Ethics
The ethics domain mandates transparency for AI-mediated decisions, independent bias evaluation using Caribbean data, monitoring of vendor concentration and AI sovereignty risks, and ongoing attention to potential long-term cognitive effects of AI dependency.
Caribbean context
Tools trained predominantly on non-Caribbean data can produce outputs that are biased or linguistically inappropriate for Caribbean students. Established tools are not exempt from evaluation.
5 provisions in this domain
- Full policy statement
Students, teachers and parents are informed when AI mediates decisions or recommendations affecting learners, in language appropriate to the audience.
Guiding principlesHuman-CentredResponsible InnovationRelated roadmap initiatives
A Caribbean scenario
A widely used adaptive learning platform is required, at renewal, to submit Caribbean-data bias evaluation. Results trigger configuration changes and a teacher advisory note that improves outcomes for Creole-influenced English speakers.
Responsibility matrix
- •Coordinate independent bias evaluation
- •Publish annual AI sovereignty analysis
Preconditions for implementation
Where to start
- 01Publish the regional AI ethics framework for education
- 02Operate independent bias evaluation using Caribbean data
- 03Publish the first annual AI sovereignty / vendor concentration analysis
What progress looks like
- Bias evaluation results published for every endorsed AI tool
- Transparent disclosure on every AI-mediated decision affecting learners
- Annual analysis identifies and acts on vendor concentration risks
Likely risks and practical responses
MitigationRequire independent evaluation using Caribbean data as a condition of endorsement and renewal.
What this domain looks like in the roadmap
- RI-G01NowEstablish Caribbean Digital and AI Ethics Code for EducationEstablish shared principles and minimum requirements for the responsible design, procurement, deployment and use of digital and AI technologies in education.
- RI-G02NowEstablish transparency and human-accountability requirementsRequire clear disclosure of AI use, meaningful human oversight and identifiable institutional accountability for decisions affecting learners, teachers or schools.
- RI-G03NowEstablish bias, fairness and non-discrimination requirementsRequire evaluation of approved tools for unequal impacts across disability, gender, geography, language, income level and other relevant groups.
- RI-G04NextEstablish high-risk AI review requirementsRequire enhanced review before AI is used for high-impact functions, including student profiling, behavioural prediction, disciplinary decisions, admissions or automated decision-making.
- RI-G05NextEstablish digital and AI incident reporting and response mechanismsEstablish procedures for reporting, investigating, escalating and responding to harmful, biased, unsafe, inaccurate or inappropriate AI outputs and related ethical concerns.
- RI-G06NextEstablish student, parent and public awareness guidanceProvide clear guidance on responsible AI use, rights, reporting channels, limitations of AI outputs, misinformation and appropriate participation in digital learning environments.
- RI-G07LaterReview long-term ethical and cognitive impacts of AI useReview evidence on the effects of AI use on learner autonomy, equity, wellbeing, reasoning and public trust, and update ethical safeguards where required.
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