AI training glossary
128 terms explained in plain English.
A
- Acceptable use policyA policy that sets out permitted and prohibited uses of company technology. An AI policy often extends an existing acceptable use policy rather than replacing it.Responsible AI
- AI and copyrightThe legal questions around AI and creative work, including whether training on copyrighted material is allowed and who, if anyone, owns AI-generated output. Answers differ by country and are still being settled.Responsible AI
- AI ethicsThe principles that guide what AI should and shouldn’t be used for, and how, such as fairness, privacy, honesty and respect for human rights.Responsible AI
- AI governanceThe policies, roles and processes an organization uses to decide which AI tools are allowed, how they are used and who is accountable.Responsible AI
- AI risk assessmentA structured review of what could go wrong with an AI use case, such as errors, bias, privacy breaches or misuse, and how likely and serious each risk is.Responsible AI
- Algorithmic biasSystematic unfairness in AI output, often inherited from skewed training data or design choices, that disadvantages certain groups.Responsible AI
D
- Data privacyProtecting personal information from being collected, used or shared without proper permission. With AI tools, this includes what you paste in and how the provider stores it.Responsible AI
- DeepfakeAI-generated or AI-altered audio, video or images that realistically show a person saying or doing something they didn’t.Responsible AI
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Commonly confused terms
AI literacy is understanding what AI is and what it can and can’t do. AI fluency is the practical ability to work with it well on your own tasks. Literacy comes first; fluency comes from practice.
Upskilling improves how someone does their current job. Reskilling prepares them for a different job.
A workshop is hands-on: participants practice on real tasks. A masterclass is expert-led and deep on one topic, with more demonstration than practice. “Training” is the umbrella term for both.
An assistant responds to each request and waits for the next one. An agent takes a goal, plans the steps and uses tools to carry them out with less direction.
An outcome states what the learner can do afterward. An objective states what the trainer aims to achieve. Many organizations use the two interchangeably.
A certificate of completion shows someone finished a course. A certification shows they passed an assessment against a standard. Accreditation is when an external body approves the course or provider itself.
E-learning is delivered entirely through digital platforms. Blended learning combines online study with in-person sessions. Live online training is real-time and trainer-led over video.
A self-paced course runs on each learner’s schedule. A cohort-based course moves a group through together on fixed dates, with live sessions and peer discussion.