Author: Paul Mah
Publisher: CDO Trends
Publication Year: 2022
Summary: The following article describes how according to a recent study, over $77.5 billion was invested in artificial intelligence (AI) in 2021. But with the growth of AI, the concern about bias has grown as well. Even though organizations are not actively trying to perpetuate and amplify biases, data has been collected in ways that make this nearly impossible to avoid. And though it is unavoidable, bias is also not something that can be ignored either. Large companies like Google and Microsoft have turned down AI-centric projects due to ethical concerns in the past. The best way to create ethical algorithms and AI projects is to properly educate data scientists as they enter the field. A recent study found that only 17% of data science educators reported to teach ethics, and 22% teach bias. The author also called for more structured guidelines for data ethics to be created. Similar guidelines must be applied in the workplace, too; companies should incorporate data ethics into their trainings and recruitment practices. While AI bias is a very difficult and serious issue to address, intentional and effective practices are a good place to start.