Work is learning. Learning is the work. Without AI.
On the last Friday of each month I curate some of the observations and insights that were shared on social media. I call these Friday’s Finds.
“Listen, generative LLMs and art imaging tools will get better and better over time. If your opposition is based on crappy outputs, that problem will get solved.
Problems such as unsustainable resource consumption, unfair labour practices, accelerating wealth inequity and the absolute death of joyful creativity, however, will not be fixed.” —@barsoomcore
In an article on the impact of AI on computer science education, the general conclusion is that all jobs will have a generative AI component and it will be necessary in most jobs to understand computer science. The piece opens with an experiment conducted by a professor with one of his computer science classes.
One group was allowed to use ChatGPT to solve the problem, the second group was told to use Meta’s Code Llama large language model (LLM), and the third group could only use Google. The group that used ChatGPT, predictably, solved the problem quickest, while it took the second group longer to solve it. It took the group using Google even longer, because they had to break the task down into components.
Then, the students were tested on how they solved the problem from memory, and the tables turned. The ChatGPT group “remembered nothing, and they all failed,” recalled Klopfer, a professor and director of the MIT Scheller Teacher Education Program and The Education Arcade.
Meanwhile, half of the Code Llama group passed the test. The group that used Google? Every student passed.
The current hype around ‘artificial intelligence’ in the form of generative pre-trained transformers and large language models is impossible to avoid. However, I have yet to try any of these out other than two questions posed to Sanctum.ai — auto-marketing — on my computer and not on some cloud. So far, these are my reasons for not jumping on this bandwagon.
On the last Friday of each month I curate some of the observations and insights that were shared on social media. I call these Friday’s Finds.
I was in Long Beach in 2012 when Nick Hanauer gave his, “It’s absolute bullshit that the rich are job creators” TED talk. I was so eager to share it with co-workers and friends, I checked the TED site every day waiting for them to post it. I gave up after six months
It eventually showed up on YouTube but I don’t think TED ever put it on their site or even linked to it. I’m surprised they welcomed him back to the main stage just a couple years later. —@kims
Are we headed toward a society of feudal techno-peasants and a small class of the analog-privileged?
The Future is Analog (If You Can Afford It)
The idea of “analog privilege” describes how people at the apex of the social order secure manual overrides from ill-fitting, mass-produced AI products and services. Instead of dealing with one-size-fits-all AI systems, they mobilize their economic or social capital to get special personalized treatment. In the register of tailor-made clothes and ordering off menu, analog privilege spares elites from the reductive, deterministic and simplistic downsides of AI systems. —Maroussia Lévesque
Once again Jane Hart is asking, “What are the most popular digital tools for learning and why?” in the 18th Annual Top Tools for Learning survey. Voting ends on 30 August.
My tools have not changed much since last year. I am not using social bookmarks much any more, so Diigo did not make the list. It’s interesting that social bookmarking was my #3 tool in 2012, and how little I use it now.
Donald Clark has posted about how many people are using AI as assistive technology.
Time and time again, someone with dyslexia, or with a son or daughter with dyslexia, came up to me to discuss how AI had helped them. They describe the troubles they had in an educational system that is obsessed with text. Honestly, I can’t tell you how often I’ve had these conversations. —Plan B: 2024-08-15
Donald goes on to cite several types of assistive technology.
Stay in your lane. Stick to your knitting. These are perhaps the worst cliché words of advice anyone can give in our interconnected, networked world.
For much of history, particularly since The Enlightenment, our societies have been quite adept at creating classifications and creating fields of work and study.
At the end of the day, fields represent a specific kind of research machinery: a collection of rallying cries, norms, funders, and bureaucratic arrangements that are designed to output new insights about the world at large. Fields rise and fall on the strength of their ability to deliver knowledge and useful ideas. Researchers – particularly the good ones – coalesce around productive fields because they are also the most effective engines for pursuing the questions they want to pursue. At the end of the day, that is what matters. —Field Essentialism
Fields are often created to be useful but they can also be used for power and control. I remember visiting the Apartheid Museum in South Africa and one of the rooms showed all the laws around race that had been in place during the apartheid regime. These started as a few laws but more kept being added as there was no way to make a complex field merely complicated.
“It might be down to the time of year; it’s always quieter in the summer months but it feels a bit different right now.
Firstly, it feels like there has been a BIG pause because of ChatGPT and other LLMs. It feels like people are still getting their heads round what they can do, their effectiveness, quality, etc. And when they do look at it, they don’t ‘get’ how they’ll use it.” —Andrew Jacobs 2024-08-09
I have witnessed this same malaise in the business world for the past year. If it’s not an AI initiative, it does not get any attention. The bad and the ugly aspects of this new flavour of machine learning are dominating the IT sector and all it touches. Here are some recent examples shared in our community of practice.
On the last Friday of each month I curate some of the observations and insights that were shared on social media. I call these Friday’s Finds.
Note: Regular readers may have noticed that my blog posts are rather infrequent at this time. I am taking a break from blogging through the Summer and intend to be back this Autumn. There are over 3,500 older posts always available to peruse here.
“Everyone is tired because individually we’re trying to do all the things that can only really be achieved by communal living.” via @gemelliz
“The modern conservative is engaged in one of man’s oldest exercises in moral philosophy; that is, the search for a superior moral justification for selfishness.” —John Kenneth Galbraith (2002)