Following up on the “Ask Me Anything: How to Prepare for a New CMS” webinar, this post answers questions we received regarding the impact of AI on your CMS.

Our thanks to everyone who sent in questions! Your participation helps us craft future content that is of the most use to you, our colleagues.

Today’s post is about how Artificial Intelligence (AI) will affect data creation and management. AI and our adoption of it (even if unknowingly) is rapidly evolving in both capacity and potential application. I intend to explore AI and implications for broader museum work in the upcoming year. For today we’ll concentrate on how AI may impact or support museum data creation and remediation (aka cleanup) for the museum Collections Management System (CMS).

Q. How is Artificial Intelligence (AI) entering the conversation of data creation and management?

First, I’d like to provide a brief orientation to the AI landscape for the non-expert. There are several options available to facilitate your interaction with AI. Open AI’s ChatGPT is perhaps the most widely known, but other heavyweights such as Microsoft’s Bing AI and Google’s self-described “AI experiment” Bard are also available.

Open AI’s ChatGPT comes with the following description: We’ve trained a model called ChatGPT which interacts in a conversational way. The dialogue format makes it possible for ChatGPT to answer follow up questions, admit its mistakes, challenge incorrect premises, and reject inappropriate requests.

Microsoft’s Bing AI lists the functions its best known for: to create, organize, and compare anything. It can also give advice to help you pack for vacation or buy a thoughtful gift for a friend, or even tell you a joke.

Google’s Bard states it can help you brainstorm ideas, spark creativity, and claims that it can accelerate your productivity.

While AI tools can ultimately perform an unlimited number of action sequences, the functionality of focus for today’s post is the ability to inform, create, and edit content. For these popular tools, the interface is a chat box where you submit your initial query or prompts.

Here’s a topical example. I gave Bard the following prompt: How to effectively clean up museum data in a collections management system.

It sounded so familiar that I asked Bard to share its sources. This amusingly affirmed its #2 source as a previous blog post I wrote for Lucidea’s Think Clearly Blog.

With this kind of power and source checking in mind, here’s how I see AI supporting our data creation and cleanup work:

• Helpful for writer’s block when creating an object description or artist biography.
• Instructive for data management or cleanup approaches (as demonstrated in the prompt example above). As well as specific areas of data to cleanup via Excel Power Query or Open Refine.
• Pattern recognition and identification of areas for data for review.
• Data organization and remixing.

• Script creation to run with (mostly open-source) collections management systems to extract and/or transform data.

I encourage you to experiment, but also keep in mind that AI only knows what it has access to. The nature of our work means that ourselves as well as the non-accessible parts of our collection files are not available for AI to reference.

Conclusion

The potential for AI to influence our work in data creation and cleanup is great. However, as with all new tools, it will take time to learn (for both us and the AI!) and refine the efficacy of its application. I suspect we will see much more from AI and its potential for the museum field in the next year—stay tuned!