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Bias in AI is a constant concern because large datasets are not necessarily representative of what they’re supposed to reflect, Irina Raicu, the director of internet ethics at the Markkula Center for Applied Ethics at Santa Clara University, told Lifewire in an email interview. 

Given the complexity of the non-digital world, “large amounts of data” can still mean “incomplete and inaccurate,” Raicu said. “Bias can be expressed even at the level of what we choose to measure--what we choose to turn into data--not just by not including certain variables (or people) in a data set in representative numbers, but also by not developing certain datasets at all.”

Irina Raicu, director of internet ethics, interviewed by LifeWire.