Member-only story
What Is Algorithmic Bias in AI and How Can We Fix It?
As we depend more on AI for decision-making, we must confront the growing challenge of algorithmic bias — its causes, its real-world impact, and how we can reduce it.
The more we use AI algorithms to discover patterns or generate insights just to help us make decisions, the more we should be concerned with the impact of algorithmic bias. So, what is it and how can we minimize it?
Algorithmic bias can lead to harmful decisions and actions that cause machine learning algorithms to produce unfair or discriminatory outcomes. It’s something we want to avoid. There are some causes that occure algorithmic bias.
Let’s point out to the causes
Algorithmic bias is not necessarily caused by the AI algorithms themselves, but by how data is collected and coded. Here I am pointing to …
Bad Data
The most obvious is biases that occur in the actual training dataset itself. That data is in some other way a misrepresentation of the ground truth. It can also be data that is incorrectly classified, causing the algorithm to misunderstand what the data represents, and a little…
