So how do we ensure debiasing in AI?

Understanding the process

AI is not yet able to think for itself, therefore, human assistance is required in assembling the necessary data it needs. It’s a bit like programming any other computer in the sense we only get good results or correct decisions from the right information and correctly organized. Get this wrong and the results can be devastating. 

For example, in training recruitment algorithms based on historical data, we had AI that favored young, white men and exclude women and people of color. In short, the training data here was clearly wrong and biased. Understanding this can help us begin the debiasing process as some models will need vast amounts of data to help them make sense of the world. Something as simple as getting the correct associated metadata linked to demographics is vital. 

Asking the all-important questions?

 

Full article: https://tbtech.co/innovativetech/artificial-intelligence/how-can-we-debias-artificial-intelligence/

 

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