One major pitfall is machine bias. Thus, if built on subjective data, machines can amplify existing human bias such as racial discrimination. Machine algorithms that are particularly prone to this bias are those used for profiling -- assessing or classifying individuals based on characteristics. Profiling algorithms like risk assessment, job placement and customer segmentation are susceptible to any kind of bias that exists within the data. Aside from machine bias, companies should be cautious of blind spots that may accompany data-driven culture.

Source: Bangkok Post February 20, 2018 21:45 UTC