AI Vocabulary – Advanced (C1–C2)

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Augmented intelligence
Augmented intelligence helps doctors make better diagnoses by analyzing patient data faster.
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AI that supports human abilities rather than replacing them
Generative AI
Generative AI tools such as ChatGPT can produce essays, images, and even code.
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AI that creates new content like text, images, or music
AI literacy
Improving AI literacy helps people use smart tools effectively and ethically.
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the ability to understand and use artificial intelligence responsibly
Explainable AI
Explainable AI is essential in finance and healthcare to ensure accountability.
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AI systems that can clearly explain how they make decisions
Automation fatigue
Workers can experience automation fatigue when relying too heavily on digital platforms.
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mental stress caused by constant exposure to automated systems
Digital ethics
Digital ethics guide how companies handle user data and online behavior.
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principles for using technology in a fair and responsible way
Smart algorithms
Smart algorithms allow recommendation systems to adapt to your preferences.
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advanced sets of rules that guide how AI behaves or learns
AI surveillance
AI surveillance is used for security but also raises privacy concerns.
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monitoring people or environments using AI-based systems
Tech dependency
Tech dependency can make it difficult for people to function without digital tools.
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over-reliance on technology in everyday life
To revolutionize industries
AI is expected to revolutionize industries such as healthcare and transportation.
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to completely change sectors through new technology
To adapt to technological change
Employees must adapt to technological change to stay competitive in the job market.
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to adjust to new tools and systems
Human-AI collaboration
Human-AI collaboration helps companies innovate faster.
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humans and AI systems working together efficiently
Job displacement
Job displacement is a serious concern in manufacturing and data entry roles.
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the loss of jobs due to automation or AI systems
Ethical concerns
There are growing ethical concerns about bias and data collection in AI.
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issues related to what is right or wrong in using technology
AI-driven decisions
AI-driven decisions can improve efficiency but also risk hidden bias.
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choices made with the help of artificial intelligence
AI-powered education
AI-powered education provides personalized learning experiences for students.
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learning supported by AI-based tools and platforms
Cutting-edge technology
Cutting-edge technology like quantum computing will reshape data analysis.
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the most advanced and innovative form of technology
Data privacy
Companies must ensure strong data privacy policies to maintain user trust.
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the protection of personal or sensitive digital information
Predictive analytics
Predictive analytics helps banks detect fraud before it happens.
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using AI and data to anticipate future outcomes
Sentiment analysis
Sentiment analysis allows companies to track customer satisfaction on social media.
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AI that detects emotions or opinions in text
AI regulation
The EU is currently working on strict AI regulation to protect consumers.
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laws or policies that control the development and use of AI
Human-like intelligence
Researchers are still exploring how to create true human-like intelligence.
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AI’s ability to simulate human reasoning or behavior
Automation-resistant skills
Developing automation-resistant skills can protect workers from job loss.
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skills that are difficult for AI to replace, like creativity or empathy
Technological advancement
Technological advancement has led to faster innovation cycles.
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progress in developing new and improved technologies
Digital transformation
Digital transformation is key for modernizing public services.
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the process of integrating digital tools across industries
AI-powered economy
An AI-powered economy demands new skills and digital awareness.
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an economy where artificial intelligence drives growth and innovation
Data-driven culture
Building a data-driven culture helps businesses make smarter strategic moves.
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a mindset where decisions are based on data rather than opinions
Explainability gap
The explainability gap is one reason some people don’t fully trust AI systems.
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the difference between AI’s decisions and our understanding of them
AI transparency
AI transparency is necessary to build public confidence in new technologies.
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the openness about how AI systems work and make decisions
Human oversight
Human oversight ensures that AI-powered tools follow ethical standards.
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the role of people in supervising and correcting AI systems
Bias mitigation
Bias mitigation techniques are vital for making AI systems more inclusive.
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the process of reducing unfairness or discrimination in AI
Responsible AI
Responsible AI development helps companies avoid ethical and legal issues.
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AI designed and used with accountability and fairness in mind
AI governance
Strong AI governance is needed to ensure innovation doesn’t harm society.
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the frameworks and policies that regulate AI systems
Digital footprint
Your digital footprint can be used by advertisers or even by AI algorithms.
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the trace of personal data a user leaves online
AI-powered healthcare
AI-powered healthcare helps doctors detect diseases earlier and more accurately.
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medical systems that use AI to improve diagnosis and treatment
To integrate AI
Companies integrate AI to increase efficiency and reduce costs.
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to incorporate artificial intelligence into existing products or workflows
To ensure ethical AI
Organizations must ensure ethical AI to prevent harm or discrimination.
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to make sure AI systems are designed and used responsibly
AI sustainability
AI sustainability is becoming an important research topic.
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developing AI that minimizes environmental and social impact

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