“Our cognitive biases are being transferred into algorithmic biases,” Manny Patole, Industry Assistant Professor at NYU Tandon’s Center for Urban Science + Progress (CUSP), explained to the Alliance for PIT. “I tell my students: ‘Just because you can, doesn’t mean you should,’” he said, emphasizing the critical need to integrate ethics education into STEM curricula. He noted that while specialized ethics programs existed at universities, comprehensive ethics training was rarely mandatory across all STEM disciplines.
“We’re teaching our students to address the problem, but we’re not actually teaching them to ask the right questions,” Patole said, adding that engineering students are typically taught to solve problems but not to question whether they were addressing the right problems in the first place.
Part of teaching ethics in STEM is understanding the society in which students will have to think critically about why and how to solve which problems. He said data has become the new raw material in a sort of “Columbian Exchange 2.0″—a reference to the transfer and global spread of plants, animals, and diseases between the western and eastern hemispheres from the 15th century onwards. Users across the world and across all other demographic borders have unwittingly provided valuable data that companies have monetized. “If you’re not paying for the product, then you are the product,” he shared. He questioned whether clicking “accept all cookies” constituted genuine informed consent, comparing it to “terms and conditions … written in six point font.”
Patole introduced the concept of “fair trade data,” drawing parallels to fair trade coffee. “How can a community that’s disenfranchised, that’s constantly studied but never receives the remuneration for their time and effort … monetize their own community data?” he asked. He suggested these communities were essentially becoming “customers of their own data” when research based on their information was sold back to them through policy implementations funded by their taxes.
Regarding student engagement, he argued: “if it’s valued by the community and the world around them, they will be more accepting of learning it and wanting to master it, as opposed to being something that’s a requirement.” He stressed the importance of critical thinking in technology development, asking, “if the social sciences can become more technological, can technology become more social?”
Patole expressed concern about technology setting culture rather than following it. While AI’s rise has been exceptionally rapid, he noted there are still “no checks and balances” on using it in informal settings.
He also cautioned that just because society has given AI so much of its attention of late, students flocking to AI is not necessarily a good thing svince it often means neglecting traditional engineering fields. “Everyone wants to do AI, that’s great, but we still need the person who’s doing the land survey,” he noted, maintaining that while AI tools were valuable, they should complement rather than replace essential engineering roles.
— Mythili Sampathkumar