Stephen Downes

This is from a few days ago but I want to make sure I don't forget it. Alan Levine, channeling some Mastodon discussion, points to a nice trick to get right of all the garbage in Google search engine results (by 'garbage' what I mean is all the stuff Google puts in the results page that isn't part of the search results). In particular, if you add '&udm=14' to the end of the URL on your results page, you can force it to display search results only. I do a similar thing with my personal Start Page, where I've created a small form to handle that for me. I also use '&tbs=qdr:y' to force it to return results only from the last year, so I'm not getting out-of-date results.

I've had discussions with people from time to time about the difference between networks and systems, and to me one of the main differentiators is this: a system has a purpose, and a network doesn't. Sometimes this difference can be difficult to parse, and this phrase, which originates with Stafford Beer, sits right along that dividing line. The idea that "The purpose of a system is what it does" (POSIWID) allows us to retroactively assign an intent to a system, even if it was not designed that way. A network, by contract, does not imbue cognitive properties; the structures and processes are purely physical, with no cognitive guidance whatsoever.

If you have beliefs about AI, one way or another, that you hold with religious fervour, then perhaps your faith is misplaced. AI is neither the stuff or prayers or nightmares; it occupies that mundane space in between. Moreover, as the Walrus puts it trenchantly, "The problems facing Canada or the world—not just climate change but the housing crisis, the toxic drug crisis, or growing anti-immigrant sentiment—aren't problems caused by a lack of intelligence or computing power... the fixes are difficult to implement because of social and political forces, not a lack of insight, thinking, or novelty."

There are two things we can draw from this short article. First, generative AI isn't to the point yet where it can reliably create things like employee handbooks (and therefore, other training materials). But second, the fact that companies are already using it for this makes it clear that when GAI is reliable, it will be widely used for this purpose. Via George Station.

The summary in Daily Nous says it all, I think: "You might not have heard the philosophy lectures of Michael Sugrue, who died recently, but hundreds of thousands of others have — 'The type of professor you'd ditch class to go and listen to,' says one YouTube commenter." Open Culture leads with, "If we ask which philosophy professor has made the greatest impact in this decade, there's a solid case to be made for the late Michael Sugrue." If impact is defined as reach, then maybe. Though it might be hard to surpass Peter Adamson's monumental History of Philosophy Without Any Gaps. But the main point here - which surely ought to dominate any discussion of online learning - is that the apparatus of colleges, courses, degrees and credentials is only a very small part of the picture, and that real contributions are being made outside the classroom walls, out in society, where such learning surely belongs.

This post comes from the larger publication, AI and Digital Inequalities (72 page PDF). Emma Ruttkamp-Bloem argues that such a policy should include "social values such as affirmation of the interconnectedness of all humans with each other, equity and human agency; human rights values such as privacy, transparency and accountability; and research values such as honesty and integrity." She also argues that "three of the biggest obstacles to attaining these goals include digital poverty concerns, the creation of monolithic societies and misinformation." This article is reflective of the publication as a whole (which is definitely worth a read): it is generally policy-based and founded in social justice themes. But the publication as a whole feels a bit lazy, in the sense that it essentially lists important global social justice issues and applies them to AI, with stipulations that AI should mitigate or in some way address these concerns.