In light of recent racial and social unrest in the US, many educators are calling for a larger incorporation of ideas of ethics into mathematics, statistics, and computer science curriculum. Given that students in these classes are the future experts in data assessment and technology development, there is urgency in ensuring that they understand the power and consequences that their work could entail. Although computers and machines may not harbor biases, the creators of algorithms, mathematical models, and statistics can perpetuate systemic racism and bias. By educating ourselves as faculty, we hope to inform our students on how to be more responsible and civic-minded creators and users of data, mathematics, and technology.
By gathering ACM faculty to participate in a shared learning experience, this project will educate faculty in mathematics, statistics, and computer science to a standard level of cultural competency through a dedicated reading group, accompanied by workshops with invited colleagues in the social sciences and conversations with students on their experiences. Furthermore, faculty will create deliverables that aim at fostering a more inclusive and equitable learning environment as informed by our readings and discussions, which in turn will help us better support students at our institutions.
Goals
After Professors Eikmeier and Miller participated in the Cultural Competence in Computing program last year, directed by Professor Nicki Washington at Duke University, we have become more acutely aware of the need to better educate ourselves as faculty and, in turn, our students on systemic racism and bias present in real-world applications of mathematical and computational sciences. The past several years have been marked by racial and social unrest, which has raised public awareness of problematic policies and technologies that perpetuate the historical discrimination of marginalized communities. For example, algorithms determine who is approved for home loans and where cops patrol based on predictions for recidivism, but these algorithms use proxy data, such as zipcodes, that target poor communities with a high proportion of marginalized racial groups.
Faculty at liberal arts colleges are uniquely primed to integrate cross-divisional ideas into their classes, bring awareness to the impact future leaders can have in society, and inspire those future leaders to implement more just and equitable practices. However, faculty in the mathematical sciences and computer science are not traditionally trained in ethical issues. In providing an opportunity for faculty development and support through this program, we seek to better address ethical issues in our classrooms with hopes that we and our students responsibly implement, use, and interpret data and technology. Additionally, we plan to learn about and discuss topics that directly impact student experiences in the classroom including gender and racial identities, identity development, intersectionality, bias, racism, and other forms of oppression.
Activities
Faculty Seminar: In Fall 2022, we will invite all ACM faculty members in mathematics, statistics, and computer science departments (and related fields, such as data science) to participate in a monthly discussion group.
We will read and discuss a common book to establish a shared vocabulary and host discussions with subject-matter experts in, e.g., psychology, race studies, and pedagogy. Participants may also host focus groups at their institutions for students with vested interests to contribute their perspective on what is needed and how best to address current deficits. Possible books include “Why are all of the black kids sitting together in the cafeteria?” by Beverly Daniel Tatum; “Weapons of Math Destruction” by Cathy O’Neil; “Algorithms of Oppression” by Safiya Noble.
Deliverables: During Spring 2023, faculty will work together on identifying current needs as informed by discussions in the Faculty Seminar and design deliverables, e.g., a module for an existing class, a new course, or department- or campus-wide initiatives. We will hold 2-3 check-ins with invited speakers to continue conversations from Fall and provide faculty additional opportunities to learn how to effectively and successfully implement their deliverables.
Workshop: In Summer 2023, we will host an in-person workshop to learn more about deliverables being developed, to give feedback to each other, and to continue working on deliverables for successful implementation.
Final check-in: In Fall 2023, we will hold a virtual check-in with faculty to learn about the effectiveness of the implementation of their deliverables and solicit feedback for improvements.
Dissemination Strategies
Faculty participants will create deliverables of their own choosing, which they will implement in their home institutions. Faculty will work on and share their deliverables at the Summer 2023 workshop, after which we will create a website that houses links to resources and the created deliverables. Furthermore, faculty will be encouraged to share what they learn with their colleagues at their home institutions and at other regional and national venues, such as the annual meeting at the Mathematical Association of America’s MathFest and the meeting of the Special Interest Group in Computer Science Education (SIGCSE) at the annual Association for Computeing Machinery’s International Computing Education Research Conference.
Resources & Materials
The deliverables will be the products that we will implement in our classrooms, departments, and campuses. Since the deliverables will be developed directly by faculty who serve their students, the products will be variable and tailored to the needs of the specific curriculum. We also anticipate waterfall effects; for example, faculty may choose to go on to develop more products for their curriculum after the workshop is over, and non-participating faculty may choose to use the resources created.
Outcomes and Significance
The main outcomes we hope to achieve in these project activities are to learn and then teach our students about systemic racism and bias resulting from the use of computational and mathematical sciences, to build more equitable and inclusive learning environments for our students, and to prepare our students to be future leaders in dismantling systems of oppression. These outcomes will be achieved by first educating our faculty through our book study and trainings with invited subject-matter experts, and then developing deliverables that will expose students to the same issues and empower them to be agents of change through the use of mathematics and computer science for social justice.
