Future Leaders in AI

For two weeks in mid-July, 70 high school students from the Northwest and beyond took part in a virtual program sponsored by Seattle University and AI4ALL to learn about artificial intelligence and machine learning. In a virtual classroom-like setting, participants used data from the Seattle Police Department to help SPD identify potential bias crimes in the details of police reports. 

This project provided SPD’s Bias Crimes detective with near real-time analytics to help identify emergent, concerning patterns that may be fruitful for proactive intervention. The project’s data-forward approach seeks to streamline the analyzing and identifying of bias incidents, giving investigators more time to investigate crimes, rather than wrangling spreadsheets. 

 According to Loren T. Atherley, director of Performance Analytics & Research and senior research scientist at the SPD, the project is focused on making the process of investigating crimes with a bias motivation more efficient, more confident and faster. This area of “operationalized analytics” is conventionally referred to as Intelligent Decision Support and in this case is based in machine learning and natural language processing. 

Through the Seattle U Summer Scholars High School Institutes students took advantage of a long-term relationship between the university’s criminal justice program and SPD. For example, the natural language processing classifier that the police department uses now to identify use of force incidents in its reports is being adapted by Seattle U instructor Eric Lloyd, a data scientist in the Albers School of Business and Economics, to identify potential bias crimes. 

To comply with confidentiality rules, students used mathematical data based on the contents of the police reports to help identify whether bias crimes were committed. 

Seattle U is one of 16 colleges and universities nationwide that are partners with AI4All, a U.S.-based nonprofit dedicated to increasing diversity and inclusion in AI education, research, development and policy. Its emphasis is on reaching students from communities that are underrepresented in higher education and encouraging them, through their partnerships, to pursue AI and related fields in college. 

Originally designed to be an in-person residential program on the Seattle U campus, the program—July 12-24—shifted online due to the coronavirus pandemic.

The SU AI4ALL course featured three Seattle U faculty and a graduate assistant, Pa-Ousman Jobe. Ten undergraduate students served as mentors. 

In addition to Lloyd, Pete Collins, PhD, associate professor of criminal justice, taught an overview of the criminal justice system. Nathan Colaner, PhD, director of the Business Analytics Program at Albers, presented an ethics curriculum. Lloyd taught machine learning concepts with an overview of the Python programming language.  

Eva Sedgwick, JD, LLM, associate professor of business law and director of University Summer Programs, says the Seattle U AI4ALL program was a “perfect example of excellence in Jesuit education, tackling the incredibly complex challenge of racism at this precise moment of history within a rigorous and holistic STEM curriculum.”

The curriculum, developed over eight months, was especially impactful because it integrated multiple academic specialties and emphasized the intersection of race, human rights and technology. Students, a mix of underrepresented minorities and those from more privileged backgrounds, met in small groups and had regular real-time interactions with faculty and their undergraduate mentors, who were themselves from underrepresented communities. A mindfulness component was included at the beginning of each day to center everyone for the day’s work. Faculty led the students in guided meditations and gratitude practices. The course itself included resources for these and other self-care tools.

The students commented favorably about how the Seattle University team cared for and attended to each participant. “They felt safe, seen and heard, particularly in the small group breakout sessions during class and with their SU mentors,” says Sedgwick.

One student gave this testimonial in the program evaluation:

“The camp was super interesting and fun and I learned so much more about AI and criminal justice than I knew before. I never knew about the various biases in machine learning and liked learning about all the aspects of machine learning and AI. I also really enjoyed getting to learn more about coding and using computer applications. I became more comfortable with coding and using computer applications. I liked how close I got with my group and my counselor and although it was online I had a fun time. I learned a lot about subjects that I was interested in but never really knew about. This camp was captivating and interesting, with a healthy mix of having fun and learning, and I would definitely recommend this to other high school students.”