Teaching, Curriculum and AI Literacy

Martin has taught an AI Marketing and Ethics course at the University of Hawaiʻi at Mānoa.

That sentence is the whole of what is claimed, and it is published as qualified rather than verified: it rests on Martin's own statement and has not yet been corroborated against an official course listing or faculty page. No academic title, department, appointment, or current position is asserted, here or anywhere else on this site. If you need any of those for a piece you are writing, ask rather than inferring them, because the honest answer today is that they are not on record.

The AI skills conversation in most organizations is still stuck between two inadequate positions: enthusiastic adoption without governance, and cautious refusal without analysis. The curriculum described here is an attempt to give working adults a more useful map, one that starts with what they already know, accounts for the practical and organizational constraints they actually face, and moves toward decisions they can justify.

The intended audience is not data scientists or machine-learning engineers. It is the operations manager deciding whether to run customer inquiries through an AI tool, the nonprofit director weighing AI-assisted grant writing, the small-business owner unsure whether a particular vendor is selling capability or compliance theater. People making real decisions with limited time and real accountability.

The material is also shaped by the Hawaiʻi context. The economic structure here (99.3 percent small businesses, tourism-adjacent workforce, relationship-based business culture, limited access to local technical talent) means that a curriculum designed for large mainland enterprises does not apply without significant adjustment. See AI in Hawaiʻi for the context that shapes this work.

The material is structured for adult learners who have real work to return to at the end of the session. That means starting with a problem the participant already owns (a workflow that is slow, a communication task that consumes disproportionate time, a governance question that nobody has answered) and working backward from that problem to the relevant AI capability or framework.

The Japanese learning progression of shu, ha, ri (follow the form, adapt the form, transcend the form) is a useful description of how capability with AI actually develops in organizations. The curriculum is organized around this structure: early material gives participants a reliable form to follow; later material creates the conditions for adaptation and independent judgment. Participants who skip the first stage and try to adapt before they have the form reliably tend to produce unreliable outputs and fragile workflows.

Case examples are drawn from the actual contexts participants work in: small businesses, nonprofits, public agencies, professional services firms, and community organizations operating in Hawaiʻi's relationship-based environment. Generic mainland examples are adjusted or replaced rather than applied without modification.

Participants are expected to leave with something actionable: a workflow mapped, a governance question answered, a specific next step with a named owner. Not with an attitude toward AI in general.

Resources for participants in teaching sessions are provided during or after the session in the format agreed with the organizer. Publicly available resources relevant to the curriculum themes are listed below by topic.

For AI governance frameworks: the NIST AI Risk Management Framework (AI RMF 1.0) is the most widely referenced U.S. standard for organizational AI governance. ISO/IEC 42001 covers AI management systems at a systems level.

For workforce readiness and adoption data specific to Hawaiʻi: Future Skills Hawaiʻi (futureskillshawaii.org) is the primary civic research organization covering these topics locally. Their published research is the authoritative local data source.

For implementation-level material: the AI implementation page on this site covers the workflow-level practice that underpins the implementation module of the curriculum. The responsible AI governance page covers the governance material in more depth than a single session permits.

This page describes curriculum themes and pedagogical approach. It does not list specific courses, credit hours, or institutions, because the claim governing that information (teaching-uh-shidler) is currently unverified in the register. Any institutional affiliation will appear only with exact verified wording from the institution.

The teaching described here is oriented toward working adults in organizational contexts, not undergraduate or graduate degree programs. The approach and examples are calibrated for that audience.

This page is not a booking form and does not set pricing or availability. Commercial team training engagements are handled through workshops and AI Marketing Box. For other teaching enquiries, use the contact form.

No student counts, pass rates, satisfaction scores, or learning-outcome statistics appear on this page. None have a baseline, method, and permission on file that would meet the evidence standard applied elsewhere on this site.