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Designing Intelligent Content for AI – Part 1

Welcome to the first of a dual part series on writing for Artificial Intelligence. Let’s begin with a discussion on understanding and designing Intelligent Content.

Artificial Intelligence is a hot topic. From intelligent virtual assistants like Google Home and Amazon’s Alexa, to chatbots and more, AI as a household discussion is becoming more prevalent. If you haven’t jumped on the bandwagon, however, how do you get your content ready for a future full of AI assistants? And what does this mean for a content developer?

The AI industry is evolving rapidly making the voice and text-based user assistance commonplace. Consider it a form of hired help, with each AI assistant providing a different set of skills based on your need.

What is Intelligent Content?

Intelligent Content is not only the content itself, but the combination of human and technological brains working in tandem. In other words, it is the way the content is structured, allowing it to be used efficiently and intelligently. Intelligent content is intended to be segmental, structured, reusable, format-free, and semantically rich. This allows content to be manipulated and accessed anytime, anywhere, device independent.

Content is everywhere within our organization in varying forms, including: customer documentation, FAQ’s, knowledge base, and online help. So where – and how – do we begin?

Audit existing content

Before starting, we should always know where we are: how much content is available; can it be used; should it be modified; etc. To understand this, it is important to perform a thorough content audit. The auditing process can help us better understand existing content, past content, and the gaps in content. This information can then be used to analyze and create a content model.

Create a content model

A content model is not a menu or a decision tree. A content model is context-independent and therefore enables you to map out the content types, output platforms, and metadata elements for each content type. From here, you can create consistent, predictable, and logical guidelines for content creation while at the same time providing structure to your source content for scalable, future-proof content.

Create a content library

When creating your library, use the following structure to be able to maximise your content:

  • Taxonomy: Capture and create content using taxonomy. The first function of a taxonomy is to help people understand the structure of a knowledge domain at a glance. Predictability is the most important feature of good taxonomy design. It is necessary to understand the natural categorization patterns of your different user communities, and to balance out the ways that they compete or conflict with each other.
  • Metadata: Metadata drives search. Increase searchability by thoroughly tagging all or parts of your content, making it semantically aware. The product and its features are tagged with metadata, enabling it to be indexed and sorted.
  • Reuse: Create a content source once, and reuse content several times. This allows several components to be used multiple times for outputs of different formats, and allows content to be easily updated across multiple devices, platforms, and outputs.
  • Granular Content: Each piece (independent pieces) of content you create becomes discoverable, reusable, and adaptable to your output requirements.

Context-driven content delivery

There is a paradigm shift in the way end users access information. We have multi-channel delivery methods such as customer portals, smartphones, chatbots, and AR apps to access and consume information anywhere, at any given time.

To create content that is adaptable, we need to move from concept and task-based writing to context-based writing. We can use the following elements to create stand-alone, format independent pieces of content that’s both intelligent and efficient:

  • Capturing Context
  • Classifying Intents
  • Defining Entities
  • Matching Context and Content

Stay tuned for the sequel of this post where I will be diving deep into content modeling and context based writing with examples for AI!

Ruchi Vohra has over ten years of experience as a Technical Writer with extensive experience in techcreating documentation from scratch and rebranding the existing documentation for Networking products, Public safety domain, and Financial sector. She is passionate about researching in the fields of Agile Methodology, User Experience through UI and UX, and Information Experience.

 

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