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Artificial intelligence (AI) is becoming pervasive across industries, making it important for management information systems (MIS) students to understand the ethical issues involved. We present an active learning approach to teaching the fast-changing topic of AI ethics using a debate format. This approach was piloted in an undergraduate MIS course of 30 students. Over a five-week period, student teams were assigned to argue either the opportunities (pro) or dangers (con) viewpoint for five different AI technologies. A post-project survey indicated this format helps students gain a better understanding of the applications, opportunities, and potential misuse of AI. Students found this to be an engaging and fun way to explore the multiple dimensions of AI ethics that also required them to employ critical thinking, collaboration, research, and communication skills. We share our findings about the benefits of co-creating knowledge in the classroom using a debate format to explore an evolving topic. 

The Nation's research enterprise faces a shortage of data scientists. Expanding the pipeline of data science students, particularly from underrepresented populations, requires educational institutions to increase awareness of data science and inspire a passion for data in students as they begin their academic careers. In this tutorial we discuss the development and delivery of a free seminar designed to provide hands-on lessons in the use of both Apache Spark and Jupyter notebooks to students from any academic background in an approachable, no-risk environment. An explanation of the seminar resources, exercises, and implementation guidelines are included, as are lessons learned from several successful seminars held both in-person and virtually at two institutions of high education. 

The Python Foundations seminar emphasizes a hands-on approach and is designed to reach a diverse student population to provide them with the entry-level programming skills required in data science. The creation of the seminar materials has been funded by a three-year federal grant and has followed a systematic approach to enhance the student learning experience and raise student awareness of data science. The seminar materials—structured in three parts: pre-seminar, live seminar, and post-seminar—are licensed under the Creative Commons Attribution-ShareAlike 4.0 International license to encourage adoption by any institution. To foster interest in the seminar, students have the possibility to earn a digital badge attesting to their newly acquired skills. 

The COVID-19 public health emergency caused widespread economic shutdown and unemployment. The resulting surge in Unemployment Insurance claims threatened to overwhelm the legacy systems state workforce agencies rely on to collect, process, and pay claims. In Rhode Island, we developed a scalable cloud solution to collect Pandemic Unemployment Assistance claims as part of a new program created under the Coronavirus Aid, Relief and Economic Security Act to extend unemployment benefits to independent contractors and gig-economy workers not covered by traditional Unemployment Insurance. Our new system was developed, tested, and deployed within 10 days following the passage of the Coronavirus Aid, Relief and Economic Security Act, making Rhode Island the first state in the nation to collect, validate, and pay Pandemic Unemployment Assistance claims. A cloud-enhanced interactive voice response system was deployed a week later to handle the corresponding surge in weekly certifications for continuing unemployment benefits. Cloud solutions can augment legacy systems by offloading processes that are more efficiently handled in modern scalable systems, reserving the limited resources of legacy systems for what they were originally designed. This agile use of combined technologies allowed Rhode Island to deliver timely Pandemic Unemployment Assistance benefits with an estimated cost savings of $502,000 (representing a 411% return on investment).