Human Biases Reflected As Computer Biases

Bias: prejudice in favor of or against a thing, person, or group

What is “computer bias”?

The existence of prejudiced outcomes in the decisions or predictions made by computer systems/algorithms. Bias can be implemented into algorithms because of human biases being intentionally inserted or because of the data utilized being biased.

Explicit Data: Information directly provided by user.

Implicit Data: Infomration that can inferred from explicit data.

Based on either explicit/implicit data that has been used to train an algorithm, whether intentionally introduced or during the process of training data generation, bias can be created.

A notable example of this is seen in Netflix, where there are is a human factor that drives bias: Netflix exclusives are placed ahead (a show that is a Netflix exclusive means that users will be more likely to stay with Netflix). The bias in this case is Netflix’s prioritzation towards Netflix-produced shows.

Hack 1:

What is another example of a human bias being implemented into an algorithm?

Answer:

Reducing Bias

Programmers should take action to reduce bias in algorithms used for computing innovations as a way of combating existing human biases. Softwares need to be unbiased, consider all everything, and reject human bias.

Things to consider when developing programs:

  • What are potential sources of bias?
  • Is your program enhancing or intentionally excluding?
  • Are you receiving feedback from a widespread group of people?
  • How could people who differ from you use your developments?

Hack 2:

What is another way a programmer can reduce bias in their softwares?

Answer:

Types of Bias in Software Development

Biases can be embedded at all levels of software development.

It can be intentional or unintentional. Some software development are made for a certain market and ensure that people of certain places or demographics can use them easily. However, this doesn’t mean that they are trying to exclude.

Examples:

Intentional:

  • Games could be geared towards a certain age range (Talking Tom vs Valorant)
    • Game concepts
    • Music
    • Visuals

  • WeChat and KakaoTalk
    • Almost everyone in China uses WeChat
    • KakaoTalk is the Korean version

Unintentional:

  • Social media, Facebook vs. instagram

Hack 3:

What are some other examples of intentional and/or unintentional bias in innovations (games, social media, technology, etc.)?

Answer:

Homework

Question 1:

Define “computer bias” in your own words and explain how it can result from intentional or unintentional factors in software development. Give a brief example of this. Explain how programmers can actively work to reduce bias in their algorithms?

Answer: Computer bias is when a data that computer gets isn’t entirely accurate, as their sources may be varied. A real world example of this is taking data from a survey that is less recent. This could be unintentional, as the computer can’t actually decide for itself whether the data is accurate to today or not and must be verified by humans. Programmers can reduce bias in their algorithms by elimitating all possible sources of bias, and data can be fact checked by multiple people/sources before being used.

Question 2:

Briefly describe the two types of bias in software development and provide examples from the gaming industry and social media platforms. How might biases in software design affect user engagement and experiences?

Answer: There are intentional and unintentional biases in software development. Intentional bias is when something is designed to cataer towards a certain audience: for example, we get emails from colleges because we are high school students and colleges are looking to advertise to our demographic; they wouldn’t bother advertising to someone who’s already in or done with college. Unintentional bias is when the programmers didn’t intend to aim at a certain demographic yet still hit it. For example, the demographic for instagram is heavily focused towards the younger generation, even though it wasn’t entirely. Biases in software design affect user engagement, as these biases will obviously cater towards certain audiences, and these audiences will be more attracted than others.