Seven Ways to Avoid Bias in Your Data

AI is taking off in all areas of business and in our daily lives – from improving agriculture and predicting where forest fires might erupt to determining who is likely to return to a hospital after discharge. With advanced GPUs that can crunch more data faster and growing demand from companies looking to increase competitive advantage, machine learning and other forms of AI are expected to become more pervasive. Today, many companies are relying on smart apps to provide the insight needed to make decisions that can affect people's lives, such as who qualifies for a mortgage or who will be insured. Because of this responsibility, it's more important than ever that data professionals don't inadvertently automate any biases into the AI algorithm because of the data they use or don't use, and how they use it. While AI should be regulated to ensure the fair and ethical use of data, particularly as it impacts decision-making and people's lives, unfortunately, we still have a long way to go before this happens.