The photo listed below is one I have often made use of in clarifying sensemaking with the PKM framework. It describes how we can make use of various types of filters to inquire and understanding and after that apply this by doing and producing, and after that share, with added value, what we have learned. One arising obstacle today is that our mathematical understanding filters are becoming dominated by the outcome of generative pre-trained transformers based on big language models. And a growing number of, these are generating AI slop Which implies that machine filters , like our search engines, are no longer trusted resources of info.
Therefore, we have to build better human filters– professionals , and topic networks
As search engines and efficiency devices maintain spewing the very same– or a variation of– slop, we move toward “an orthodoxy that ruthlessly tightens public thought” (John Robb). Generative AI and their surprise algorithms are hacking away at 3 points that human organizations require to find out, innovate, and adjust– variety > > understanding > > depend on
We need to ditch these sloppy devices and concentrate on linking and communicating with our fellow human beings. Keep generating human-generated writing, like blogs, and use social networks that is not algorithmically generated, like Mastodon We have actually just ended up a PKM workshop with a global accomplice and the consensus from individuals is that abilities such as media literacy, crucial reasoning, and interest are still essential for making sense of our technologically connected world.