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Also known as: Human-AI Collaboration
An approach where AI systems enhance human capabilities and decision-making rather than fully automating tasks.
DESCRIPTION
Augmented intelligence prioritizes human oversight and collaboration with AI to improve decisions and productivity. It emphasizes transparency, interpretability, and usability to align AI with human goals. Typical applications include decision support, copilots, and tools that amplify expert judgment. The approach acknowledges limits of automation and incorporates human feedback loops. It is central to responsible AI and regulatory expectations for human control. System design focuses on UX, explanations, and error recovery. Measurement balances task performance with user satisfaction and trust. It often leverages human-in-the-loop training and evaluation. Augmented intelligence is gaining traction across industries, especially in high-stakes domains.
ALTERNATIVE DEFINITIONS
Wikipedia
Augmented intelligence (sometimes referred to as intelligence amplification) is the use of technology to augment human intelligence rather than to replace it.
Highlights augmentation over automation and ties to intelligence amplification.
IBM
Augmented intelligence uses AI to support and enhance human decision-making and productivity, emphasizing human oversight, transparency and collaboration between people and AI systems.
Stresses governance, transparency, and human oversight in practice.
Stanford HAI
Human-centered AI research seeks to augment human capabilities with AI systems that are collaborative, ethical, and aligned with human values and societal needs.
Frames augmented intelligence within a human-centered, ethical paradigm.
RELATED TERMS
Human-in-the-Loop Explainable AI Decision Support System Human-Centered AI Active Learning Responsible AI AI Governance Interactive Machine Learning Human Oversight
COMPETING TERMS
RELATIONS
- Broader: Artificial Intelligence
KNOWLEDGE AREAS
AI Governance AI Data Science Domain & Business Context
TARGET AUDIENCE
AI Product Manager Data Scientist AI Engineer Chief Data Officer Data Governance Manager Chief Technology Officer
EXTERNAL SOURCES
- Wikipedia - Augmented intelligence
- SAS - Overview of augmented intelligence concepts
- OECD - AI principles emphasizing human-centered values
- NIST - AI Risk Management Framework
TOP QUESTIONS
What distinguishes Augmented Intelligence from Autonomous AI?
Augmented intelligence centers humans as the ultimate decision-makers, using AI to support them. Autonomous AI minimizes human intervention, targeting full automation for certain tasks.
Category: Comparison
Why is Augmented Intelligence relevant now?
Regulations and ethics emphasize human oversight. Complex, high-stakes contexts benefit from human judgment supported by AI, improving trust, safety, and adoption.
Category: Relevancy
How do you implement Augmented Intelligence effectively?
Design with users, provide explanations, capture feedback loops, and measure both task and user experience metrics. Align with governance and domain workflows.
Category: How-To
What are risks of Augmented Intelligence?
Overtrust in AI suggestions, cognitive overload, and biased recommendations are risks. Training, guardrails, and UX design mitigate them.
Category: Risks
Which metrics matter for Augmented Intelligence?
Decision quality, time-to-decision, user satisfaction, override rates, and error recovery effectiveness are key alongside model performance.
Category: Metrics
What is a common misunderstanding about Augmented Intelligence?
That it is slower than automation. In practice, human-AI collaboration often improves overall speed and accuracy in complex tasks.
Category: Misunderstanding
How does explainability support Augmented Intelligence?
Clear model explanations increase user trust, calibrate reliance, and facilitate error correction—critical for cooperative workflows.
Category: Relation
Where is Augmented Intelligence widely applied?
Domains like healthcare, finance, law, and customer support use AI copilots, triage tools, and decision support systems.
Category: Examples
How does Augmented Intelligence relate to Responsible AI?
It operationalizes responsible AI by embedding human oversight, transparency, and feedback, aligning systems with societal and ethical norms.
Category: Governance
What is a hot topic in Augmented Intelligence?
LLM-based copilots integrated into productivity suites and developer tools, with guardrails and evaluators, are rapidly evolving.
Category: Topic