Artificial intelligence (AI) excels at finding patterns like unusual human behavior or abnormal incidents. It can also reflect human flaws and inconsistencies, including 180 known types of bias. Biased AI is everywhere, and like humans, it can discriminate against gender, race, age, disability and ideology.

AI bias has enormous potential to negatively affect women, minorities, the disabled, the elderly and other groups. Computer vision has more issues with false-positive facial identification for women and people of color, according to research by MIT and Stanford University.

Sixty-three percent of organizations will deploy artificial intelligence in at least one area of cybersecurity this year, according to Capgemini. AI can scale security and augment human skills, but it can also create risks. Cybersecurity AI requires diverse data and context to act effectively, which is only possible with diverse cyber teams who recognize subtle examples of bias in security algorithms. The cybersecurity diversity problem isn’t new, but it’s about to create huge issues with biased cybersecurity AI if left unchecked.

Read more: Biased AI Is Another Sign We Need to Solve the Cybersecurity Diversity Problem (securityintelligence.com)