Mitigating Bias in Artificial Intelligence

Artificial intelligence (AI) has become a major part of our lives. Each time you ask Siri or Alexa to complete a task, you are using AI. In addition, AI counts up the number of “likes” and the types of accounts that you follow to recommend pages in the explore tab of Instagram. Facial recognition software, an AI application used by law enforcement has been used to help solve crimes. However, due to high error rates in the AI algorithms, innocent minorities have been arrested. Some critics say there's a concerning lack of diversity among those who create AI software, and that is causing some of the biases found in artificial intelligence. These biases are also harmful for women and older adults who may be discriminated against when AI is used in the hiring process.  Listed below are steps to take to mitigate biases in artificial intelligence.

Mitigating bias

1.       Assemble a diverse developer team to build machine learning algorithms.

2.       Demographic data used in AI algorithms should account for gender, race, and age.

3.       Use objectively measured data to train the AI algorithms instead of historical data.

4.       Consistently monitor the data and outcomes produced by AI to detect potential biases.

5.       Stay current on the latest developments in AI and how to avoid biases.

Artificial intelligence will benefit society effectively if we consistently consider the impacts of it on all citizens.