Map your actual work.
Map five responsibilities in your field. Imagine AGI can execute the associated tasks. Identify the goals, values, consequences, and accountability that still need deliberate governance.
For the entire IT industry: business and administration, accounting and finance, development and research, consulting and analysis, architecture and engineering, product and project management, managers and leaders. Explore what human agency means when AGI could execute work across these functions.
Working premise: imagine AGI performs most routine and complex execution across an organisation. This is a scenario for preparation, not a claim that AGI has already replaced those jobs. The exercises do not guarantee career security.
Hypothetical AGI scenarios, not live model outputs.
No API key or paid model needed.
Use the rubric for self-review. These checks are not an externally validated assessment.
You may practise early; the notebook records when you did. No reminder is sent.
Across every function, practise framing goals, judging evidence,
resolving trade-offs, and governing delegated work.
Map five responsibilities in your field. Imagine AGI can execute the associated tasks. Identify the goals, values, consequences, and accountability that still need deliberate governance.
Compare slow, uneven, and rapid AGI adoption scenarios. Explore effects across finance, people, customers, products, and operations. Identify choices that remain useful under several futures.
Choose a cognitive practice: problem framing, causal reasoning, systems thinking, ethical judgment, negotiation, or metacognition. Apply it outside your usual department and explain your reasoning without assistance.
Create a decision brief: objectives, stakeholders, alternatives, assumptions, evidence, and review triggers. Show how you would retain agency and revise your decision as capabilities and conditions change.
Current AI studies inform specific design choices.
They do not establish how future AGI will affect people.
Our focus is AGI readiness. Research on today’s generative AI and human–AI collaboration offers bounded observations, not proof about future AGI or ASI. AGI scenarios in the lab are original thought experiments. Test their assumptions rather than treating them as findings.
Compare study designs, populations, controls, measures, and limitations. A preprint, a narrative review, and an experiment answer different questions. ResearchGate can help locate author copies; verify citations against the original publication.
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