Explore Tasks
Set and review the organisation's AI use policy and AI literacy requirements
Every Function receives an approved AI use policy (permitted, restricted and prohibited uses, approval route and literacy expectations), reviewed at least yearly against incidents and regulation.
1job does it
4jobs help with it
42skills it needs
- AI Governance Lead
- Data Protection Officer
- Head of Data & Analytics
- Head of Data Governance
- Chief Data & AI Officer
Does itHelps with it
- Reading and tracing unfamiliar code
- Reviewing human- and AI-generated code changes for correctness and risk
- Sampling and reviewing a team's work against standards
- Diagnosing misleading data visualisations
- Verifying reports and dashboards before and after release
- Verifying AI-assisted outputs against sources
- Disclosing AI contribution to professional work
- Testing competing explanations with discriminating evidence
- Independently checking analytical conclusions and claims
- Escalating unresolved risks with evidence and clear ownership
- Giving specific developmental feedback on data and AI work
- Judging the materiality of defects and deficiencies for the intended use
- Classifying AI uses against regulatory obligations
- Governing shared data definitions
- Enforcing and auditing data access
- Judging whether and how to use AI for a task
- Applying data classification and handling rules
- Assigning and operating data ownership and stewardship
- Designing enforceable data governance policies
- Mapping stakeholders' decisions, constraints and needs
- Working through stakeholder conflict over evidence and responsibility
- Identifying and prioritising critical data elements
- Designing decision rights and dispute routes for data and AI work
- Building data protection by design into data products and pipelines
- Designing AI-assisted workflows with bounded tools and human authority
- Bounding and securing AI systems' tool and data access
- Designing and running evaluations of AI systems
- Presenting and defending evidence-based recommendations to decision-makers
- Decomposing one's own tasks for AI assistance
- Protecting sensitive data in AI-assisted work
- Evaluating fitness and full cost of AI-assisted work
- Analysing error patterns and failure modes in models and AI systems
- Evaluating responsible AI use risks
- Assessing privacy risk through data protection impact assessments
- Assessing supplier dependency, data-handling and exit risk
- Rating risks against appetite and choosing proportionate treatment
- Identifying and quantifying decision downside and exposure
- Making accountable decisions under uncertainty
- Revising prior decisions when evidence changes
- Reasoning about systems, feedback and second-order effects
- Facilitating group decisions using disputed evidence
- Recognising and resolving ethical conflicts in data and AI work
Paths that teach the skills it needs
Skill Path
Data Literacy for Business Decisions
Judge whether a business claim from a table, KPI, chart or dashboard really holds up.
- Modules
- 5 open
- Practice data
- Raket Parts
Skill Path
Data Governance, Catalogues and Lineage
Govern definitions, stewardship, lineage and enforceable policy.
- Modules
- 5 open
- Practice data
- Raket Parts
Skill Path
Diagnostic Investigation and Root Cause Analysis
Resolve contradictory evidence and find, verify and prevent the causes of business and data anomalies.
- Modules
- 5 open
- Practice data
- Raket Parts
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