The Future of Knowledge Base in the Age of Generative AI
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It goes
without saying that technical writers create knowledge base articles for
internal teams and customers. The knowledge base article is available in a wide
variety of flavors, including user manuals, technical spec documents,
configuration guides, procedures, and software product features. These
knowledge base articles are read by humans, who then act!
This
paradigm shift is taking place in terms of how knowledge base articles are
produced, used, and some actions are carried out. The following technological
trends and consumer behavior are responsible for this change.
· Consumers who want things done
quickly will favor automating low-value, routine tasks with bots.
· Customers want rough answers to the
"right" questions so they can get things done more quickly.
· Rise of Generative Artificial
Intelligence (AI) makes enterprise applications more accessible to
non-technical users by streamlining knowledge discovery and content curation.
· an increase in people's faith in AI
systems
In this
blog, we'll examine how changes in consumer behavior will affect the creation
of knowledge base articles and how people will use them.
Change in Technical Writer Role
Technical
writers and knowledge base providers are still determining how the rapid
technological change following the release of ChatGPT-4 will affect their
respective job roles and technological platforms. However, as shown in the
table below, there is a change in consumer consumption trends for knowledge
creation, discovery, and consumption.
|
Trends |
Then |
Now |
|
Audience
of your knowledge base |
Humans |
Artificial
Intelligence bot |
|
Content
discovery engine |
Search
engines such as Google, Bing, and so on |
Generative
AI such as ChatGPT, Bard, and so on |
|
Content
discovery optimization |
Search
Engine Optimization (SEO) |
Semantics
content structuring |
|
Content
discovery mechanisms |
Search
keywords |
Prompt |
|
Outcomes
of knowledge consumption |
Humans
doing work |
Artificial
Intelligence bot doing work with minimal human intervention |
Technical
writers need to change the way they think when creating knowledge base content
so that it is understandable to AI bots and humans alike. Technical writers
have traditionally produced content primarily for humans, so this is a radical
change in how they do it now. Technical writers will create new knowledge for
AI bots in the future, particularly for Generative AI technologies. However, as
shown in the table below, the characteristics of writing for human consumption
and how to create content for AI bots are very different.
|
Characteristics |
Writing for humans |
Writing for an AI bot |
|
Content
length |
Concise
and precise |
As
explanatory as possible |
|
Use of
visuals |
Short
videos and gifs |
Media
content needs rich annotation |
|
Adding
Metadata |
Optional |
Mandatory |
|
Accessibility |
Mandatory |
Mandatory |
|
Inclusive
language |
Mandatory |
Mandatory |
|
Content
tone |
Can be
conversational, monotone |
Generic
tone |
|
Content
output |
Fixed |
Highly
customizable |
|
Content
design |
Mandatory |
Flexible |
Writing for Humans
Given the short attention span of
people, a technical writer must write knowledge base articles with concise
content. The traits are determined by a person's biology, psychology, and
cognitive abilities. This is equivalent to
·
The majority of people
have shorter attention spans, which restricts the content's word count and
reading time.
·
For quick learning, most
people prefer visuals and video. Because of this, technical writers create rich
multimedia content like screenshots, videos, and animated gifs.
·
Since most people prefer
simple language, technical writers are constrained to use a limited number of
words and vocabulary to convey complex ideas in straightforward language.
·
Humans are motivated by
emotions and ideologies; therefore, the content must be inclusive and open to
all people. The information cannot be biased.
Humans engage in specific actions as
described in the knowledge base article once they have read and understood it.
For instance, if a software user reads about a feature of a product in software
documentation, they may configure that software.
Writing for an AI bot
Technical writers must modify their approach when creating new
knowledge base articles for AI bots. An AI bot can interact with both humans
and other AI bots and has limitless computing power to synthesize new knowledge
and limitless storage to store massive amounts of data!
Given the traits of the AI bot,
writing for an AI bot or Generative AI requires a different approach. This is
equivalent to
·
Create content that is
as illustrative and structured as you can. Generative AI is capable of
condensing lengthy content into briefs and can simplify complex concepts.
·
More conversation-like
scenarios with examples are needed to make the content easier to consume by
generative AI technologies.
·
Semantic metadata
addition: Increasing the amount of metadata used to annotate content enhances
and expands the textual content.
·
Include FAQs - By
creating FAQs with a series of prompts (questions) and responses (answers), you
can train generative AI.
·
Keep a glossary of
business terms that includes definitions, nuances, assumptions, metrics, and
other information.
·
adding metadata to
textual information In order for Generative AI to decide whether to seek human
intervention when actions are automated, it is helpful to add metadata
indicating whether a specific action is an input to or an output from an
interface.
·
Related content a list
of articles that, from the perspective of a technical writer, are related to
the current articles
If technical writers create content
that is AI-friendly, then a customer can ask Generative AI what goal they want
to achieve. Precise steps can be provided by generative AI technologies like
ChatGPT, Bard, and others. Bot technologies like RPA and intelligent automation
through APIs will probably ask a customer if they want to carry out those
actions on their behalf.
Content Evaluation
How can we make sure that our current
publicly available knowledge base contents are prepared for generative AI
models to ingest and provide accurate answers based on our customers' prompts,
given that technical writers will produce content for AI bots? A sizable corpus
of text taken from the public internet is used to train large language models
(LLMs), such as ChatGPT. Your knowledge base content must be used by the LLMs,
so those language models must be adjusted. Numerous
examples of prompts and responses must be provided in order to fine-tune the
LLMs. This can be accomplished by creating numerous FAQs with questions and
detailed responses. The steps for technical writers to adapt their current
knowledge base to be AI-friendly are listed below.
·
Add more information and
clarifications to all of your knowledge base articles.
·
More metadata should be
added to text and multimedia elements.
·
Create a glossary of all
business terms and use them consistently throughout your knowledge base.
·
Create numerous FAQs
with numerous questions and laboratory responses.
·
To create a visual
connection between your content entities, add "Related Articles" to
all of your current articles.
·
Check all of your
content to make sure it is H1-H6 structured.
Metrics
When making efforts to future-proof
your current knowledge base, quantifying the efforts required to create the
content for your knowledge base is helpful. Vendors of knowledge base platforms
will develop tools to aid technical writers in creating content that is AI-friendly.
The metrics listed below can aid in winning over business stakeholders.
- Number of words per
article: 3000 – 5000 words
- Content structure
compliance: H1 – H6
- FAQs per article: 10 –
20 FAQs
- Business glossary: 20 –
30 business terms
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