jagged frontier
In plain wordsThe uneven edge of what AI can do: it may excel at some hard tasks yet fail at seemingly easier ones, so how hard a task looks is a poor guide to whether AI can handle it.
The irregular boundary between tasks that current AI systems perform well and tasks they perform poorly, where difficulty for humans is an unreliable guide to which side of the boundary a task lies on. In the field experiment that introduced the term, 758 consultants at Boston Consulting Group worked on realistic tasks with or without GPT-4. On tasks inside the frontier, AI users completed about 12% more tasks, about 25% faster, with output rated more than 40% higher in quality; on a task designed to fall just outside it, consultants with AI gave correct answers 19 percentage points less often than those working without it, because they accepted plausible but wrong output. The concept underlies advice to map the frontier for one's own work by experiment and to keep human checks where it is uncertain.
The model drafts the contract flawlessly but miscounts its clauses: the jagged frontier in a single document.
Origin
Introduced in 'Navigating the Jagged Technological Frontier' (Harvard Business School working paper, September 2023) by Fabrizio Dell'Acqua, Edward McFowland III, Ethan Mollick and colleagues, and popularized through Mollick's newsletter and his book Co-Intelligence (2024).
Usage note
Overlaps with jagged intelligencejagged intelligence, n.: The uneven pattern of AI abilities: today's systems can solve very hard problems yet fail at some a child could manage, so their skills form a spiky profile rather than a smooth one., which describes the uneven capability profile of models themselves; the frontier version stresses the worker's practical problem of knowing where reliance is safe. The frontier moves as models improve, so any task's position on it is dated.
Related
- jagged intelligencejagged intelligence, n.: The uneven pattern of AI abilities: today's systems can solve very hard problems yet fail at some a child could manage, so their skills form a spiky profile rather than a smooth one.
- centaurcentaur, n.: A human and an AI working as a team, each doing what it does best, like a chess player who consults a computer before every move. The name comes from the mythical half-human, half-horse creature.
- augmentationaugmentation, n.: Using AI to help people do their work better or faster while they stay in charge, instead of having the AI do the job on its own.
- overrelianceoverreliance, n.: Leaning on an AI system more than its reliability justifies: accepting its answers without checking, or letting it make decisions it often gets wrong.
- Moravec's paradoxMoravec's paradox, n.: The observation that what is hard for people, like chess or algebra, is often easy for computers, while what toddlers do effortlessly, such as seeing, walking and picking things up, is very hard for machines.
- co-intelligenceco-intelligence, n.: Ethan Mollick's term for working and thinking alongside AI as a partner — treating it like a capable but odd colleague whose strengths and blind spots you learn through experience.
Sources
- Dell'Acqua, F., McFowland, E., Mollick, E. R., Lifshitz-Assaf, H., Kellogg, K., Rajendran, S., Krayer, L., Candelon, F. & Lakhani, K. R. (2023). Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality. Harvard Business School Working Paper 24-013.
Mentioned in
augmentationaugmentation, n.: Using AI to help people do their work better or faster while they stay in charge, instead of having the AI do the job on its own., capabilitycapability, n.: Something an AI system is able to do, such as writing working code or solving math problems, and how well. Measuring capabilities is how researchers track progress and spot dangerous skills., centaurcentaur, n.: A human and an AI working as a team, each doing what it does best, like a chess player who consults a computer before every move. The name comes from the mythical half-human, half-horse creature., jagged intelligencejagged intelligence, n.: The uneven pattern of AI abilities: today's systems can solve very hard problems yet fail at some a child could manage, so their skills form a spiky profile rather than a smooth one., Moravec's paradoxMoravec's paradox, n.: The observation that what is hard for people, like chess or algebra, is often easy for computers, while what toddlers do effortlessly, such as seeing, walking and picking things up, is very hard for machines., task exposuretask exposure, n.: A measure of how much of a job's work AI could, in principle, do or speed up. High exposure means many of the job's tasks are within AI's reach, not that the job will vanish., co-intelligenceco-intelligence, n.: Ethan Mollick's term for working and thinking alongside AI as a partner — treating it like a capable but odd colleague whose strengths and blind spots you learn through experience., Ethan MollickEthan Mollick, prop. n.: An American management professor at Wharton whose experiments and popular writing on how people use AI at work introduced ideas such as the 'jagged frontier'.