AI Literacy
The ability to understand, evaluate, and effectively use AI systems. AI literacy includes knowing what AI can and cannot do, how it works at a conceptual level, and how to critically assess AI outputs.
Why It Matters
AI literacy is becoming as essential as digital literacy. Employees, leaders, and citizens who lack AI literacy will be disadvantaged in the AI-powered economy.
Example
A marketing manager who understands that AI-generated statistics might be hallucinated and knows to verify them, versus one who blindly trusts everything ChatGPT produces.
Think of it like...
Like financial literacy — you do not need to be an accountant, but you need to understand enough to manage your money wisely and spot when something does not add up.
Related Terms
AI Ethics
The study of moral principles and values that should guide the development and deployment of AI systems. It addresses questions of fairness, accountability, transparency, privacy, and the societal impact of AI.
Responsible AI
An approach to developing and deploying AI that prioritizes ethical considerations, fairness, transparency, accountability, and societal benefit throughout the entire AI lifecycle.
AI Governance
The frameworks, policies, processes, and organizational structures that guide the responsible development, deployment, and monitoring of AI systems within organizations and across society.
Prompt Engineering
The practice of designing and optimizing input prompts to get the best possible output from AI models. It involves crafting instructions, providing examples, and structuring queries to guide the model toward desired responses.