this post was submitted on 26 Mar 2024
398 points (100.0% liked)
Technology
37757 readers
358 users here now
A nice place to discuss rumors, happenings, innovations, and challenges in the technology sphere. We also welcome discussions on the intersections of technology and society. If it’s technological news or discussion of technology, it probably belongs here.
Remember the overriding ethos on Beehaw: Be(e) Nice. Each user you encounter here is a person, and should be treated with kindness (even if they’re wrong, or use a Linux distro you don’t like). Personal attacks will not be tolerated.
Subcommunities on Beehaw:
This community's icon was made by Aaron Schneider, under the CC-BY-NC-SA 4.0 license.
founded 2 years ago
MODERATORS
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
That reminds me of a fairly recent article about research around visualisation systems to aid with interpretable or explainable AI systems (XAI). The idea was that if we can make AI systems that explain their reasonings, then they can be a useful tool, especially in the hands of domain experts.
Turns out that actually, the fancy visualisations that made it easier to understand how the model had come to a conclusion actually made subject matter experts less accurate in catching errors. This surprised researchers and when they later tried to make sense of it, they realised that they had inadvertently dialled up people's likelihood to trust the model because it looked legit.
One of my favourite aphorisms is "all models are wrong, some are useful." Seems that the tricky part is figuring out how wrong and how useful.