Embedding ethics modules within computer science courses has become a popular response to the growing recognition that CS programs need to better equip their students to navigate the ethical dimensions of computing technologies like AI, machine learning, and big data analytics. However, the popularity of this approach has outpaced the evidence of its positive outcomes. To help close that gap, this empirical study reports positive results from Northeastern’s program that embeds values analysis modules into CS courses. The resulting data suggest (...) that such modules have a positive effect on students’ moral attitudes and that students leave the modules believing they are more prepared to navigate the ethical dimensions they’ll likely face in their eventual careers. Importantly, these gains were accomplished at an institution without a philosophy doctoral program, suggesting this strategy can be effectively employed by a wider range of institutions than many have thought. (shrink)

This commentary draws critical attention to the ongoing commodification of trust in policy and scholarly discourses of artificial intelligence (AI) and society. Based on an assessment of publications discussing the implementation of AI in governmental and private services, our findings indicate that this discursive trend towards commodification is driven by the need for a trusting population of service users to harvest data at scale and leads to the discursive construction of trust as an essential good on a par with data (...) as raw material. This discursive commodification is marked by a decreasing emphasis on trust understood as the expected reliability of a trusted agent, and increased emphasis on instrumental and extractive framings of trust as a resource. This tendency, we argue, does an ultimate disservice to developers, users, and systems alike, insofar as it obscures the subtle mechanisms through which trust in AI systems might be built, making it less likely that it will be. (shrink)