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 refers to the presence of unfair or prejudiced outcomes in the decisions or actions taken by a computer system. Intentional factors occur when the people designing and developing the software knowingly introduce bias, either due to personal beliefs or external pressures. For example, if a developer has a bias against a certain demographic, they might unknowingly encode that bias into the algorithms they create. Unintentional factors, on the other hand, often stem from oversight or lack of awareness. For instance, if a facial recognition system is trained mostly on data from a specific ethnicity, it may perform poorly on individuals from other ethnic backgrounds. Programmers can reduce bias by Diverse and Representative Data or Regular Audits and Testing.

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: Intentional Bias: Definition: Deliberate inclusion of prejudices or preferences in the development process. Example: A game developer intentionally designs non-playable characters to perpetuate gender stereotypes, reinforcing traditional roles or presenting certain groups in a negative light to align with personal beliefs.

Unintentional Bias: Definition: Bias that emerges inadvertently, often due to flawed data, insufficient diversity, or unnoticed algorithmic patterns. Example: In a game character customization feature, unintentional bias may arise if the available options are limited and do not represent a diverse range of skin tones, body types, or gender identities, inadvertently excluding certain players.

Exclusion and Alienation: Effect: Biased design may inadvertently exclude certain user groups, making them feel alienated or underrepresented.

Unfair Treatment: Effect: Biased algorithms or design choices may result in unfair or discriminatory outcomes for certain users.