The advent of Artificial Intelligence (AI) is alarming in many fields of technology, with technical writing being no exception. Individuals in this field fear AI replacing technical writers.
Mike Dodaro answered a question on Quora concerning AI replacing technical writers. His response was :
“Not likely. Technical writers generally write about new products that AI hasn’t yet researched. Stack Overflow disallowed answers generated by ChatGPT. Evidently, too many of them were junk.”
This notion is far from reality. Despite advancements in this field, technical writers must adapt to these technologies and find ways to use them in writing quality documentation.
In this article, you will learn:
What is AI?
What AI tools do you need?
Relevance of AI in technical writing
The complexity of AI for technical writing
Overcoming the complexities of AI in technical writing
The future of technical writing with AI
What is AI?
Artificial Intelligence is a field of computer science focused on the simulation of human intelligence in creating machines to perform tasks. This includes abilities like problem-solving, learning, decision-making, etc. They are trained in a manner that would enable them to perform tasks. AI encompasses a broad range and has various branches, including:
Machine Learning(ML): This field allows machines to learn from data without explicit programming.
Deep Learning: An aspect of ML that requires the structure and function of the brain using artificial neural networks.
Natural Language Processing(NLP): Focuses on developing algorithms and techniques that enable computers to interact with, understand, and process human language.
Various fields like software, healthcare, finance, and transportation have integrated AI applications.
However, there are many complexities associated with using AI for technical writers. This will be discussed later in this article.
What AI tools do you need?
These tools can significantly enhance your ability to craft engaging and high-quality documentation.
ChatGPT
For example, ChatGPT is a large language model developed by OpenAI and first introduced in 2018. It generates content based on a prompt.
Since its evolution, ChatGPT has become a valuable asset for technical writers. It can help with tasks like making outlines, generating ideas, explaining complex concepts, aiding research, and offering advanced features.
ChatGPT offers various plans to suit user needs:
Free plan: This plan gives you access to unlimited messages, interactions, history, and the GPT-3.5 model. It is supported on the web, iOS, and Android.
Plus Plan: The Plus plan requires payment and provides access to GPT-4, additional tools like DALL.E, browsing, and advanced data analysis.
Team plan: This paid plan grants access to everything. It includes an admin console for managing workspaces.
Here is an example of prompting ChatGPT to write a troubleshooting guide
Gemini AI
Another example of an AI tool for technical writers is Gemini AI, formerly known as Bard, developed by Google and based on a large language model. Gemini AI is a powerful tool.
It aids technical writers in conducting research by crawling information from Google and providing cited links for content. You can also upload images as prompts.
Additionally, Gemini AI has a microphone feature for recording prompts. The Gemini AI comes in three optimized sizes:
Gemini Ultra: This model tackles highly complex tasks.
Gemini Pro: This model is designed for scaling across various tasks.
Gemini Nano: This model is optimized for on-device tasks.
An example using the image feature of Gemini AI
Grammarly Go
Lastly, Grammarly Go is an AI tool integrated with Grammarly. It helps writers rewrite, compose, and brainstorm content ideas and generate content for emails, articles, and websites.
Here are some additional AI tools you can leverage:
Relevance of AI in Technical Writing
AI is a powerful tool that enhances and streamlines the workflow of producing technical documents. The benefits are stated as follows:
Improved Documentation: It provides feedback and suggestions on areas that need improvement in your documentation.
Content Generation: AI is programmed to crawl information from various websites. This helps it extract relevant information from online content, thereby generating better content. It also assists in drafting outlines.
Grammar and spelling check: AI tools like Grammarly enhance technical writers' ability to improve their documentation. These tools detect grammatical errors and punctuation and provide suggestions to ensure consistency and accuracy in documentation.
Translation: AI translation tools help technical writers create documentation in multiple languages, reducing the cost of paying a translator. However, human review is required for accuracy.
Research Assistance: AI provides support in researching specific subject matters. It gives you insight into topics, bringing about an understanding of the subject matter. In essence, you can adapt AI tools as refined versions of search engines.
Content Management: AI content management systems help organize and update documentation. They also ensure version control and track changes in documentation.
Benefits of AI in Technical Writing
Cost Saving: AI reduces the cost associated with translating documents. With AI-powered translating tools, paying a translator for the work would be less important.
Saves time: AI chatbots save time replying to large messages. They are trained to respond to automated instructions, which is faster than manually replying to messages.
Improved accuracy and consistency: This is seen in its ability to detect grammatical errors, ensuring consistency and accuracy, thereby producing high-quality content.
Complexity of AI for Technical Writing
While the benefits of AI are numerous, it poses certain challenges in technical writing.
Content Authenticity: No company wants fake content. From my personal experience, I can easily detect content written with AI. Today, most AI gives out similar information; imagine everybody using a similar prompt. This will reduce the authenticity of the information displayed to users.
Interpretation: AI may be unable to interpret hardware or software and document the steps. You can only utilize it to produce documents and starter content. In this situation, a technical writer must interpret and optimize end-user content.
Poor data quality: Some aspects of technical writing require getting data from engineers. AI cannot give you exact data that requires practical experiments. Even if you prompt it, the data may not be accurate and prone to errors. In technical writing, one of the goals is to provide original information to your audience.
Lack of Personalization: AI content lacks insight into your target audience, background, and individual preferences. Thus, it produces content that does not resonate with the end user's problem.
For example, a technical writer is assigned to write about a product. The technical writer will have to rely on the information provided by subject matter experts(SMEs) to gather information about the product. An AI cannot provide the information the technical writer will gather from these individuals.
Security: AI tools don’t understand the importance of handling sensitive data. Thus, utilizing AI for content generation creates issues, such as accessing unauthorized data, which poses a risk to information confidentiality and the generation of inferior content.
Lack of Creativity and Style: AI lacks creativity, and its content may not be appealing and engaging for readers.
Collaboration: AI cannot collaborate with SMEs and other stakeholders to gather information, which reduces its relevance in technical writing.
Lack of Domain Expertise: AI lacks understanding and expertise in specific domains because it may not understand their complexity.
Content Evolution: In this era, technologies are changing every day. AI does not possess the ability to reflect those changes. However, it can help update but may need more contextual understanding to make informed updates.
Overcoming the Complexities of AI in Technical Writing
Technical writers should validate AI-generated information and content from trusted sources and current industry trends.
In addressing security issues, there should be an equilibrium between guidelines and ethical principles. Some of these principles include transparency, fairness, and involving stakeholders in designing and developing AI systems.
Technical writers should collaborate with AI systems to refine content to ensure credibility and accuracy.
Prompt engineering should be an additional skill in technical writing. These systems garbage in and garbage out the information they are prompted with, enhancing technical writers' ability to get clear and relevant information.
Gather feedback from stakeholders and potential users to review the authenticity of the content.
Your content should be user-centered. In essence, you are keeping information concise, breaking down technical jargon, and ensuring consistency throughout your content.
Implementing NLP tools that are capable of generating text that sounds more human.
AI should be trained to produce quality data.
The Future of Technical Writing with AI
In an interview with Tirzah Alexander, She says, “For now, AI can’t detect complex nuances in language, intonation, or tone. AI is expanding, but it remains limited to what a person tells it to generate or do.”
The future of technical writing with AI will remain. AI cannot replace technical writers. Instead, it will improve the writing process. Technical writing is a creative process that requires human expertise.
As AI continues to evolve, technical writers can leverage this technology, as it makes work easy, faster and saves costs.
However, it's important to remember that AI systems are not a complete replacement for human expertise. Human input is needed to maintain and train these tools, ensure accuracy, and improve the overall quality of technical documentation.
At the same time, don't focus your content on AI. This will diminish your authenticity. No company wants AI-generated content in its blog.
Wrap up
In summary, AI assists technical writers in producing quality technical documentation. It is a tool that makes technical writing efficient. The best approach is to use AI tools with human expertise. This will ensure concise and relevant documentation.