There's all kinds of goodness in this post, and in the This is DaveJ website generally. This post shows how you can use Google Sheets to extract data from web pages and organize it in a spreadsheet. The secret is the =IMPORTHTML and =IMPORTXML function in Sheets. It makes me think of what it will be like when all applications have something like that. There are also ways to import JSON into Sheets. This is just the tip of the iceberg. Dave Johnson has written a ton of really useful leading-edge tutorials. If you like messing around with this stuff, don't miss this site.
This is another update from Tony Bates to his online textbook. This one looks at the role and potential application of artificial intelligence in learning. "There are two somewhat different goals for the general use of artificial intelligence," he writes. "The first is to increase the efficiency of a system or organization, primarily by reducing the high costs of labour... that of teachers and instructors. The second is to increase the effectiveness of teaching and learning, in economic terms to increase outputs: better learning outcomes and greater benefits for the same or more cost. With this goal, AI would be used alongside or supporting teachers and instructors." I don't think I'd frame AI as for-or-against teachers, or as cost-versus-outputs. That presents AI (incorrectly, in my view) as contributing to a zero-sum outcome.
This is an update on John Bersin's longish post addressing the idea that learning can and should happen in the flow of work. There's a sales pitch (of course; he's a consultant) but some useful observations as well: "workforce productivity platforms like Microsoft Teams, Slack, Salesforce, and Workplace by Facebook are turning into learning platforms." Of course they are. People on the job trying to get stuff done want to be able to learn right in the environment they're using to work and collaborate. You'll find - if you look for it - that tools like IDEs, word processing solftware, sales and CRM platforms, etc., are also becoming learning platforms. The really interesting learning technology question is: how are they doing this?
Just by coincidence Alan Levine dug up a question I've been thinking about this week, leading me to pose a question, which in turn led Grant Potter to point me toward BRCK, a company and hardware platform offering distributed web access to people who can't afford it. The way they address the issue is as interesting as the hardware itself: "a tool that was actually a highly ruggedized micro-data center. With this, we could host content on each device, as well as get people connected to the internet. Another way to think about the accessibility side of what we do is that we have a new model for how a distributed CDN works on a nation-scale, moving away from the centralized model that the rest of the world uses." This is a really interesting and important model not just for Africa but for all of us.
So here's a question: is this experience real? It's "a leg prosthesis with the residual nerves in the user’s thigh allows above-the-knee amputees to feel their prosthetic foot and knee in real time." So wearers 'feel' their artificial leg touching the ground. This is only the beginning of what will most certainly be called 'Artificial Senses' (AS) (more here, here, here). They need not be limited to analogues of the five senses, and they need not be limited to types of bodily experience (imagine feeling 'up' or 'down' depending on how the stock market is performing, for example). While some may wonder how these can be used in education, the real question looking forward will be how we can help people learn to use and benefit from artificial senses.
I can't link to Hutto and Myin directly, because it's a stupid book with access only via a paywall. But this criticism does a good job of presenting their view. The view, in a nutshell, is "cognition does not essentially involve content and admits explanations on a semantic level only as far as it is scaffolded with social and linguistic practices" because "serious philosophical problems with applying a semantic-level vocabulary of representations, models, and computations: it is troublesome to give a non-circular account of how content emerges in the natural world." Quite so. The discussion in this paper is pretty dense and detailed, but as I said, offers a good exploration of the issues, especially with respect to the relation between content, representations and neural networks.
Starting with the premise that people might vote blue if they think all their friends are voting blue, this article posits that friend networks can be gerrymandered in order to produce that effect even when the majority of people in the network would vote orange, potentially changing the outcome of the vote. While the most obvious applications are in an election, probably the more long term effect (and harm) is caused in the area of social beliefs, product preference, and cultural norms.
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