Bias is when something consistently strays from what’s considered normal or standard. For example, bias in statistics can refer to when a sample group might not accurately represent the whole population, or in ethics it can refer to when a group is favored over another. There are many other ways bias can show up.

Algorithmic bias is when bias happens within a computer program or system. This is often talked about in relation to systems that operate on their own, like artificial intelligence.

There are several ways algorithmic bias can happen:

• Biases in the data used to train the system. For example, a program that translates text might be biased if the data it was trained on wasn’t good enough in one of the languages it’s translating.
• Biases in what information is included or left out of the system. For example, a program that predicts who will miss doctor appointments might unfairly target poor people, racial minorities, or people living in rural areas if it includes data on race, income, or distance from a medical center.
• Biases introduced to fix other issues with the system. For example, a programmer might add new biases to try to balance out the original unfairness in the program that predicts doctor appointment no-shows.
• Biases caused by using the system in a different context than it was designed for. For example, a program designed for use in the United States might not work well in a different legal, social, or economic context.
• Biases in how the system’s results are interpreted. For example, the person using the program might not fully understand what the program’s results mean and might make assumptions or decisions that aren’t reasonable.

When you hear the word “bias,” it’s important to understand what the person using the word means. Also, remember that bias doesn’t always mean someone did something wrong or prejudiced. People using computer systems should always be aware of potential sources of bias and stay involved in making decisions, no matter what area they’re working in.