Automated Decisions Register

1. Purpose and scope

This register covers automated decision-making within Nova 5 (the Service). It describes the kinds of personal information used by automated systems, the kinds of decisions made solely by those systems, and the kinds of decisions to which they substantially and directly contribute. It is written in plain language so the people affected — learners and the staff of training organisations — can understand and question what the Service automates.

• Maintained automatically: when the Service changes, this register is rewritten to match, and every version is archived at a permanent address.
• The register describes the Service as it is — never planned or future capability.

2. Design stance

Nova 5 is deliberately built so that decisions with significant consequences for a person are made by people. The Service provides formative practice, teaching materials and evidence tooling; competency, assessment, enrolment and recognition decisions remain with the training organisation's qualified staff. Automated systems in the Service are engineered to inform those decisions, not to make them.

• Learner identity is pseudonymous by default — most automated processing operates on a pseudonymous visitor identifier, not a name.
• Personal information use is minimal by design: no street addresses, no precise location, no raw IP addresses stored against learner activity.

3. Kinds of personal information used by automated systems

The following kinds of personal information are used in the operation of the automated systems described in this register.

• A pseudonymous visitor identifier and, where a learner or their organisation chooses, a display name.
• Learning activity events: starts, steps, answers, completions, time engaged, and scores within practice activities.
• Work a learner chooses to upload for formative feedback, where their organisation has enabled that feature.
• Learning-management-system identity (name and email as supplied by the organisation's LMS), where the organisation connects Nova via LTI.
• Coarse, city-level location derived from network routing at the time of access (never an address, precise coordinates or a stored IP address).
• For training organisation staff using the provider portal: name, email address, role and workspace activity.

4. Decisions made solely by automated systems

The following decisions are made by computer programs without human involvement in the individual decision. None of them determines competency, certification, enrolment or any comparable right; each states its effect and how to question it.

• Access control on learning links: the Service automatically serves or declines a learning link based on its status, expiry and the organisation's subscription standing. Effect: a learner may be unable to open a learning space until the organisation resolves the link. To question it: contact the training organisation that issued the link.
• Practice scoring and instant feedback: activities mark answers, award points in live class games, and generate formative feedback automatically. Effect: the learner sees scores, streaks and feedback in the moment. These results are formative practice signals only and do not decide any outcome about the learner. To question one: raise it with the trainer, who can escalate to us from the portal.
• Practice-support selection: the Service automatically selects reminders, refresher questions and study suggestions from a learner's own activity. Effect: which nudge or practice item a learner sees next. No access or outcome depends on it.

5. Automated systems that substantially contribute to human decisions

The following systems do not make the decision, but do something substantially and directly related to a decision made by a person at the training organisation. In each case the deciding human is identified and the system's contribution is recorded.

• Grade signals to a connected LMS: where an organisation connects Nova to its learning management system via LTI, activity scores and completion signals are written to the LMS gradebook automatically. Any assessment decision drawing on those signals is made by the organisation's staff under its own assessment policy — the Service passes practice signals, it does not assess.
• Recognition of prior learning (RPL) evidence mapping: where enabled, the Service drafts a map of a candidate's self-assessment and evidence against unit requirements. The draft is an input for a qualified human assessor, who makes the recognition decision; drafts are marked as drafts and the assessor's decision is their own.
• Insights and reports: the Service aggregates learning activity into dashboards, weekly reports and delivery records that inform trainers' and managers' decisions about teaching. The records identify what was automated; sign-off of delivery records is a human act.

6. What automated systems never decide

For the avoidance of doubt, no automated system in the Service makes, or substantially contributes to making, any of the following decisions about an individual.

• Whether a learner is competent, passes a unit, or receives any qualification, statement of attainment or certification.
• Whether a person may enrol, continue in, or be excluded from a course.
• Any decision about a training organisation staff member's employment, performance or pay.
• Any pricing, credit or eligibility decision about an individual.

7. Human oversight and contestability

Every consequential pathway in the Service has a human checkpoint, and every automated action that matters is recorded.

• Delivery records are confirmed by a named trainer before they stand as evidence; RPL maps await a human assessor; assessment obligations remain with the organisation.
• An auditable log records automated actions (including automated content changes and report runs) and is available to each organisation for its own workspace.
• A learner who believes an automated result is wrong should raise it with their trainer or training organisation, which can escalate to Supahuman from the portal; we review and respond.
• Questions about this register: hello@supahuman.ai.

8. Content automation (not individual decision-making)

The Service also automates decisions about content — quality checks on generated materials, regulatory currency checks that can update material when legislation changes, and scheduled rewrites of public documents such as this one. These systems act on teaching content, not on personal information about an individual, and are listed here for completeness and honesty. Content changes made automatically are recorded in the audit log.

9. For training organisations: your own privacy policy

If your organisation uses Nova 5 and is an APP entity, your privacy policy must describe automated decision-making that uses personal information about your learners and staff, including processing performed by service providers such as Supahuman Limited. The provider portal generates suggested wording that reflects your workspace's actual configuration; this register is the supporting detail that wording refers to.

10. Document control

This register is reviewed and rewritten automatically as the Service changes, and every version is archived at a permanent address so a copy referenced on any date remains retrievable. The current version is always published at this address. Where an agreement references this register, the agreement's terms prevail to the extent of any inconsistency.