IAI is domain-agnostic. It requires only that the researcher has encountered a phenomenon that existing theory inadequately explains and has formed a prior view of it. That condition is met across virtually every field. Select your domain in the tool to load field-specific literature for each area.
📈Management & Strategy
The concept of competitive advantage has not been meaningfully updated since Porter (1985). IAI is suited to generating the new category that existing data has been waiting for — starting from a practitioner’s observation that something in current strategy theory does not fit what they see in the field.
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Competitive advantage is no longer a property of firms — it is a property of ecosystems, and firms that optimise for individual advantage destroy the conditions for their own survival.
Example provocation
🏛Public Policy
The gap between what evidence shows and what policy debates address is often not empirical but categorical — policymakers are asking the wrong question because they do not yet have the concept to ask the right one. IAI generates the concept: the provocation-to-framework journey it traces is precisely the journey from "something is wrong with how we think about this problem" to "here is the category that makes it legible."
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Pronatalist policy cannot work because it compensates for the wrong variable — it targets cost, not aspiration.
Example provocation
🧠Psychology
The replication crisis in psychology is partly attributable to researchers testing hypotheses derived from unexamined categories. IAI’s logical debate stage — requiring that the internal coherence of a theoretical construct be subjected to adversarial pressure before it is operationalised — would significantly reduce the proportion of studies that produce statistically significant results for constructs that are theoretically incoherent.
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Resilience is not a psychological trait — it is a measurement artefact produced by ignoring the conditions that make coping necessary.
Example provocation
💹Economics
The most intellectually productive recent work in economics — behavioural, complexity, feminist — came from researchers who noticed that the existing categorical apparatus did not fit what they observed and insisted on building new categories rather than forcing data into old ones. IAI formalises that instinct, making it available to researchers who have the observation but not the confidence to trust their own departure from the field’s dominant categories.
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Economic growth is not a solution to inequality — it is its primary mechanism.
Example provocation
🤖AI Research
The speed at which new phenomena are appearing in AI research has outpaced the development of adequate categories to describe them. Terms like "alignment," "hallucination," and "emergence" are in widespread use without rigorous theoretical definition. IAI — particularly with AI as the sparring partner — is unusually well-suited to generating those frameworks at the speed the field requires.
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AI alignment is not a technical problem — it is a political one, and framing it as technical is itself a political act.
Example provocation
🌍Sociology & Demography
Demographic transitions, institutional change, and social inequality all involve phenomena where the decisive variable is often not captured by existing theoretical frameworks. IAI’s stress-test stage is particularly valuable here: demographic data is rich and contradictory, and the most important theoretical contributions come from frameworks that can survive engagement with the inconvenient case.
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Development does not produce social equality — it produces new and more durable forms of stratification.
Example provocation