As artificial intelligence (AI) technologies begin to permeate diverse fields--from healthcare to education--consumers, researchers and policymakers are increasingly raising concerns about whether and how AI is regulated. It is therefore reasonable to anticipate that alignment with principles of'ethical' or'responsible' AI, as well as compliance with law and policy, will form an increasingly important part of AI development. Yet, for the most part, the conventional computer science curriculum is ill-equipped to prepare students for these challenges. To this end, we seek to explore how new educational content related to AI ethics and AI policy can be integrated into both ethics-and technical-focused courses. This paper describes a two-lecture AI policy module that was piloted in a graduate-level introductory machine learning course in 2024. The module, which includes an in-class active learning game, is evaluated using data from student surveys before and after the lectures, and pedagogical motivations and considerations are discussed. We find that the module is successful in engaging otherwise technically-oriented students on the topic of AI policy, increasing student awareness of the social impacts of a variety of AI technologies and developing student interest in the field of AI regulation. Introduction The explosive growth of artificial intelligence (AI) technologies is widely documented and increasingly evident in everyday life: some responses from the search engine Google now include an "AI Overview" inserted before the first webpage link; companies like Tesla and Waymo have seen success in implementing partial or full autonomous driving in vehicles on live roads; and "Apple Intelligence" was the flagship feature for the launch of Apple's new smartphone in fall 2024. Yet what legal or policy response this technological growth will precipitate is less certain [1, 2]. Nevertheless, it should be expected that the development and enactment of regulatory frameworks for AI will demand AI engineers with a command not only of the technical intricacies of AI models, but also of the policy and regulatory landscape for AI development and compliance [3].

The domain of Artificial Intelligence (AI) ethics is not new, with discussions going back at least 40 years. Teaching the principles and requirements of ethical AI to students is considered an essential part of this domain, with an increasing number of technical AI courses taught at several higher-education institutions around the globe including content related to ethics. By using Latent Dirichlet Allocation (LDA), a generative probabilistic topic model, this study uncovers topics in teaching ethics in AI courses and their trends related to where the courses are taught, by whom, and at what level of cognitive complexity and specificity according to Bloom’s taxonomy. In this exploratory study based on unsupervised machine learning, we analyzed a total of 166 courses: 116 from North American universities, 11 from Asia, 36 from Europe, and 10 from other regions. Based on this analysis, we were able to synthesize a model of teaching approaches, which we call BAG (Build, Assess, and Govern), that combines specific cognitive levels, course content topics, and disciplines affiliated with the department(s) in charge of the course. We critically assess the implications of this teaching paradigm and provide suggestions about how to move away from these practices. We challenge teaching practitioners and program coordinators to reflect on their usual procedures so that they may expand their methodology beyond the confines of stereotypical thought and traditional biases regarding what disciplines should teach and how. This article appears in the AI & Society track.

The future of artificial intelligence (AI) is here: self-driving cars, grocery-delivering drones and voice assistants like Alexa that control more and more of our lives, from the locks on our front doors to the temperatures of our homes. For example, should an autonomous vehicle swerve into a pedestrian or stay its course when facing a collision? These questions plague technology companies as they develop AI at a clip outpacing government regulation, and have led Seattle University to develop a new ethics course for the public. Launched last week, the free, online course for businesses is the first step in a Microsoft-funded initiative to merge ethics and technology education at the Jesuit university. Seattle U senior business-school instructor Nathan Colaner hopes the new course will become a well-known resource for businesses "as they realize that [AI] is changing things," he said.

The future of artificial intelligence (AI) is here: self-driving cars, grocery-delivering drones and voice assistants like Alexa that control more and more of our lives, from the locks on our front doors to the temperatures of our homes. For example, should an autonomous vehicle swerve into a pedestrian or stay its course when facing a collision? These questions plague technology companies as they develop AI at a clip outpacing government regulation, and have led Seattle University to develop a new ethics course for the public. Launched last week, the free, online course for businesses is the first step in a Microsoft-funded initiative to merge ethics and technology education at the Jesuit university. Seattle U senior business-school instructor Nathan Colaner hopes the new course will become a well-known resource for businesses "as they realize that [AI] is changing things," he said.

The New York Times has confirmed what some have long suspected: The Chinese government is using a "vast, secret system" of artificial intelligence and facial recognition technology to identify and track Uighurs--a Muslim minority, 1 million of whom are being held in detention camps in China's northwest Xinjiang province. This technology allows the government to extend its control of the Uighur population across the country. It may seem difficult to imagine a similar scenario in the U.S., but related technologies, built by Amazon, are already being used by U.S. law enforcement agencies to identify suspects in photos and video. And echoes of China's system can be heard in plans to deploy these technologies at the U.S.-Mexico border. A.I. systems also decide what information is presented to you on social media, which ads you see, and what prices you're offered for goods and services.