AI & Journalism Glossary

A set of rules or instructions that a computer follows to solve a problem or complete a task. In journalism, algorithms power everything from content recommendation to automated story generation.

Systematic errors in AI outputs that reflect prejudices in training data or system design. In journalism, AI bias can lead to skewed coverage of certain communities or topics.

An AI program designed to simulate conversation with human users. Newsrooms use chatbots for audience engagement, customer service, and interactive storytelling.

A form of journalism that uses data analysis and visualization to tell stories. AI enhances data journalism by enabling analysis of larger datasets and identifying patterns humans might miss.

AI-generated synthetic media (video, audio, or images) that convincingly depicts events that never occurred. A major concern for journalism as it challenges verification processes.

When an AI model generates information that sounds plausible but is factually incorrect or fabricated. A critical concern for journalists relying on AI-generated content.

An AI model trained on vast amounts of text data that can generate, summarize, translate, and analyze text. Examples include GPT-4, Claude, and Gemini.

A subset of AI where systems learn and improve from experience without being explicitly programmed. Used in journalism for content classification, trend detection, and audience analysis.

The branch of AI focused on enabling computers to understand, interpret, and generate human language. Powers tools like automated transcription, sentiment analysis, and text summarization.

A computing system inspired by the human brain, consisting of interconnected nodes that process information in layers. The foundation of modern AI systems including those used in journalism.

The input text or instruction given to an AI model to generate a desired output. Effective prompt engineering is becoming an essential skill for journalists working with AI tools.

A technique that combines AI text generation with information retrieval from specific sources, reducing hallucinations by grounding responses in factual data. Particularly useful for journalism applications.

The dataset used to teach an AI model. The quality, diversity, and representativeness of training data directly impact the accuracy and fairness of AI outputs in journalism.

A neural network architecture that processes sequential data using attention mechanisms. The technology behind modern LLMs like GPT and BERT that are transforming journalism workflows.