Writing Review: Becoming an Informed Technology Consumer

Source package reviewed: Radar Package: Becoming an Informed Technology Consumer

Incorporated

• Kept Becoming an Informed Technology Consumer as the internal durable title.
• Preserved the core frame that this is broader than AI and belongs inside technology-consumer literacy, AI readiness, and risk assessment.
• Built the purchasing cycle around Choose. Test. Adopt. Review. Renew, change, or leave.
• Included current capability versus future promise, product maturity, compatibility, upgrade-cycle evidence, experiment graduation, support, road maps, community participation, lock-in, and exit planning.
• Represented personal, family, creator, and small-business decision layers.
• Created the five fictional product-card activity and companion decision worksheet, renewal review, experiment graduation, and compatibility exercises.
• Added future artifact placeholders without over-producing V0.
• Separated durable lesson notes from current examples and added a last-reviewed mechanism.
• Linked the module into AI Readiness and Risk Assessment Support and made it optional in Creative AI Makerspace.

Pushback / Feedback

• The module should not be framed as “Buying AI.” AI examples are useful, but the stronger durable category is technology-consumer judgment.
• The V0 package is large enough that the next pass should prune for a 60- to 90-minute learner experience. The source can stay broad, but the first class should not attempt every section with equal weight.
• The agreement section should stay practical. Asking learners to review every legal word would make the module inaccessible and would shift the tone from consumer literacy to legal anxiety.
• The product maturity language needs careful facilitation because labels like alpha, beta, MVP, mature, and enterprise are inconsistent in the market. Observable evidence should carry more weight than labels.
• Creator/maker placement should remain optional. Creators need help choosing paid tools and subscriptions, but a mandatory consumer-purchasing module would slow the make-first confidence path.
• The fictional product cards are better than named current products for V0. Named examples can help later, but they will need dated review and should not become the durable lesson.
• Avoid fake precision scoring. Status words and decision records are better than numeric risk scores for this audience.

Suggested Next Pass

1. Pilot the product-card lab with only three cards: Mature Utility, Hype Machine, and Quietly Critical Experiment.
2. Convert the learner decision worksheet into a one-page printable.
3. Create a current-example review template before adding named products.
4. Decide whether renewal review becomes a required AI Readiness step or remains a supporting module.

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Source: Feedback/becoming-an-informed-technology-consumer/2026-07-11 13-56 - codex - writing-review.md