Summary: A new study identifies the core cognitive engine behind human creativity and technological progress: semantic knowledge. This internal map of how concepts relate and can be applied is shown to be an essential precondition for meaningful invention.
Combining computational models of cultural development with a large human experiment involving more than 1,200 participants, the researchers demonstrate that without a built-in understanding of how the world works, human innovation collapses into random trial-and-error. Participants who lacked semantic context performed no better than uncalibrated random agents, even when they could observe and copy others through social learning.
Key Facts
- The overlooked creative engine: While cultural evolutionary theory often highlights the roles of social learning and motivation in human progress, this work elevates semantic knowledge—our grasp of functional relationships and how to apply them—as a critical cognitive contributor to innovation.
- The 1,200-participant innovation arena: In a large behavioral experiment, people played a custom computer game that rewarded novel combinations of items. One group worked with familiar, meaningful objects (for example, rocks and branches); another group faced arbitrary abstract symbols that carried no semantic content.
- The random-bot baseline: Results revealed a sharp cognitive threshold. When participants could draw on semantic knowledge, their ability to find useful, high-performing combinations rose substantially. In contrast, without semantic cues, human performance fell to the level of random, unthinking bots—even when social learning was available.
- Double-innovation multiplier: Semantic knowledge and social learning interact synergistically. Groups with access to both produced roughly twice as many unique innovations as groups restricted to social learning alone, demonstrating how conceptual understanding and peer information amplify and refine ideas across generations.
- Intergenerational transmission: The findings refract how cultural heritage works: earlier generations transfer not only concrete inventions but also a conceptual toolbox—a dynamic blueprint of how the world operates—that shapes future innovation.
- The paradox of strong priors: The authors note an important caveat for future work: dense, entrenched semantic wiring can sometimes impede radical breakthroughs by creating strong assumptions about what is reasonable, causing innovators to overlook counterintuitive or “unreasonable” solutions.
Source: Karolinska Institute
What drives human inventiveness? According to this study, a central role is played by semantic knowledge—our internal understanding of how objects and concepts connect and how those connections can be applied. That knowledge functions as a mental toolbox, shaping the search for usable combinations and steering creativity toward meaningful solutions.
In the experiment, participants who could rely on familiar object properties solved problems far more effectively than participants confronted with meaningless symbols. The latter group, deprived of semantic context, explored in shallow, random ways and achieved success rates equivalent to chance. Importantly, access to other people’s solutions—the mechanism of social learning—did not compensate for the absence of semantic knowledge.
“Semantic knowledge is our cognitive toolbox,” says Björn Lindström of the Department of Clinical Neuroscience at Karolinska Institutet. “It helps us understand which things can work together and why.”
The study also used an agent-based computer model to simulate cultural evolution. Virtual agents that could consult an internal knowledge map produced more effective innovations and generalized discoveries to new contexts, mirroring the human results. Across both modeling and behavioral approaches, semantic knowledge directed exploration toward meaningful, repeatable solutions and boosted innovation success.
Crucially, semantic knowledge and social learning combined to accelerate cumulative cultural change. When both were present, groups not only copied but also improved and extended ideas, leading to a higher rate of unique innovations over time. This synergy helps explain how human cultures accumulate complex technologies across generations.
At the same time, the researchers caution that strong conceptual priors can become blinders. While semantic maps make everyday innovation efficient, they can also encourage dismissal of unusual or counterintuitive possibilities—an effect the team plans to study in more realistic, complex scenarios.
Funding: The research was a collaboration between Karolinska Institutet and Vrije Universiteit Amsterdam, funded by the European Research Council (ERC) and the Knut and Alice Wallenberg Foundation. No conflicts of interest were reported.
Key Questions Answered:
A: Copying behavior without understanding why a solution works is empty mimicry. The experiment showed that when people solved problems with meaningless symbols, observing successful peers did not improve results. Social learning becomes powerful only when paired with a conceptual toolbox that allows decoding, refining, and building on others’ ideas.
A: Semantic knowledge operates like a mental map that estimates how properties and functions interact. Recognizing what a rock and a branch can do together filters out millions of implausible combinations and focuses effort on options that are more likely to work.
A: Yes. Strong semantic priors create entrenched expectations about what is reasonable. These conceptual constraints can blind experienced innovators to surprising, counterintuitive ideas—an issue the researchers intend to explore further.
Editorial Notes:
- This article was edited by a Neuroscience News editor.
- The journal paper was reviewed in full by editorial staff.
- Additional context was added by the editorial team.
About this research on innovation and creativity
Author: Press Office, Karolinska Institutet
Source: Karolinska Institutet
Contact: Press Office – Karolinska Institutet
Image: Image credited to Neuroscience News
Original Research: Closed access. “Semantic knowledge guides innovation and drives cultural evolution” by Anil Yaman, Shen Tian, and Björn Lindström. PNAS. DOI: 10.1073/pnas.2530750123
Abstract
Semantic knowledge guides innovation and drives cultural evolution
Cultural evolution enables ideas and technologies to accumulate across generations, reaching exceptional complexity in humans. Although social learning transmits innovations, the cognitive mechanisms that generate those innovations have been unclear.
Classical theories often model innovation as random variation, a simplification that fails to capture human cultural complexity. The authors propose that semantic knowledge—the network of associations linking concepts with properties and functions—directs human innovation and fuels cumulative culture.
Combining an agent-based model with a large-scale behavioral experiment (N = 1,243), the study found that semantic knowledge focuses exploration on meaningful solutions, enhances innovation success, and supports generalization from prior discoveries. Semantic knowledge also synergizes with social learning to amplify innovation and speed cultural accumulation, while its absence leaves participants performing at chance and relying on shallow exploration strategies.
Overall, these findings position semantic knowledge as a key cognitive process underlying human cumulative culture.