This week’s blog post is coming in just under the deadline wire because, admittedly, I’ve been distracted by all the goings-on in the world of tech. It’s CES week, when all the cool new tech is revealed. I’m especially interested in NVIDIA’s Project DIGITS, an “AI supercomputer on your desk.” This could be a game-changer for small businesses that benefit from running a model more specific to their industry with more straightforward security (I’m looking at you, freelance writers and editors).
But, DIGITS aside, today we share some tools you can use to judge for yourself which approach to AI is secure and fits your business needs.
Professionals need to use generative AI (genAI) with a clear understanding of the risks and benefits of specific platforms and uses. Sticking your head in the sand about genAI will, increasingly, render your business model obsolete, because you will not be able to produce as quickly as those who use genAI in some capacity. These days, business moves at the speed of genAI. (We can debate the virtues and pitfalls of this emerging approach to staffing and contracting, but that’s a topic for another day.)
In an effort to provide our Evergreen community with tools to understand how genAI works and how it may benefit members’ practice, I have pulled together some resources I’ve developed over the past months with the medical writing and editing community in mind. You can use these tools to form your approach to implementing AI in your practice.
- For an introduction to relevant terminology, I started a series that introduces AI terminology (Part 1 and Part 2) and provide examples for each term in the biomedical and health care context. I arrange the terms in an order of importance for medical writers and editors and write the related entries to be consistent with one another. For example, algorithm, training, model, and application are related terms that are part of a process, so they appear in sequence. The series can be found here. (More entries will be added as time allows.)
- To understand AI and machine learning in these contexts, check out the AMWA Journal piece The Use of Artificial Intelligence and Machine Learning in Clinical Research and Health Care. (I’ve worked in AI in the biomedical research context for nearly a decade as a consultant, writer, and merit reviewer, so I rolled it all up into a session for AMWA 2022.)
- An invited piece, Communicating About and With Artificial Intelligence Applications, provides a landscape view of AI, from theory to applied practice.
And don’t miss the AI resources we have compiled here at Evergreen in our Insights.
Last, but not least, keep an eye out for AMWA‘s new Artificial Intelligence Task Force. 2025 promises to be an exciting year in artificial intelligence for the medical communication community!