Types of Computing Bias - Tarun
- Data Bias: The data does not accurently represent the values of the real world ex. If data is taken from a sample size that doesn’t reflect the actual population - If you wanted data to represent the population in America but your sample that is being surveyed is from a Texas. The population in Texas does not accurately reflect the entire population of America.
- Human Bias: Those who make programs may be influenced by their own biases ex. If a development team are experts in using a certain language and their algorithm demonstrates that language, they will feel that people who specialize in that language are qualified and better. This is essentially bringing in their personal biases and applying to a larger amount of people.
Explicit data vs Implicit data: - Pranavi
Explicit data:
- takes the data that you give
- When watching a video, and it asks “are you enjoying this?”, and you respond with either a thumbs up or down, you are giving them explicit data
Implicit data:
- When you watch or search up certain things, data can be deduced on what is the “norm” for the person
Example: Netflix
- When browsing through Netflix, they show Netflix exclusives, they do this because they want your subscriptions
- showing the netflix exclusives is the bias in this scenario
Popcorn Hack:
In what other applications could have intential bias?
Intentional Bias vs Unintentional Bias - Tanvi
Example 1: Hypothetical Loan company
- Suppose a software was created to assist loan officers, and certain trends of successful loans were taken
- If people are rejected of those who don’t fit in their trends of either age, gender, race, etc.
- This software is biased in the way that it only chooses candidates who will have higher chances in successful loans
Example 2: Candy Crush vs Call of Duty
- Call of Duty is geared towards the teenage boy demographic, 18-24, with more grunge type of music
- Candy Crush is more visually appearing to younger audience as it includes pictures of candies and playful music
- This is biased as the games include aspects and characteristics that will seem appealing to a specific audience
Popcorn Hack:
How is their unintentional bias in apps such as TikTok or Instagram or otehr social media apps?
Mitigation Strategies - Shubhay
- Utilize data from various sources
- Pre-Processing: A way to check the inputs for bias before it is being used as data
- In-processing: This algorithm changes the data during analysis of the data to keep the data consistent
- Post-Processing: # step check to make sure the model is fair and accurate
- Input Correction: This strategy makes adjustments to the data to make the data more comparable
- Classifier Correction: polishing and adjusting the algorithm after it has been trained to reduce the biases
- Output Correction: The predictions made by the model is modified to eliminate biases
Homework:
- Is bias enhancing or intentionally excluding?
Bias is enhancing because it is directed at certain groups of people. Its intention is to support and benefit a certain group of people and their interests. Since bias is specifically selective and directed towards a smaller group, it is able to appeal to that group really well. Because its purpose is to support only a small group of people, it selectively hightlights the groups’ positives/advantages and may unintentionally pass over other aspects.
- Is bias intentionally harmful/hateful?
Bias itself doesn’t necessarily carry harmful intent as it builds off of preferences. Bias appears because a target audience can only include a certain group of people and is impossible to appeal to everyone. Because of this, by appealing to one group, it may unintentionally seem harmful or hateful to an opposing group. This is natural and impossible to avoid, but the bias that comes from trying to appeal to one group is not purposefully trying to drag down or hurt an opposite/opposing group.
- During software development are your receiving feedback from a wide variety of people?
Yes, we are receiving feedback from a wide variety of people such as our fellow group members, other classmates, and the teacher Mr. Lopez. All of these opinions can result in biases that can impact the final presentation of a project.
- What are the different biases you can find in an application such as Youtube Kids?
These biases include algorithmic biases, where recommendation algorithms can unintentionally support existing biases towards certain videos and skew content representation. Cultural biases may lead to an underrepresentation of certain demographics or cultural groups. Gender biases might result in the reinforcement of stereotypes, limiting exposure to diverse gender roles. Educational biases may restrict the range of educational content offered. Additionally, commercial biases could favor popular creators, potentially sidelining smaller content producers.
Answer in complete sentences, due Sunday 11:59 pm