Contents
There are some basic phrases that come up again and again when you ask tech writers about AI. After so many years of waiting to implement an AI strategy, many companies have decided to dive in and embrace the new. We're told not to fear AI, that AI can enhance your business capabilities, improve your output, save you time and more. Or, we are told that AI is going to replace you. The truth of AI is somewhere in the middle, the grey in between.
This presentation explores the impact of AI on technical writing, highlighting successes, failures, and ethical challenges. The grey zone addresses dual-use technologies, plagiarism risks, and balancing AI efficiency with human oversight. It emphasizes the need for ethical AI deployment, industry standards, and upskilling technical writers.
The conclusion calls for embracing AI responsibly while maintaining a human-centered approach to ensure quality, inclusivity, and trust in technical writing.
Takeaways
Practical examples of AI's best and worst case use - what's most likely to go wrong or right and how to navigate from wrong to right
A list of tasks worth consulting AI (improving output)
A list of tasks you're better off using anything but AI
Prior knowledge
none