Computer algorithms influence many aspects of modern life, from shopping lists to first dates and even job offers. But who writes algorithms and code, and how do their personal values find their way into these sequences?
That’s what Drexel Sociologist Kelly Joyce, PhD, wanted to find out in her National Science Foundation-backed study, “The Ethics of Algorithms.”
“Any time you automate a process, you are going to have the potential for bias. We don’t know the decisions that were made about what to include or exclude in an algorithm; we just encounter the effects of them,” Joyce says.
These effects, she says, reflect a lack of training around the range of ways that big data can affect human subjects.
To fill this gap, Joyce and a former colleague in Drexel’s College of Computing & Informatics spent four years studying teams of computer scientists and engineers who build big data sets. After interviews and dozens of meetings in which they noted when and how ethical considerations arose, the researchers translated what they learned to create data-driven scenarios, designed to engage future computer scientists in ethical problem solving.
Three Drexel master’s students in Science, Technology and Society — Kendall Darfler ’17, Dalton George ’17 and Jason Ludwig ’17 — wrote the scenarios to evoke the voice, terminology and real-life ethical dilemmas of computer scientists and engineers.
The scenarios were tested in five universities, where STEM classrooms debated issues like data validity and sensitive information. The scenarios were then refined and made available on the project’s website. Four were featured in the National Academy of Engineering’s Online Ethics Center, increasing accessibility to educators and practitioners of STEM ethics.
Joyce believes in the importance of training STEM students to recognize the complexity of human-based data — but ultimately, she says, product design and implementation require the deep expertise provided by a range of fields.
“A lot of universities are starting data science programs, and if you look at who is considered an expert, there are computer scientists, mathematicians, but rarely social scientists,” she says. “We are making a case for training students in STEM to think about these issues, but also in terms of research teams, to really think about who is at the table.”