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the virus will be far more present in far more places when school starts in August than it was when most schools shut down in March

I am among the crowd who both believes that online learning can be done quite well, and that there is something irreplaceable about the experiences of face-to-face learning, when that learning is happening under reasonable conditions that is. These are not reasonable conditions. Do not get me wrong. This is a loss. The experience of community is not the same at a distance or over the internet. It is not necessarily entirely absent, but it is not as present.

In an online environment, seminars will work best if they occur asynchronously in the discussion boards in an LMS

The 4 key elements for a seminar that need to be replicated during remote instruction include: A prompt or text(s) that the student considers independently in advance Guiding questions that require analysis, synthesize and/or evaluation of ideas The opportunity to share personal thinking with a group Ideas being developed, rejected, and refined over time based on everyone’s contributions

Students need specific guidance and support for how to develop, reject, and refine ideas appropriately in your course.  If you want students to share well, consider requiring an initial post where you and students introduce yourselves and share a picture. Describe your expectations for norms in how everyone will behave online Provide a lot of initial feedback about the quality of posting.  Consider giving samples of good and bad posts, and remember to clarify your marking criteria. Focus your expectations on the quality of comments, and set maximums for the amount you expect to reduce your marking load and keep the discussions high quality. Someone will need to moderate the discussion. That includes posting the initial threads, reading what everyone posts all weeks and commenting to keep the discussion flowing.  Likely, the same person (you or a TA) will also be grading and providing private feedback to each student. Consider making the moderation of a discussion an assignment in your course. You can moderate the first few weeks to demonstrate what you want, and groups of students can moderate other weeks. It can increase engagement if done well, and definitely decreases your work load.

How and why do well-educated, well-intentioned scientists produce biased AI systems? Sociological theories of privilege provide one useful lens.

Scientists also face a nasty subconscious dilemma when incorporating diversity into machine learning models: Diverse, inclusive models perform worse than narrow models.

fairness can still be the victim of competitive pressures in academia and industry. The flawed Bard and Bing chatbots from Google and Microsoft are recent evidence of this grim reality. The commercial necessity of building market share led to the premature release of these systems.

Think of ChatGPT as a blurry JPEG of all the text on the Web. It retains much of the information on the Web, in the same way that a JPEG retains much of the information of a higher-resolution image, but, if you’re looking for an exact sequence of bits, you won’t find it; all you will ever get is an approximation. But, because the approximation is presented in the form of grammatical text, which ChatGPT excels at creating, it’s usually acceptable. You’re still looking at a blurry JPEG, but the blurriness occurs in a way that doesn’t make the picture as a whole look less sharp.

a way to understand the “hallucinations,” or nonsensical answers to factual questions, to which large-language models such as ChatGPT are all too prone. These hallucinations are compression artifacts, but—like the incorrect labels generated by the Xerox photocopier—they are plausible enough that identifying them requires comparing them against the originals, which in this case means either the Web or our own knowledge of the world. When we think about them this way, such hallucinations are anything but surprising; if a compression algorithm is designed to reconstruct text after ninety-nine per cent of the original has been discarded, we should expect that significant portions of what it generates will be entirely fabricated.

ChatGPT is so good at this form of interpolation that people find it entertaining: they’ve discovered a “blur” tool for paragraphs instead of photos, and are having a blast playing with it.