sensemaking through the slop

The image below is one I have often used in explaining sensemaking with the PKM framework. It describes how we can use different types of filters to seek information and knowledge and then apply this by doing and creating, and then share, with added value, what we have learned. One emerging challenge today is that our algorithmic knowledge filters are becoming dominated by the output of generative pre-trained transformers based on large language models. And more and more, these are generating AI slop. Which means that machine filters, like our search engines, are no longer trusted sources of information.

As a result, we have to build better human filters — experts, and subject matter networks.

As search engines and productivity tools keep regurgitating the same — or a variation of — slop, we move toward “an orthodoxy that ruthlessly narrows public thought” (John Robb). Generative AI and their hidden algorithms are hacking away at three things that human organizations need to learn, innovate, and adapt — diversity > learning > trust.

We need to ditch these sloppy tools and focus on connecting and communicating with our fellow humans. Keep on producing human-generated writing, like blogs, and use social media that is not algorithmically generated, like Mastodon. We have just finished a PKM workshop [next workshop starts 16 February 2026] with a global cohort and the consensus from participants is that skills such as media literacy, critical thinking, and curiosity are still essential for making sense of our technologically connected world.