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Posted in January 2026

Data Disappearing Acts: Navigating Government Misinformation and Finding Reliable Alternatives

¶¶Òõ¸£Àûµ¼º½ Librarians Roberta Richards and Veronica Vichit-Vadakan discuss the removal and alteration of federal government data in public health and climate science. They introduce ¶¶Òõ¸£Àûµ¼º½ Library resources—including Statista and specialized guides—to help faculty and students locate verified statistics, archived records, and trustworthy alternative data. Posted January 30, 2026

Beyond Bias: What Every Student Needs to Know About Al

In this presentation, CIS Department Chair Marc Goodman examines how AI engineering, tokenization, and engagement-driven architectures shape model accuracy. Moving beyond basic data bias, he breaks down hallucinations, retrieval-augmented generation (RAG), and reinforcement learning. Goodman reveals why chatbots prioritize persuasion over objective truth and shares practical strategies to teach critical AI fact-checking skills. Posted January 30, 2026

Will Al Elevate Student Achievement and Equity or Will Poorly Executed Al Drive Poorer Outcomes and Wider Academic Gaps?

In an interactive roundtable, ¶¶Òõ¸£Àûµ¼º½ presenters explore how AI impacts student achievement, equity, and practice. Treating AI as a socio-technical issue, ¶¶Òõ¸£Àûµ¼º½ rejects automated proctoring and plagiarism detection to avoid algorithmic bias. The session emphasizes "backstage learning"—valuing process over final products—alongside compassionate human care teams, data privacy, and ethical institutional governance. Posted January 30, 2026

Al and Copyright: Legal Realities and Ethical Questions

Cascade Faculty Librarian Rachel Bridgewater examines the intersection of copyright law and generative AI across four key questions, including output eligibility and training fair use. Highlighting case law, she explains why copyright law often falls short of addressing ethical concerns and why real solutions depend on licensing, labor regulations, and ethical standards. Posted January 30, 2026

Higher (order) Education: The Role of Colleges in Teaching the Cyborg Student

As AI evolves into reasoning agents, higher education must reframe technology from an external threat to an extension of student cognition. While AI simplifies synthesis, it risks superficial "informational collages." Consequently, colleges must shift focus toward teaching epistemic hygiene, metacognition, source validation, and complex project design rather than policing tool usage. Posted January 30, 2026