Emergent behaviors
Also written: Emergent, autonomous behaviors, Emergent abilities
Unexpected capabilities or characteristics that arise in complex AI systems as they scale or interact, not explicitly programmed.
Emergent behaviors are surprising abilities or traits that appear in AI models as they get larger or more complex. These are not things that developers specifically programmed into the AI. Instead, they seem to arise naturally from the way the AI is built and trained.
For example, a large language model might suddenly become good at writing computer code, even if it was primarily trained on text. This new skill was not directly taught but emerged from its vast training data and complex internal structure.
Emergent behaviors are capabilities or characteristics that are not present in smaller models but appear in larger models, often unpredictably. They arise from the complex interactions within the neural network and the scale of training data. These behaviors are not explicitly designed or anticipated by the developers.
The phenomenon is observed across various AI tasks, including language understanding, reasoning, and problem-solving. Understanding and controlling emergent behaviors is a key area of AI safety research, as they can lead to both beneficial new capabilities and unintended, potentially harmful, outcomes.
Recent research from Google and Anthropic highlights the growing concern over emergent behaviors. As AI models become more powerful and complex, identifying and understanding these unexpected capabilities is crucial for ensuring safety and reliability.
- Anthropic Found Something That Shouldn't ExistAnthropic · Two Minute Papers ·
- Investing in multi-agent AI safety researchGoogle · Google DeepMind Blog ·
- A “diff” tool for AI: Finding behavioral differences in new modelsAnthropic · Anthropic Research ·
- Third-party testing as a key ingredient of AI policyAnthropic · Anthropic News ·
- Anthropic Claude
- Anthropic is developing tools to detect unknown behavioral differences in new AI models, which can include emergent behaviors.
- Google Gemini
- Google DeepMind is investing in research to address emergent risks in multi-agent AI systems.
- Generalization
- Generalization refers to an AI's ability to perform well on unse
- Overfitting
- Overfitting occurs when a model learns the training data too well a
- Fine-tuning
- Fine-tuning adapts a pre-trained model to a specific task, whereas
The concept of emergent behaviors has roots in complex systems theory, but in AI, it gained prominence with the observation that capabilities not present in smaller neural networks appear in larger ones. Source ↗
Ask a large language model like ChatGPT or Google Gemini to explain a complex scientific concept, then ask it to write a poem about it. Observe if the quality of the poem is surprisingly good or creative, suggesting an emergent ability in creative writing.
The Playbook: reusable how-tos, prompts, configs and tips pulled out of the news.
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- HeuristicDouble coding agent task completion with docs linksProviding coding agents with a documentation link significantly increases their task completion rate. · 2 min
Questions people ask
- Are emergent behaviors always bad?
- No, emergent behaviors can be beneficial, leading to new and unexpected capabilities. However, they also pose risks if they are undesirable or harmful and were not anticipated.
- How do researchers find emergent behaviors?
- Researchers often discover emergent behaviors through extensive testing and evaluation of AI models, especially as models increase in size and complexity. Tools are being developed to systematically detect them.
First seen on Subvolts Dec 19, 2024. Updated Oct 5, 2026. Written by an AI model from the items above and reviewed against them weekly; report an error.