It’s that time of year for us to gaze into our crystal ball and share your and our predictions for the future of technical communication for 2024 and beyond.
Transcript
This is the Cherryleaf podcast. Hello and welcome to the Cherryleaf podcast. What we do at the end of the year is we look at trends for the following year.
And that’s what we’re going to be doing in this episode. We’re going to be looking at trends in technical communication for 2024 and beyond.
We’ve done the same as we’ve done in previous years and that is to pose the question on social media and to see what responses people provided. So I’m going to be going through some of those.
We’ve also done something differently this year and we’ve also asked a couple of chatbots. What they see as being trends for the future.
We didn’t get as many responses from people on social media as in previous years, and that might be a reflection on the decline of some of the sites. But anyway, let’s go through the responses that we had.
On LinkedIn John Saunders said:
I see productivity improvements, as technical writers encounter AI assist (intentionally or by accident) through the tools they already use. For example I’ve seen that already with the Confluence beta Atlassian Intelligence. It, for me, is the moment of “Oh, that’s an interesting way of putting it, I can rework that”.
On the Write The Docs forum, Bogdan Crudo replied:
The transition from simple (or clear cut) to elaborate will continue on in 2024. Added layers of complexity will increase the time needed for users to traverse material. Beautified UI elements will continue to bedazzle documentation while steering it further away from its functional purpose: clear, simple and boring looking.
On Blue Sky, Craig Wright replied
Short term: more widespread use of AI for all aspects of content creation and management. Longer term: People communicate with machines naturally, machines do what they ask for. No docs just prompts.
Ed Marsh on Twitter replied:
Everyone and their mom will want you to have some sort of AI solution for your docs… yesterday.
And as I said, we also asked some chatbots what they thought would be the trends for 2024 and beyond.
We asked ChatGPT that’s ChatGPT using GPT 4. The more powerful version of the large language model that drives ChatGPT. As it replied:
The future of technical communication beyond 2024 is likely to be shaped by several key trends:
1. **Increased Reliance on AI and Automation**: AI tools will continue to evolve, aiding in the creation, translation, and customization of technical content. They might be used for tasks like generating first drafts, providing real-time language translation, and creating personalized user documentation.
2. **Greater Emphasis on User Experience (UX)**: There will be a stronger focus on delivering clear, concise, and user-friendly technical content. This might involve interactive elements, more visual content, and a shift from text-heavy documents to more engaging formats.
3. **Expansion of Video and Multimedia Content**: Given the rise in preference for visual learning, technical communication will likely include more video tutorials, animations, and interactive simulations. This can help in explaining complex concepts more effectively.
4. **Collaborative and Agile Workflows**: The adoption of agile methodologies in technical writing teams will continue, with an emphasis on collaboration, flexibility, and rapid response to changes.
5. **Integration with Emerging Technologies**: Technical communicators will increasingly need to understand and document emerging technologies like blockchain, quantum computing, and advanced robotics.
6. **Focus on Accessibility and Inclusivity**: There will be a greater emphasis on making technical documentation accessible to diverse audiences, including those with disabilities, and ensuring content is culturally sensitive and inclusive.
7. **Growing Importance of Data Analysis**: Technical communicators will increasingly use data analytics to understand how users interact with their documentation, enabling continuous improvement of content based on user behavior and feedback.
8. **Environmental Considerations**: Digital documentation will continue to grow in preference over printed materials, driven by environmental concerns and the need for easily updateable content.
9. **Globalization and Localization**: As businesses continue to operate on a global scale, there will be a higher demand for localization of technical content, ensuring that it’s culturally and linguistically appropriate for different regions.
10. **Continued Professional Development**: Technical communicators will need to continuously update their skills, not only in writing and communication but also in technical domains and technology tools to keep pace with the rapidly changing tech landscape.
And it finished with:
Overall, the field of technical communication is expected to become more dynamic, user-centered, and integrated with cutting-edge technologies.
And we also asked another chatbot called Claude. And it replied:
Online Help Innovations in 2024
In 2023, we saw exciting new developments in online Help like intelligent chatbots, augmented reality guides, and greater personalisation. As we look ahead to 2024, experts predict even more innovative Help solutions leveraging cutting-edge technology.
### Self-Diagnosing Help Systems
One area expected to grow is self-diagnosing help systems powered by artificial intelligence. These systems will allow customers to describe an issue in their own words. Advanced natural language processing will then analyse the problem and match it to the most likely fixes. Some programs may even ask clarifying questions if more details are needed. The final result will be a custom set of troubleshooting tips aimed at the core issue. With less need for back and forth, these AI-powered systems could resolve customer problems faster than ever.
### Interactive Virtual Assistants
Chatbots and other virtual assistants are also expected to become more advanced and life-like. New speech synthesis and speech recognition technology will allow for natural conversational exchanges. The assistants may even adopt human-like personalities and voices tailored to specific brands. These interactive helpers could field customer inquiries, recommend solutions, and guide users through detailed steps to address issues. Think Siri or Alexa but specialised for customised Help across industries.
### Predictive Help Recommendations
We may also see Help systems that anticipate user needs before they even ask. This proactive approach would use predictive analytics to determine where customers might need assistance. If the system detects a user struggling with a task like setting up a new device, it could automatically offer tips without requiring prompts. These predictive recommendations would provide help right when users need it most.
### Intelligent Chatbots
One major innovation is the improvement of chatbots that rely on artificial intelligence and natural language processing. Chatbots are becoming better at understanding context and holding true conversations. Companies like Google and Microsoft are developing chatbots that can answer common customer service questions with increasing accuracy. Some of these AI helpers can now point users to relevant Help articles or even walk them through fixes step-by-step. The ultimate goal is for these chatbots to serve as virtual assistants that resolve issues quickly without the need for human involvement.
### Augmented Reality
Augmented reality (AR) is also coming to online Help in the form of interactive troubleshooting guides. With AR, users can hold up their phones to equipment and get overlayed instructions right on their screens. For example, Ikea offers an AR manual that shows shoppers exactly where different furniture parts go. Companies can now create these AR helpers for their products so customers get precise visual assistance. The technology is still emerging but holds promise for enabling self-service Help.
### Greater Personalisation
Online Help is also becoming more personalised to serve users’ specific needs. Help sites now use visitor data and machine learning to understand each user’s goal and knowledge level. Content is then tailored to give the most relevant Help to each person. Personalized recommendations also point site visitors to FAQs and troubleshooting materials likely to be most useful. This custom-fit approach makes the Help experience more streamlined.
And it finished with this statement:
While recent innovations have moved online Help forward, 2024 promises even more dramatic developments. As artificial intelligence and related technologies improve, we can expect more automated, visual, and personalised Help experiences. The end goal is to resolve all customer issues seamlessly behind the scenes.
So what about our thoughts at Cherryleaf regarding what’s going to happen in 2024 and beyond?
In some ways, we spent quite a bit of this year talking about the future on this podcast, and also on the YouTube videos that we’ve posted about AI in particular.
For this year, we’re probably less certain than in other years about where we will be in 12 months’ time. There’s likely to be a lot of change in the next 12 months.
We can expect that a lot of that change will be relating to APIs and to artificial intelligence, but exactly where we end up at the end of 2024 and into 2025 is hard to see from here, but let’s give it a go.
One area where we may see change is with the merging of content that’s provided for support, for training, and for documentation, and that users will access that information via an AI assistant, a chatbot, and get a personalized experience, the ability to self-serve themselves when they get stuck, when they would otherwise raise a support call.
And we’re likely to see more websites and more apps have chatbots, and that those chatbots become a competitive differentiator between one product and another. And so, the documentation that is fed into these chatbots becomes more important.
We may also see those chatbots within the app itself, a return to Clippy, as it were, in-app help, in-app chatbot user assistance.
And this may have an impact on traditional user documentation, be it a PDF user guide or an online Knowledge Base in that it may be that users go to that less, that they use chatbots instead of that traditional documentation.
Now, that doesn’t mean that there is less need for technical documentation. In some ways, it might become more important. Because if you want the answers provided by ChatGPT or Claude, you need that traditional documentation for them to find, to ingest into their large language models, and to provide those answers.
If we still see that there will be a place for Google and search engines, that people will still search on those types of sites, you’ll still need traditional documentation for those sites to spider and index and to provide the links when people get stuck.
Another thing to watch out for is the ability of artificial intelligence to understand video, to look at a collection of stills from a video, and to be able to describe what’s inside those stills.
Related to this is Google GoalCycle3D. This is part of a new way for AI agents to acquire knowledge from human demonstrations in real-time. This could be useful in techcomm: documenting machine maintenance and assembly.
And whether we get to the point where we can record a walkthrough of a video and then AI can generate a user guide from that walkthrough, understand the different elements, where the mouse is moving and so on, and get to perhaps a first draft or even look at an application, click on all the buttons, work out what the system does, and again generate a user guide.
There are early systems that can do that, but they’re limited to about one minute of video, but that may change over the next year.
Both of these are part of a trend we’ve called “demo to docs”.
We might see some of the more mundane tasks in technical documentation done by AI, for example, the creation of README files, an AI system that could look at changes in code or within an application and create a summary of that suitable for a readme document.
We think we’ll also see a lot of attempts at creating what you might call headless avatars, where the AI can generate the content and can generate an avatar, have that avatar speak, answer the questions that people have, and respond in a way that has the potential for generating a lot of content very quickly and cheaply.
But we do worry, or we do think, that there will always be an uncanny valley element to those avatars, that they never quite are the same or as effective as a real-life person. And of course, with that, if that ability does arrive, then you also have the ability for people to use those types of avatars for malicious purposes like pretending to be somebody to get money from a bank account or pretending to be somebody on an online dating site.
Another area we might see is the emergence of support systems or websites that provide a chatbot that provides answers not from just one source, like from one application, but from multiple sources. So similar to what we see with ChatGPT, and chatbots so specialized chatbots that somebody creates these and is able to make money by providing the answers for a range of different products. So it might be for fixing a range of different cars.
Behind the scenes, we think one big change we might see related to AI is the growth in automated agents, the ability to train AI agents together so that they can do specialised tasks and hand off their work to another AI agent that does the next step in that process.
What this means for technical authors, technical writers, is they need to take advantage of this opportunity to be the ones that are leading within the organization when it comes to using chatbots and artificial intelligence, they need the skills, they need to train, they need to learn. Otherwise, other departments might lead the projects and technical publications. The tech pubs department might get left behind
So what do you think? As always, like we say at the end of all of our podcasts, you’re welcome to let us know by emailing us info@cherryleaf.com.
We’ll provide links to our training course on using artificial intelligence and technical communication, and the YouTube videos that we’ve produced. And another series of YouTube videos that we participated in, which is around lessons learned in applying AI in technical communications.
If you’d like more information on Cherryleaf, our website is a good place to go cherryleaf.com.
So that’s it for 2023. Thank you for listening. We wish you a great holiday and good fortune in 2024.
More information
Microsoft’s Akash Dubey has created a YouTube playlist that contains a series of interviews with people from Microsoft, Meta, Across Systems, and Cherryleaf, on lessons learnt with AI:
https://www.youtube.com/playlist?list=PL1Utia1tpDy4cceBHsMDZFbyzVMWfijjG
Generative AI and Techcomm playlist on YouTube:
https://www.youtube.com/watch?v=LyzNPwCV9rY&list=PLUsv4sNfwtYe3Crhz-ldp8JRoKLIh7k8l&pp=iAQB
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