How Can Washington State Policies be Evaluated to Mitigate Asian AI Bias.

Meet Your Researcher.

Simon Kapran

AP Capstone Candidate, Class of 2026.

Aspiring to have a future in Law.
Fascinated and passionate of AI and learning of it.
yes, I did use AI to create the picture for this website, ironic right?

Research Question

How can Washington State policies surrounding artificial intelligence be modified or created in order to mitigate Asian AI bias in prestigious Washington Universities?

Problem Statement

Since the uses of Artificial Intelligence Technology has upgraded in many ways, different GenAI tools such as ChatGPT have found their ways into Higher Education universities.

According to the Civil Rights Act of 1964, discrimination based on race, color, national origin is illegal in public facilities such as schools, workplace facilities, restaurants, etc. This means that Artificial Intelligence discrimination which creates unfair bias that is confirmed by many existing studies is illegal due to it not fully providing fair outputs to certain ethnic groups in a federally assisted higher education facility.

Many studies have shown that Artificial Intelligence has discrimination towards different groups of people. This project evaluates different policies and/or creates new policies that work against discrimination, with a scope to mitigate Asian Artificial Intelligence discriminatory bias that higher education students receive at universities.

My hypothesis for this project as shown below is that currently prestigious higher education universities primarily in Washington either lack policies that are based on artificial intelligence and discriminatory outputs, or that they do exist, but they aren't effective in prioritizing the student's education and allow AI to continue having a bias upon them.

Hypothesis

When starting the research process, the researcher hypothesized that since 75,3% of people who use AI in their daily lives are usually 18-25-year-olds, according to Thormundsson (2024), currently in UW Seattle with a population of 51,719 people, and 23% Asian-Americans according to UW’s official website, there are possible hints of AI bias that currently exists in UW Seattle. There is a lack of rules and guidelines to prevent AI bias that could potentially create unfair disadvantages for students.

Method of Inquiry

Case Study Research: I will provide further information and understand the issue on why the current law framework and AI bias in prestigious Washington Universities.

Qualitative Study: Interviews with the asian population of UW Seattle and Gonzaga about their experiences with AI, and a short questionnaire that comes as a QR code with brief questions about further AI experience.

Student evidence from Prestigious Washington Universities.

Create: Proposing a new policy that would tackle AI bias towards Asians at prestigious Washington Universities.

Significance

Discrimination of AI in Higher Education settings may arise with problems for students.

AI biases can cause student's education to lack with AI tools often making decision on behalf of teachers without teachers having any insight into what variables are leading to those decisions.

Important Sources

Civil Rights Act of 1964
Bahammam AS, Trabelsi K, Pandi PSR, Jahrami H. Adapting to the Impact of Artificial Intelligence in Scientific Writing: Balancing Benefits and Drawbacks while Developing Policies and Regulations. Journal of Nature & Science of Medicine. 2023;6(3):152-158. doi:10.4103/jnsm.jnsm_89_23
Howard, A., & Borenstein, J. (2018). The Ugly Truth About Ourselves and Our Robot Creations: The Problem of Bias and Social Inequity. Science & Engineering Ethics, 24(5), 1521–1536. https://doi.org/10.1007/s11948-017-9975-2
Jacques PH, Moss HK, Garger J. A Synthesis of AI in Higher Education: Shaping the Future. Journal of Behavioral & Applied Management. 2024;24(2):103-111. doi:10.21818/001c.122146
Daher, W., & Hussein, A. (2024). Higher Education Students’ Perceptions of GenAI Tools for Learning. Information (2078-2489), 15(7), 416. https://doi.org/10.3390/info15070416
Thormundsson, B. (2024, September 10). Weekly usage of AI tools in 2023, by age range. statista. https://www.statista.com/statistics/1450290/weekly-ai-tool-usage-age-rangeweekly-ai-tool-usage-age-range/

Definitions

-AI: A set of programmed technologies that enable computers to perform a variety of functions, including the ability to see, understand, write, translate, and perform human capable actions through a spoken, written language.

- Mitigate: Make less sever, lower the chances of happening.

-Bias: Prejudice in favor of or against one thing.

- University Policy: a governing principle formally approved and established to provide vision, guidance, assistance, and direction to the University community in the conduct of University or Unit affairs.

Results

15 participants overall. 53,3% of the respondents were primarily in the Biological/Biomedical field, and 6,7% of the respondents were in Engineering, Psychology, Geography, Public Health, Law Societies & Justice, and Computer Science.

66,7% of the participants are well aware of AI, meaning that they understand how it works, the issues it may contain, and potentially use it in their daily lives.

46,7% of the participants agreed that LLMs and chatbots were the most vulnerable to AI biases.

33,3% and 26,7% agreed that biases were primarily in admissions and hiring.

Implications

There is no doubt that students who want to attend a higher education facility or are already attending one face a significant issue related to AI technology. These specific issues cause not only trouble for students of a particular ethnicity, for example, Asian Americans, but also legal issues that arise from these issues. As presented by the evidence, higher education students do agree that AI bias exists in higher education facilities. AI bias creates unfairness within the student population with facial recognition technology, LLM’s, admissions, and hiring. Students who attend higher education facilities and are ethnically diverse often face challenges when encountering AI biases. AI will continue to adapt and develop further in society, creating problems as the AI biases currently present in higher education facilities may transfer onto our jobs, creating problems larger than just education.

Conclusion

The legal issues arise when knowing that discrimination is illegal. In this research paper, the researcher develops the Equitable AI Acts policy to mitigate the AI biases identified at the University of Washington (UW) in Seattle, using data from the paper, and to limit legal issues that can arise from AI while also increasing the comfort of students attending UW Seattle. Despite this study not being able to confirm or refute the existing gap, further research is needed, as AI has not yet fully evolved.

If any future researchers take this topic, they need to design a larger study and gain more data in order to refute or support this gap. Further on, laws need to be designed and passed in order to control AI biases and its problems. Even though its impossible to fully prevent AI problems and Biases, these laws will help mitigate them and thus create less problems in society and education.

Equitable AI Act

University of Washington (UW) Seattle Policies & Procedures

Definitions

Artificial Intelligence Discrimination Bias refers to automated artificial intelligence programs having prejudice in favor against one race or ethnic group compared with another usually in a way that is considered unfair.

Purpose

This policy applies to primarily University of Washington: Seattle but is also adoptable by other universities in Washington State.

POLICY GUIDELINES

Official Statement

University of Washington (UW) Seattle will mitigate AI Biases that students currently experience by monitoring any AI programs in action, and preventing those Biases from happening.

University of Washington (UW) Seattle will also make sure that students understand that AI Biases exist and understand the issues that it can potentially create.

Policy Procedures

University of Washington (UW) Seattle will be monitoring GenAI tools such as ChatGPT, DALL-E, MidJourney, and other tools that students may use, facial recognition technology, AI grading tools, AI admissions tools, and any other AI tool that can exhibit potential Biases.

Scope

This policy applies primarily to the University of Washington: Seattle but is also adoptable by other universities in Washington State.

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