I'll stop harping on this soon. But again, I want to stress, using linguistic (or other) cues in the article itself is a poor way to identify fake news. That's what both the humans and the AI systems do as described in this article, and yet we find they're both wrong a quarter of the time. The way to distinguish between fake and non-fake is not to study the news item more closely, it's to find additional sources, to verify, to confirm. The only thing fake-news-detecting algorithms will produce is more convincing fake news.
I've done this. Not on purpose, but I've had conferences get away from me, and I spend the entire time talking to people, doing interviews, working the trade show floor, and doing my own talks. But it's unusual and I really do try to see at least a representative sample of talks. But the point of the article - that there's a lot more to a conference than the presentation - is true.
The key message in this post is that researchers should look beyond the typical data collected in educational studies. In particular, they should "take a broad view of impact" and "take the long view". In particular, "Research on the effects of an education initiative typically looks only at later educational outcomes, but these investigators examined the impact of preschool on the totality of these children’s lives." Also, "Most education research adopts a short time horizon, rarely looking at the impact of a program beyond two or three years." For example - the early lessons I had in writing and public speaking had a lifelong impact on my character and career, but this impact would be invisible to pretty much every educational research study out there.
This ground-breaking paper makes it pretty clear that knowledge consists of patterns of connectivity in the brain. These patterns now have a name: the synaptome. As Shelly Fan explains, " Like a map into internal thoughts, synaptomes drew a vivid picture of what the mouse was thinking when it made its choice... Like computer code, a synaptome seems to underlie a computational output—a decision or thought." There's a lot more in this paper - read it end-to-end. Keep reading, even if you don't understand bits. The paper is loaded with insights - the connection to small worlds networks, hubs in the hippocampus, modifying the synaptome, distributed representation, and more.
This newsletter is sent only at the request of subscribers. If you would like to unsubscribe, Click here.
Know a friend who might enjoy this newsletter? Feel free to forward OLDaily to your colleagues. If you received this issue from a friend and would like a free subscription of your own, you can join our mailing list. Click here to subscribe.
Copyright 2018 Stephen Downes Contact: email@example.comThis work is licensed under a Creative Commons License.