About AI
AI Psy101 examines how generative and agentic AI affect the work of teaching psychology, especially introductory courses.
A critical, human-centered approach
The starting point is an educational purpose and the people affected by it. We examine possible benefits, the quality of the evidence, the work and costs involved, and who can influence a decision. Student agency, instructor judgment, accessibility and the ability to question an outcome belong in the main analysis. The Ethics & Data section develops questions about information, consent, surveillance, bias and accountability.
Using AI is a choice to justify in a particular setting. A limited use, a different tool and a decision to work without AI all deserve consideration. Company announcements inform coverage; they do not determine what a course needs.
Fairness means applying consistent standards to favorable and unfavorable claims. It does not mean giving unequal evidence equal weight or deciding the conclusion in advance. A capability claim, an instructional proposal and an observed learning effect remain separate.
Who this is for
Instructors, educational developers and researchers who want to examine course preparation, teaching, learning and assessment. Psychology is the reference point. Findings from other disciplines are identified by their original setting.
How to read the site
Company profiles separate dated product developments from their possible implications for teaching. Agentic AI and systems pages explain how tools, permissions, memory and orchestration fit together. In-depth analyses examine what these changes mean for psychology education. Guides explain concepts through teaching problems. Workflows assign actions and checks. Evidence pages separate findings from interpretation. Debates show competing positions. Developments connect dated changes to decisions an instructor might face.
Classroom examples are original illustrations, not reports of research or real students. A plausible explanation, a completed assignment and a demonstrated learning outcome are different things.
Updates and review
New material is selected and reviewed manually. A development records its event or publication date separately from the date its source was checked. A check date means the cited material was examined; it does not establish that no later development exists.
Research, preprints, product documentation and commentary are labeled separately. Product claims describe capabilities or provider statements, not independent evidence of improved learning. Source access and limitations are recorded with the evidence.
This is a selective publication rather than a complete news feed. Guides are reviewed when evidence or capabilities materially affect their advice. Updates are published after review; no automatic news coverage is promised.
Corrections
Factual corrections should identify the affected passage, the source and the reason for the correction. Substantive revisions should record the date, what changed and whether the interpretation changed. A source that becomes unavailable should retain a clear access note rather than silently disappearing.
Course boundaries
Examples use invented classroom material. Instructors should examine access, student data and institutional requirements before adapting a workflow. No activity requires personal health disclosures or the diagnosis of a student.
Part of Psy101
For the broader work of designing and teaching psychology courses, visit Psy101 Teaching. This site concentrates the family’s substantive discussion of AI.