Artificial Intelligence Vocabulary Quiz
Test your vocabulary of artificial intelligence and modern technology. From machine learning to neural networks, this quiz covers the key AI terms appearing in news, academic texts, and professional discussions at B2–C1 level.
Start the Quiz →What This Quiz Tests
This quiz covers vocabulary from the rapidly evolving world of artificial intelligence and digital technology. Questions appear in realistic contexts from news articles, academic papers, and tech industry writing.
- Core AI concepts: machine learning, deep learning, neural network, algorithm, training data, model.
- AI applications: natural language processing, computer vision, chatbot, recommendation system, autonomous vehicle.
- Data and computing: dataset, processing power, cloud computing, parameter, inference.
- Ethics and society: bias, transparency, hallucination, regulation, generative AI.
- Industry terms: large language model, prompt, fine-tuning, benchmark, automation.
Choose Your Format
Practise the same topic in four different exercise formats:
Multiple Choice Quiz
Four options per question, instant feedback
Gameshow Quiz
Timed rounds, score streaks, competitive fun
True or False
Quick binary decisions on key facts
Matching Pairs
Match terms to their definitions
Sample Questions
1. A set of rules or instructions followed by a computer to solve a problem is called an ___.
Answer: algorithm
2. When an AI model generates information that is false but presented as true, this is called a ___.
Answer: hallucination
3. The branch of AI that enables computers to understand and generate human language is called ___ language processing.
Answer: natural
CEFR Level Breakdown
| Level | What to expect |
|---|---|
| B2 | Common AI and tech terms found in mainstream news and articles |
| C1 | Academic and professional AI vocabulary, nuanced technical distinctions |
| C2 | Specialised machine learning and computer science terminology |
Related Pages
- Renewable Energy Vocabulary Quiz — technology and innovation vocabulary
- Business English phrases — professional vocabulary including technology contexts
- IELTS Vocabulary Quiz — academic and topic vocabulary for exams
Related Quizzes
Frequently Asked Questions
The quiz covers core AI terminology including machine learning, neural networks, algorithms, training data, natural language processing, computer vision, and ethical AI concepts such as bias, transparency, and hallucination. Questions are set at B2 and C1 CEFR levels.
Artificial intelligence (AI) is the broad field concerned with creating systems that can perform tasks that normally require human intelligence. Machine learning (ML) is a subset of AI in which systems learn from data rather than being explicitly programmed. Deep learning is a further subset of ML that uses multi-layered neural networks.
A neural network is a computational model loosely inspired by the human brain. It consists of interconnected layers of nodes (neurons) that process information and learn patterns from data. Neural networks are the foundation of most modern AI systems, including image recognition, language translation, and large language models.
Training data is the dataset used to teach a machine learning model to perform a task. The model analyses large amounts of labelled or unlabelled examples and adjusts its internal parameters to improve its predictions or outputs. The quality and diversity of training data have a major influence on model performance.
A large language model is a type of AI trained on vast amounts of text data to understand and generate human language. LLMs can answer questions, write essays, translate text, summarise documents, and hold conversations. Examples include GPT-4, Gemini, and Claude. They work by predicting the most likely next word based on context.
In AI, hallucination refers to when a model generates information that is plausible-sounding but factually incorrect or entirely invented. For example, an AI chatbot might confidently cite a research paper that does not exist. Hallucinations occur because models generate text based on statistical patterns rather than verified facts.
AI bias refers to systematic errors in a model's outputs that reflect prejudices or imbalances in the training data or model design. For example, a hiring algorithm trained mainly on data about male employees may unfairly rank female applicants lower. AI fairness is the goal of designing systems that treat all groups equitably and do not perpetuate discrimination.
AI is one of the most discussed topics in contemporary media, business, and academia. Whether you are reading news articles, writing university essays, attending job interviews, or working in tech, you will encounter AI vocabulary regularly. Understanding terms like algorithm, data privacy, automation, and machine learning helps you participate in these conversations confidently.
Natural language processing (NLP) is the branch of AI that deals with the interaction between computers and human language. NLP enables machines to read, understand, translate, and generate text and speech. Applications include search engines, voice assistants, translation tools, spam filters, and AI chatbots.
Yes. Technology and AI are increasingly common topics in C1 Advanced reading and Use of English sections and in IELTS Academic reading and writing. Practising vocabulary in context through this quiz will help you recognise these words in exam texts and use them accurately in writing tasks.