AI Bias
When a system produces unfair results because its training data reflected an unfair world. It matters commercially as well as ethically: a biased model makes confidently wrong decisions about real people.
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When a system produces unfair results because its training data reflected an unfair world. It matters commercially as well as ethically: a biased model makes confidently wrong decisions about real people.
Turning written text into spoken audio. Modern voices are convincing enough to be used for real narration, which raises its own questions about disclosure.
A way of turning text into numbers so a computer can tell that “web hosting” and “website server space” are about the same thing. It is what makes search by meaning possible rather than search by exact word.
When a model, instead of answering from memory, asks to run a specific tool — look up a price, check stock — and uses the result. It is what turns a chat assistant into something that can act.
A system that suggests what somebody might want next based on behaviour — the “customers also bought” of an online shop. One of the oldest commercial uses of machine learning.
When the same URL serves different formats depending on what the visitor asks for — HTML for a browser, Markdown for an assistant. It lets one address serve people and machines without either getting a compromise.
AI that interprets images and video — reading a document, recognising a product, counting people. The part of AI that has been quietly working in industry for years.