I spent a few hours working through the discussion in this document. The researchers have selected and analyzed 36 documents that take a 'principled' approach to ethics in artificial intelligence - that is, they identify or articulate some set of concerns or principles of actions to define ethical AI. While the document seems at first to document a convergence on themes, it becomes clear on closer reading that "there’s a wide and thorny gap between the articulation of these high-level concepts and their actual achievement in the real world." I woul also point out that because of the nature of the documents selected - corporate and institutional studies - there is a whole swath of opinion not represented. The document appears to be mostly a means to structure the debate, and it certainly does that (see the diagram here), but I don't think an analysis of sets of principles is the way to approach such a structuring.
This article (12 page PDF) identifies the challenges and pain points of running things like data analytics in things like Jupyter Notebooks. It's good to see this sort of article, because while some people (including myself) have touted this sort of approach as a way to generate dynamic and interactive learning resources, the actuality is that they are far from usable for the average person. In fact, after reading this article, we see that they are far from usable for the average data scientist. But the research quite clearly identifies where these problems are, and will serve as a valuable guide not only for notebook designers but for learning tool developers generally. For a short summary of the paper, see this blog post.
I agree with the sentiment expressed in this article, that people should encopurage "the development and enhancement of global competencies like self-efficacy, adaptability, attitudes towards immigrants, and openness to diversity." I think the five learning activities identified by the authors should have been much more precisely stated. For example, while volunteering is important, it needs to be, um, volunteer. Cultural diversity events should help learners see the world through another culture's perspective (and not through the lens of classwork or assigned reading). Discussions about world events are useful; shouting matches about world events are not. And conflict resolution is much more than simple collaboration; it is a skill in its own right and worth offering as a part of personal development programs.
I swear, I had flagged this for inclusion in the newsletter before reading all the way to the end of the post. What caught my eye was that it offered a look at the positive developments in the last decade of online learning, a welcome counterpoint to the doom and gloom we've heard from many pundits. What positive developments? Well we have cMOOCS and Connectivism, which if I may so humbly say, represented a big leap forward. We have web annotations (ok, they don't thrill me, but so what?). We have the renewed and welcome emphasis on equity and Inclusion in learning. We have data literacy (and I would add, increasing media literacy generally). We have open resources, domain of one's own, and microcredentials. That's a lot to add to the mix for one decade, and I, for one, am gratified to see the progress we as a discipline have made over the last decade.
As this report (36 page PDF) states, "individuals in the workforce will need access to a learning system that will support them at different life stages, be easily accessed throughout their career, and be much more flexible." That's quite true. And I agree that " I agree that we will need "new pedagogical models, such as shorter-term or modular programs, stackable credentials or badges, modified and adaptable curriculum, and greater use of self-directed and online learning." But to align it with workforce needs would be a mistake. First of all, employers are much too short-sighted (and often backward looking) in their selection of learning priorities. Second, they are generally less interested in providing what the report calls 'durable' skills in favour of product- and application-specific technical skills. And third, many (if not most) people have interests that extend beyond their employment needs, and may or may not translate into a future career.
According to this article, " QBot – the learning community bot – is available as an opensource app on GitHub." Now to be clear, only the "Lite" version of QBot has been put into open source. Fleming argues, though, that "the core experience of QBot remains just as familiar and intuitive in the opensource version." And it's not really a chatbot. "Anyone in the team can tag QBot in a channel and ask a question. This then prompts QBot to notify the right tutor(s) – so that no question goes unanswered." Over time, however, QBot is supposed to learn the content from answers given, so it can answer immediately on its own.
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