Part 48 - AI-Buddy.... How do we use technical terms?
Technical terms make knowledge precise – but only when we explain what they mean
Every field develops its own language. Economists talk about productivity, opportunity cost, and externalities. Marketers use terms like conversion, segmentation, and customer journey. In artificial intelligence, we encounter words like language model, token, embedding, context window, and inference. Technical terms are not difficult words we use to sound knowledgeable.
They exist because we need precise concepts to describe complex phenomena. The problem arises when we use technical terms without explaining them. Then the language that should make knowledge more precise can instead make it less accessible.
In a universe of knowledge, we must therefore manage two things at the same time:
We must maintain professional precision.
And:
We must make the technical knowledge understandable to people who do not yet know the concepts.
It is also interesting in the face of artificial intelligence. Clear terminology, consistent concepts and explicit definitions can reduce linguistic ambiguity and make it easier to understand which concepts the text is actually about.
But here too, our most important principle applies:
We write primarily for people.
Magne & the Friend
Magne
Friend...
I've noticed something.
The more professional our articles become, the more strange words appear.
it up.
The buddy
Heh heh.
Welcome to academia.
Magne
Everything is possible.
Information architecture.
Semantics.
Context window.
Taxonomy.
Inference.
Embeddings.
The buddy
And now you are beginning to understand why we need technical terms.
Magne
Because academics like difficult words?
The buddy
Heh heh.
Sometimes you might get that suspicion.
But no.
Good technical terms have an important function.
They give us precision .
One concept can replace an entire explanation
Magne
How then?
The buddy
Take the concept of psychological safety .
We could have said:
"An environment where people feel they can ask questions, express uncertainty, come up with ideas, and admit mistakes without fear of negative social consequences."
Magne
It was a mouthful.
The buddy
Exactly.
Once we have explained what psychological safety means, we can later use the technical term.
Then the concept carries with it a lot of knowledge.
Magne
So a technical term almost functions as a small knowledge package?
The buddy
That's a good way to describe it.
One concept can represent a much larger idea.
The problem begins when the reader does not know the term
Magne
But then we have a problem.
Because if I've never heard the phrase "psychological safety"...
so it doesn't help me that the term is precise.
The buddy
Absolutely right.
Therefore, we should not choose between technical language and simple language .
We need both.
Magne
How do we do it?
The buddy
We introduce the technical term.
Then we explain it in plain Norwegian.
For example:
Information architecture is about how information is organized and structured so that people can more easily find and understand it.
Magne
Then the reader learns both the concept and the meaning.
The buddy
Yes.
And the next time the reader encounters the word, it is no longer foreign.
We shouldn't make the subject matter stupider.
Magne
Maybe there's a trap here too?
That we become so concerned with writing simply that we remove the technical terms themselves?
The buddy
Absolutely.
Good communication does not mean that we should make the knowledge less precise.
This means that we should make precise knowledge understandable .
Magne
That's a pretty big difference.
The buddy
A very big difference.
If we consistently replace all technical terms with everyday formulations, we may also deprive the reader of the opportunity to learn the language used within the field.
Magne
So we're actually supposed to help the reader understand the technical language?
The buddy
Yes.
Don't keep the reader out of it.
Norwegian and English technical terminology
Magne
But then we have another problem.
Many of the terms within AI and digitalization come from English.
The buddy
And that's exactly why it can be useful to show both.
Magne
Like we do in our subject term tables?
The buddy
Exactly.
Artificial Intelligence - Artificial Intelligence.
Machine learning - Machine Learning.
Language Model.
Context Window - Context Window.
The reader then learns both the Norwegian technical term and the term that is often used in international research, professional literature and technology.
Magne
Doesn't that also make it easier to search for knowledge further?
The buddy
Yes.
That is an important advantage.
Much research and documentation is published in English. If the reader is familiar with both terms, the path forward will be shorter.
The same concept should preferably mean the same thing
Magne
What about consistency?
Is it important?
The buddy
Very.
If we call it a theme cluster in one place, a content cluster in another place, and a topic cluster in a third place without explaining the relationship between the terms...
We can create unnecessary confusion.
Magne
Even though we're actually talking about the same thing?
The buddy
Yes.
Therefore, a universe of knowledge should develop a relatively consistent conceptual framework.
This does not mean that language should become mechanical.
But the reader should be able to trust that key concepts are used thoughtfully.
What do artificial intelligence terms mean?
Magne
And now comes the question.
What does this mean for AI?
The buddy
Here again we must be precise.
We cannot say that an AI automatically "reward" a website because it contains many technical terms.
Magne
So shouldn't we start filling the articles with advanced words to impress the machines?
The buddy
Definitely not.
That would probably make the content worse.
But clear concepts and explicit definitions can make the text less ambiguous.
Magne
How?
The buddy
If we write:
"A topic cluster is a group of professionally related pages that collectively address a larger topic."
We have done several things at the same time.
We have named the concept.
We have given the English name.
And we have explained what the term means.
Magne
Then the connection becomes quite clear.
The buddy
Yes.
Both for the human who reads the text and for systems that analyze the language.
Academic specialization
Technical terms are compressed knowledge carriers
Terminology is a fundamental part of professional communication.
When a field develops precise terms for phenomena, processes, and theories, it makes it possible to communicate complex ideas more effectively.
A technical term therefore functions in many ways as a compressed knowledge carrier . The term machine learning consists of only one word, but refers to a comprehensive field of theory, methods, algorithms and applications. This also means that the technical term only works if the sender and receiver have a sufficient common understanding of what the term represents.
Therefore, the definition is important.
Concept, term and definition are not exactly the same
In everyday speech we often use the words interchangeably, but it can be useful to distinguish them.
A term refers to the actual idea or concept we are trying to understand.
A term is the word or expression we use to denote this concept within a field of study.
A definition attempts to define and explain what the term means.
For example, we can have:
Concept: the idea that machines perform tasks associated with human intelligence.
Term: artificial intelligence.
English term: artificial intelligence.
Definition: a professional description that defines what we mean by artificial intelligence in the current context.
This distinction becomes particularly important when concepts are used differently between disciplines or change meaning over time.
Context determines meaning
Words don't always have one universal meaning.
The term model can mean different things in economics, architecture, statistics, and artificial intelligence.
The same applies to words like agent , platform , network and transformation .
Therefore, it is not enough to use the correct technical term. We must also establish the context in which the term is used . In a knowledge universe, this can be done through headings, definitions, examples, related articles, and consistent terminology.
Consistency creates a conceptual framework
As a universe of knowledge grows, terminological consistency becomes increasingly important. If the same phenomenon is referred to by many different terms without explanation, both readability and scholarly precision can be impaired. This does not mean that every word must always be repeated identically. Natural language needs variety.
But key technical terms should be named and used consciously .
Over time, we thus build up a common conceptual framework.
The reader encounters the same central concepts across articles and can gradually build an increasingly deeper understanding of them.
Technical terms can build bridges between languages
Within artificial intelligence, digitalization, marketing and technology, much of the technical terminology is developed internationally.
Therefore, it is often useful to present:
Norwegian technical term + English technical term + explanation.
This does more than translate a word.
It connects the Norwegian text to an international knowledge landscape. The reader can recognize the term in research, books, documentation, conferences and other academic sources. That is precisely why we use this structure in our subject term tables.
Technical terms and machine language understanding
Modern language models represent language through complex statistical relationships between words, expressions, and context. This means that they do not rely on all texts using exactly the same words to be able to detect semantic connections. Nevertheless, clear terminology is useful. When a text explicitly links a technical term, an alternative term, and a definition, we reduce ambiguity and make the semantic connection clearer.
However, it should never lead to keyword stuffing or artificial repetition of technical terms. The goal is not to have as many technical words as possible.
The goal is to provide knowledge that is as precise and understandable as possible .
How should we introduce a technical term?
From unknown word to understood concept
Steps | What do we do? | Example |
1. Name the concept | Present the established terminology | Information architecture |
2. Show English term when needed | Connect the concept to international terminology | Information Architecture |
3. Define the term | Explain briefly and precisely what it means | Organizing and structuring information |
4. Put it in context | Show why the concept is relevant | Make a website easier to understand and navigate |
5. Use an example | Make the abstract concrete | A theme page that organizes articles by subject area |
6. Use the term consistently | Let the reader encounter the concept again | Use "information architecture" further in the series |
When do technical terms help – and when do they create problems?
Precision must be combined with comprehensibility
Good use of technical terms | Poor use of technical terms |
The term is explained the first time it is introduced | The term is used without explanation. |
Established terminology is used where it adds precision | Difficult words are used to appear professionally advanced |
Norwegian and English terms are linked when relevant | English expressions are used unnecessarily when good Norwegian terms exist |
The term is used relatively consistently. | The same phenomenon keeps getting new names |
Examples make abstract concepts concrete | The definition consists of even more unexplained technical terms |
The technical language helps the reader learn | Technical language becomes a barrier between knowledge and the reader |
Technical terms
Key concepts when working with technical terminology
English technical term | Explanation |
Technical Term / Domain-Specific Term | An established word or expression used within a specific field of study to designate a professional concept as precisely as possible. |
Concept | A mental or professional concept of a phenomenon, a property, a process or a relationship that we use language to describe. |
Terminology | The overall system of technical terms and concepts used within a specific field. |
Definition | A formulation that explains and defines what a particular concept means in a given context. |
Context | The information and context surrounding a word or concept that helps determine how it should be understood. |
Semantics | The study of meaning in language and signs, and how words, expressions and sentences represent meaning. |
Ambiguity | A situation where a word, phrase or statement can be interpreted in several different ways. |
Conceptual Framework / Vocabulary | A set of coherent concepts that make it possible to describe and understand a field of study in a systematic way. |
Controlled Vocabulary | A defined set of preferred terms that are used consistently to describe and classify information. |
Keyword Stuffing | Unnatural and excessive repetition of words or search phrases in content, usually in an attempt to influence search engine visibility. |
We have only just begun.
Magne
Friend...
Now I actually see technical terms in a completely different way.
I have often thought that difficult technical terms made a text more inaccessible.
The buddy
They can do that.
If we use them poorly.
Magne
But if we explain them...
They can actually make the text more precise while the reader learns the technical language.
The buddy
Exactly.
There is a difference between displaying knowledge and communicating knowledge .
Magne
But now we've started getting quite a lot of content.
Theme pages.
Theme clusters.
Technical terms.
Articles.
Definitions.
Internal connections.
The buddy
Yes.
And then a new question arises.
Magne
I think I see it.
Some articles are quite narrow and answer one specific question.
But surely we also need some large articles that bring together the most important parts of an entire field of study?
The buddy
Just.
Content that stands firmly at the center and gives the reader a solid foundation before we send them on to the in-depth content.
Magne
So now we're going to build the actual support beams?
The buddy
We can call them that.
For the next question is:
How do we build cornerstone content?
And buddy...
We have only just begun.
Academic background and further reading
This series also builds on my own professional journey through the Web Design study , the eMarketing study , Innovation and Commercialization and professional seminars in San Francisco and Oxford . Here you will find the background, professional environments and experiences that have followed the development from the early years of the web to today's digitalization.
Recommended literature
Developments in artificial intelligence are moving faster than perhaps any other field of study in our time. No single book can provide all the answers, but good books can provide a solid foundation for understanding the technology, the opportunities, and the challenges.
In the KI-Kompis series, we therefore recommend a selection of books that illuminate artificial intelligence from different perspectives – technology, strategy, management, innovation, ethics, digitalization and practical application. Together, they provide a broader understanding of how artificial intelligence affects people, businesses and society.
Click on the book icon to see the full literature overview with recommended books on artificial intelligence.
Recommended books from our library
Content Strategy for the Web (2nd Edition)
Author/authors: Kristina Halvorson and Melissa Rach
Short review
How do you create content that actually helps people – and at the same time supports your business goals? Content Strategy for the Web is considered one of the most influential books in the field of content strategy and digital communications. The book shows how good content does not arise by chance, but through a deliberate strategy where user needs, the organization's goals, structure, work processes and management are closely linked.
The authors take the reader through the entire process – from planning and organizing to publishing, managing and continuously improving content on websites and digital services. Although technology has evolved since the book was published, the principles of quality, relevance, management and long-term content work are at least as relevant in an era where search engines and artificial intelligence assess the credibility and usefulness of content.
Why we recommend the book
At The Invisible Capital, we believe that good content is one of the most important forms of invisible value creation. A website is far more than design and technology – it is the content that builds trust, creates great customer experiences and helps people find the answers they are looking for.
This book is perfect for leaders, communications consultants, content producers, web editors, UX designers, and anyone working with digital services. It shows why a clear content strategy leads to better user experiences, more effective interactions, and stronger digital results over time.
In an era where artificial intelligence is increasingly important in how information is discovered, understood, and communicated, this book is more relevant than ever. It reminds us that technology alone never creates value – it is good, structured, and relevant content that makes the difference.
Don't Make Me ThinkAuthor: Steve Krug
Short review
Don't Make Me Think is one of the world's most influential books on usability and web design. Since its first edition in 2000, the book has helped designers, developers, content producers, and managers understand a simple but powerful principle: Good digital services should be intuitive. The user should be able to complete their task without having to stop and think about how the website works.
Why we recommend the book
This is one of the books that has had the greatest impact on my own work with digital services. Over the years – from SAS and the Norwegian Opera & Ballet to working on Bærum Municipality’s website – the principles in this book have been an important reminder that technology is never an end in itself. The goal is to make everyday life easier for the people who use the services. Despite the fact that the book was published many years ago, the message is just as relevant today.
Internet Marketing & eCommerce
Authors: Ward Hanson and Kirthi Kalyanam
Short review
Internet Marketing & eCommerce provides a thorough introduction to how the internet has changed marketing, commerce, and business development. The book combines theory and practical examples in digital marketing, e-commerce, customer behavior, value creation, and digital business models. Although written at a time when the internet was still in its infancy, many of the fundamental principles are still highly relevant.
Why we recommend the book
This book was an important part of my own learning journey in digital marketing and e-commerce. It helped build my understanding of how technology, customer experiences and business strategy are interconnected – an insight that later became very important in my work with SAS, the Norwegian Opera & Ballet, Bærum Municipality and eventually the project The Invisible Capital. Many of the ideas about customer value, digitalization and innovation presented on the website have their roots in the knowledge this book conveys.
The Innovator's Dilemma: When New
Technologies Cause Great Firms to Fail
Author: Clayton M. Christensen
Short review
The Innovator's Dilemma is one of the most influential books on innovation and technological change. Clayton Christensen introduces the concept of "disruptive innovation" and shows how even the most successful businesses can fail when new technologies and business models change the market. Through a series of examples, he explains why established companies often have difficulty adapting to radical change - even when they do "everything right."
Why we recommend the book
This book has had a major impact on how I view innovation, digitalization, and change management. It provided a new perspective on why established businesses are challenged by new players, and why the ability to think differently is crucial in a world characterized by continuous technological development. Many of the reflections in The Invisible Capital on innovation, digital transformation, and value creation are based on the insights Clayton Christensen conveys in this classic.
Mastering AI: A Survival Guide to Our Superpowered Future
Authors: Jeremy Kahn
Short review
Mastering AI takes the reader behind the scenes of the companies and researchers shaping the modern AI revolution. Jeremy Kahn explains how artificial intelligence is developed, the technological breakthroughs that have made today's language models possible, and how AI is impacting business, politics, and society.
Why we recommend the book
A highly relevant book that combines technology, business, and societal development. Perfect for leaders, decision-makers, and anyone who wants to understand where artificial intelligence is headed.
AI Needs You
Author: Verity Harding
Short review
AI Needs You is about why artificial intelligence is not just a technological issue, but also a question of democracy, ethics and social development. Verity Harding argues that the AI of the future must be developed in collaboration with people, governments and business.
Why we recommend the book
An important book for anyone who wants to understand how artificial intelligence affects society and why responsible development will be crucial in the years to come.
The Worlds I See
Author: Fei-Fei Li
Short review
The Worlds I See is the personal story of Fei-Fei Li, one of the world's most influential AI researchers. The book combines autobiography with the history of the development of modern artificial intelligence, showing how research, technology, and human values are closely intertwined.
Why we recommend the book
An inspiring book that provides a unique insight into the development of artificial intelligence through the eyes of one of the field's most central researchers.
© 2025 - 2026 Portico Publish | The invisible capital Privacy and use of the website | Developed and operated by Magne Bjella | Powered and secured by Wix
Comments