Be aware of the right to repair

The European “Right to Repair” directive gives customers the right to easier, faster, and cheaper repair of products, and the incentive to manufacturers to make longer lasting products. This is good news for anyone working with technical documentation, since the need for repair instructions will increase. 

Written by: Karin Askeroth

Prolonged product lifecycle 

Photo: Wix

In April 2024, the European parliament adopted the “Right to Repair” directive for customers. This new rule requires manufacturers to provide customers with timely and cost-effective repair of their products, even after the current EU required two-year minimum warranty expires. EU countries have been granted two years to incorporate this directive into their national legislation. 

There is hope that this initiative will extend the life cycle of the products included in the legislation, as well as strengthen the EU repair market, whilst reducing costs for customers. Simply put, manufacturers will be bound to providing spare parts and tools, cannot impede the use of second-hand or 3D-printed spare parts by independent repairers, and will not be able to refuse to repair a product that has previously been repaired by a third party.

How will the tech doc profession be affected?

One of the core components of the “Right to Repair” movement is the availability of repair manuals. We can expect a rise in demand for detailed, user-friendly repair instructions.  

• Technical writers will play a crucial role by creating clear, accurate, and accessible documentation for a broad audience.

• Documentation that consists of structured modular content will enable reuse of content, which in turn saves time and resources.

• There will be a need for documentation aimed at different user groups, for example repair professionals and the customers themselves.

Efficiency using  modular content

Photo: Wix

The use of modular content will effectivize work with technical documentation since it will maximize customer relevance while it decreases the personalization effort to as few and small components as possible. The personalization can be built by combining components to make the material meaningful for different user groups.

The upside of this method is that less content creation is needed to produce an exponential variety of tailored experiences.

Summary: The “Right to Repair” directive will mean an increased need for technical documentation by professionals, aimed at several different user roles. We believe that the ability to work with structured modular content will be especially important.

Our advice to you: To anyone working within tech doc: make sure you master structured modular content, reuse of content, and how you can use AI to make your work easier. To employers: having access to tech doc competence ensures your technical documentation is transformed from a barrier to a bridge, which helps you avoid issues like misunderstandings, errors, and wasted resources.

Read the whole legislative resolution

Overcoming the challenges of coaching a remote team

Being a consultant often means seeing more of your assignment colleagues, than of your colleagues at your consultancy company. As team coach it’s my task to, despite this, create a team spirit with my colleagues at informiQ in Linköping and Stockholm. Keep reading, and I will tell you how I work with overcoming the challenges of coaching a remote team. 

Written by: Mari-Ann Gripmark

The main challenge: 

We do not work together, and we do not even live in the same city. We meet in person only a couple of times per year. 

Our goals:

• Get to know each other.

• Get to know ourselves.

• Create an open climate where everyone feels comfortable and safe.

Image by: Freepik

Why are we doing this?

As a consultant, I am encouraged to look out for new consultancy assignments, both for myself and for my colleagues. This is a much easier task if I know not only my colleagues' competencies, but also their personalities, preferences, and goals.

As a consultant, I am responsible for my own competence development. Discussing with others helps me get new ideas and find new ways.

The solution we have tried so far:

Bi-weekly team meetings (remote): At each team meeting we make time for some chit-chat, but there is also a main purpose. Here are some examples of activities so far: Each team member presents his/her consultancy assignment, with focus on what he/she enjoys most and least.

• Team building games to get to know each other better.

• Exercises to find your personal motivators and understand what makes you enjoy your daily work. (based on https://management30.com/practice/moving-motivators/)

• Talk about what would be our dream consultancy assignments.

A Slack channel just for us: Anyone in the team can write about anything. Team coach posts at least once a week: Interesting links, questions, information or (most often) just a GIF or a thought.

Challenge: How to prioritize the team meetings? 

From a team building perspective, it would be better to see each other more often than every other week. You have to make a trade-off though, between team building and working on your consultancy assignment. This trade-off may look different for different organizations.

Challenge: How to use the Slack channel?

The Slack channel is a great place for sharing thoughts, problems, and tips as well as weekend plans. Though, if chatting in a Slack channel does not come naturally to the team members, there is no use trying to force this. In that case, focus on relevant information. Discuss how you want to use this channel within the team!

Image by: Freepik

Summary: To feel comfortable sharing thoughts and ideas, we first have to feel that we are a team and that we trust each other.

Our advice to you: Creating a safe and comfortable space for the team should be your top priority.

Do not underestimate the power of simple team building games that make us laugh together. Involve all team members in planning, discussions etc, but do not try to force anyone. 

Do you feel that AI is like rocket science? Well, it's not.

The idea that tools like ChatGPT, Google Bard, and various image generators seem almost alien is quite understandable. However, the reality is that when we peel back the layers, it all makes complete sense. These AI innovations are grounded in principles that are accessible and relatable once demystified. So AI is, in fact, not rocket science.

Image: Unsplash

Unveiling the Friendly Face of AI

Let's clarify one thing before we start: AI isn't about to take over the world. Essentially, AI splits into two types - ANI and AGI. The type of AI that's rapidly advancing today is known as weak AI, or ANI, and it’s exceptionally good at playing by the rules – quite literally. It's specialized, task-oriented, and a bit like that one friend who's an encyclopedia of knowledge on one topic, yet can't seem to change a light bulb. When most people think of AI, they're actually imagining AGI, a theoretical AI that thinks and learns like humans. But this isn't our reality yet, nor the focus of current developments.

It all starts with data, a lot of data

The heart of today's AI systems beats with a rhythm set by data. It's the fuel that powers the intricate engine of ANI. Just like an artist needs paint, AI needs data – and not just any data, but vast, diverse, and quality data. This abundance of data enables AI systems to learn, adapt, and excel in their designated tasks. In the world of AI, data isn't just king; it's the entire kingdom.

Data + Machine Learning = The evolution of digital intelligence

Diving deeper into the AI realm, Machine Learning (ML) stands out as the star player, the most effective technique in building AI systems. ML addresses the critical question: "How do we get computers to learn from data without being explicitly programmed?" It 

empowers AI systems with the ability to learn from experiences, improve over time, and tackle increasingly complex tasks. Crucially, ML isn't a one-size-fits-all solution; it's a diverse umbrella encompassing various techniques, each suited to different challenges.

Image: Wix

How AI learns to perform tasks independently

Peeling back the layers of AI's complexity, we find its core techniques in ML:

• Supervised learning is like a guided tour; the model is trained with labeled data, learning to predict outcomes based on past examples. 

• Unsupervised learning, in contrast, is akin to exploration without a map, where the model sifts through unlabeled data to detect patterns or clusters on its own.

• Reinforcement learning is the adventurous cousin, learning by trial and error, making decisions and adjusting based on feedback. 

Extending this is generative AI, a sophisticated offspring of supervised learning, which goes beyond prediction to creation. Each technique is a testament to AI's logical foundation: give a model data, and it learns to perform tasks independently, debunking the myth of AI as incomprehensible “rocket science”.

Tech writer or not - embrace AI

AI marks a paradigm shift, redefining problem-solving and innovation. Adopting AI puts us at the forefront of this revolution, beyond just following a trend. In the realm of technical writing, embracing AI means tapping into a suite of smart tools that enhance writing efficiency and content quality. Imagine AI as a behind-the-scenes collaborator, refining language, aiding in creative content generation, optimizing for SEO, and offering insights from user feedback. This integration of AI streamlines the writing process, elevating the technical writer’s role from just crafting words to strategically shaping impactful content.

Image: Wix

Our advice to you:

At the end of the day, AI refers to the development of systems capable of tasks that usually require human intelligence. But here's the twist – whether you're a tech writer, a marketer, or a project manager, instead of fretting that AI will usurp your job, focus on how it can enhance your daily tasks. 

AI isn't here to snatch away our roles; it's here to redefine them.

It's not about AI taking our jobs; it's about AI taking the jobs of those who don't embrace it. 

If you want to learn more about AI: https://www.deeplearning.ai/.

If you're looking to find AI tools tailored to your profession, visit https://genai.works/  - kind of a one-stop destination for all leading AI applications and software.

Written by: Victoria Björnblad