The initial categories that I assign to my new blog posts quickly become stale while new patterns emerge. Ten years ago, I therefore created a “Contents” page with headings that better reflect these patterns.
But the headings are too long (mostly 20 – 50 characters) for easy handling as WordPress tags or categories. On the other hand, without category pages, my hand-crafted post excerpts were almost invisible and unused.
Now finally I added the identifier numbers of my headings as WordPress categories, and put their long name into the category description.
So, now you can browse my blog archives via category pages and excerpts. You can even subscribe to individual categories via separate RSS feeds.
To facilitate even more overview, I wrote little summaries for the new categories. They condense much of my blogging, observations and insights of the last 18 years, so give them a try!
Furthermore, I identified ca. 40 % of the old posts as no longer recommendable, because their context has become obsolete or obscure. I did not assign them to the new categories, and greyed them out in the Contents page.
Note that there is also another method of summarising that has not changed: If a major topic emerges from the post patterns, I collect snippets from many posts into a coherent longer text, and indicate in the Contents Page listing whether such a text (currently  – ) summarizes a given post. Tags don’t play a big role in my content provision.
Hibai Unzueta asked the “people familiar with Iain McGilchrist’s thinking” for a “pragmatic summary” or a “clickbaity ’10 ways you can become more right-hemisphere dominant’“. There was none, and so I had to write one myself:
1. Be aware of what’s not ‘right-brained’ and question it. That’s easier than trying to describe and chase holistic wisdom and creativity.
2. Be wary of isolating and fixing. Of all things discrete, separable, bounded, focused, local, decontextualized, static and finished, of certainty and binarism, of mono-causalistic mechanisms.
3. Be wary of fragmenting and grouping. Of premature pigeon-holing, of hierarchical classifications and tree structuring, of seeing a whole as an agglomerate of parts.
4. Be wary of the linear and sequential. Of overly goal-directed narrow paths. Even of searching as opposed to browsing.
5. Understand representations and handles. Grasping with the right hand or with the mind works similarly, and we need wrapped concepts for referral and manipulation, but they are tools and not reality.
6. Don’t misunderstand generalizations and rich pictures. Rich pictures are not just the ‘big picture’ of zoomed-out, wrapped, closed parts. And generalizations apply to two or multiple concrete situations, unlike abstractions that apply to none.
7. Then, be open to associations. To relationships and connections, to the salient and outstanding, to context, patterns, and gestalt, to the individual and unique, and to recognition. Automatically.
I used McGilchrist’s lists of hemisphere difference from Chapter 2 of “The Master and his Emissary” and from the Introduction of “The matter with things” (p. 66 – 69), Jenny Mackness’ summary wiki, Sloww’s infographic, and my own old summary page.
Since the question was about thinking, I did not cover some remaining topics such as empathy, “the Other”, “being in the world”, or emotion. I also omitted the debate of whether the two modes of brain operation should be named by the two hemispheres.
On the other hand, I added some aspects that are, IMHO, pertinent and compatible with McGilchrist but not opined by him. In particular, these are the ideas of wrapping/ nesting (in items 3, 5, 6) and intentionality (4).
While I owe to him the notion of an “apophatic” process (negating, sculpting away), my approach to the ‘right hemisphere’ by subtracting what it is not, is my own, because I found it very difficult to follow his verbal account of non-expressible phenomena — even though his attempt was much more successful, IMHO, than Heidegger’s.
My critique of: Stephen P. Anderson; Karl Fast; Christina Wodtke. Figure It Out: Getting from Information to Understanding. Rosenfeld Media.
It is a wonderful book about understanding. There are rich, comprehensive, very plausible descriptions of how we understand by associations, with external representations, and through interactions. It does not merely reiterate the popular ideas about associations and visualisations but it clarifies why these are so important. A central statement is “Associations among concepts is thinking” (p. 43), and there is an entire chapter about “Why Our Sense of Vision Trumps All Others”.
Even more special is the notion of information as a resource that can be interacted with. And this interaction is not the usual sequential one such as in: “action and then the response” (p. 255), or read then think then write, or the question then answer dialog by teachers (or their digital simulation in H5P interactivity, which may help retention but perhaps nothing else). Rather, it is simultaneous and a “tight coupling”.
Interacting with information here also means interacting with external representations, and it has to do with the idea of the Extended Mind which I found very plausible already in Annie Murphy Paul’s book. Bring ideas out into the world, and see them anew — vision trumps, which is one part of the trick that draws on one of the two modes of brain operation. The other mode, and the other part of the trick, is ‘manipulating’:
“Computers became an everyday technology only with the widespread adoption of windows, icons, and mice for controlling the cursor. Being visual was important, but the big shift was being able to directly manipulate information through our hands.” (p. 254)
This is where the notorious Post-It Notes come in which play a major role in the book’s recommendations. But also, ‘rearranging’ and ‘connections’ play a major role.
“While all these interactions, from the beginning of this chapter through the end, play a role in understanding, there is a strong case to be made that rearranging is the essential one” (p. 283)
“In a sense, this book has been all about connections. While this is a book about how we understand, this fine thread of connections has run throughout this book: the connections between neurons that become perception. The connection between prior associations and external representations. The connection with our environment. Connecting with each other. Connecting with and through technology.” (p. 390).
And here is a problem, since connector lines between Post-It Notes don’t work with rearranging. (This became the rationale of my own tool).
Now one might think that digital versions of ‘whiteboards’ would overcome the problem, and I do think that they could. But it is not easy to mimic the affordances of the analog murals. For example, “Being large, it was easy for many people to gather around the board” (p. 303), “With the pens, the decision to have people use a Sharpie marker or something with a finer tip will affect not only how much can be written on a sticky note, but also how visible that note is from a distance.” (p. 317) — these quotes hint at the wicked problem:
How does a large mural full of post-its fit on a screen? When you zoom-in so much that you can read the small print, the famous overview gets lost.
This, IMHO, needs a shift from the one-page paradigm to a more intelligent way of combining overview and details.
(Further info: My free open source tool implements this basic idea but there is no team version. Note that it contradicts the obsolete but influential doctrine of the “Split Attention Effect”.)
Even a celebrity like Tony Bates, despite a lot of appreciation and sympathy, does not understand Downes’s connectivism, as their current debate shows. I wonder if it was easier to understand if the conceptual level was not eliminated which was formerly discussed as one of three levels of the central connectivist metaphor.
I see why it was eliminated as part of scientific and philosophical explanations. But what about using it for illustrations? I see that the notion of ‘concept’ is associated with the whole can of worms of cognitivist doctrines, computationalism, mental phenomena, folk psychology, and ultimately with ontological debates about mental representations. Now in Downes’s response to Bates, he acknowledges the usefulness of folk psychological terms as shorthand for talking about complex concepts. And I think the conceptual level would be just a handy means for illustrating the associations.
I like the term ‘shorthand‘ here because it connotes both the benefit and the pitfalls of thinking in ‘concepts’: We use a concept to wrap and grasp an idea and we use it as a handle to grab and manipulate items, but it also isolates and fixes the complex phenomena into a reduced representation which does not always do justice to them.
I think it is this fixing, isolating, reducing, distorting that makes the focus on concepts so questionable, and it contributes to the big problems of cognitivist doctrines. Maybe one could say that these theories focus too much on just one of the two modes of brain operation that McGilchrist described.
Finally, there is a comprehensive, more easily citable, work on Connectivism available (see also Tony Bates’s coverage). It explains the details of the theory as much as it reveals the major flaw of the competitor theories.
For me, it reveals how traditional theories just deal with “the process of doing the same sort of instructional activities teachers and researchers have always done”, and that they don’t even question what should be learned, but just avoid that question and go on as always.
Connectivism, by contrast, has a clear response to the core question:
“connectivism is based on the core skill of seeing connections “
N.B. it doesn’t say ‘learn connections’. If traditional content is challenged, the excuse is often that we don’t just learn single knowledge items but relationships between them. The paper acknowledges this by mentioning understanding: “you understand the parts of something, or you understand the rules, […] But […]”. But seeing the connections by oneself, is a totally different challenge.
This is also what I was trying to express in my paper on Distant Associations (5 pages PDF).
Yesterday I read a twitter thread talking about ‘divergent’ and ‘diversity’ as if these words belonged together, so I had to look up their etymology.
Ultimately, they do stem from the same Proto-Indo-European root (with descendants as diverse as wreath, worm, rhapsody, extroversion, warp, worth and many more). But already in Latin, their ancestors were very different: vertere ( = ‘to turn’) vs. vergere ( = ‘to bend, turn, tend toward, incline’).
In any case, the relationship is an occasion to think about one’s own understanding of ‘diversity’. If it only applies to groups or people that are, in some sense, ‘divergent’ from some ‘normal’ reference point or from some center, it might be a misunderstanding.
Maybe one overlooks differences that are less obvious, such as prefering synchronous over asynchronous style, oral over written style, guided over independent, mobile over desktop, neat outlines over scruffy maps, or any such, however vaguely demarcated, inclinations?
If one is not aware of their own style, how can they cater, then, to genuine diversity?
Now I finished “Science Denial” by Gale M. Sinatra and Barbara K. Hofer. Their answer to the wicked problem of “What to Do About It” focuses on educating people about how science works.
In particular, that scientists are fallible and “there is no single method that leads to some objective truth.” (p. 5), but rather, it is the collective effort that plays its role in vetting claims and reaching the scientific consensus.
This is, IMHO, a very different picture from the one that makes science so attractive for some, and misleads others: the certainty about true or false, right or wrong, which can be used as a replacement for religion (for those who feel that religion seems too old-fashioned but who still crave for being a sheep following a shepherd), and which can be used as a banner to follow like a sports fan club (who is certain that their team will win and hence they are on the right side of history).
While this complacent arrogant image might have put off the deniers, they also fell prey to the underlying binary thinking, just with the added thrill of being on the opposite side of, and feeling even smarter than, the mainstream. While every dumb database ‘knows’ that there are three possible values — true, false, and ‘NULL’ ( = don’t know, yet) — they equal unproved with disproved (much like simple-minded ‘myth-busters’ do, BTW).
Sinatra and Hofer give plenty of useful advice to science communicators, for example “‘Both sides’ is for opinions, not science” (p. 176). IMHO, these tips are more promising than expecting that individuals are “adopting a scientific attitude” (p. 8), evaluating complex information, or “Monitor your own cognitive biases.” (p. 165) and “Know the role of your emotions.” (p. 167).
But what I think is very necessary, is that many experts themselves do not reinforce the impression of certainty and complacency. In particular, it is dangerous if they do so in a neighbor discipline which the layman cannot really distinguish. I, for example, could not sufficiently keep apart the scopes of Virology, Immunology, and Epidemiology, when the pandemic started.
After my 19 blog posts for the cMOOC called “Ethics, Analytics, and the Duty of Care“, I need a summary — although this is almost impossible for such a massive course of approximately 790 slides/ 43 hours video/ 500+ pages spoken text (net weight, i.e. without the 23 technical and ~ 20 discussion videos).
The most important positive insight for me was that AI in education should and could mitigate vulnerabilities and oppression (457), in particular by applications similar to formative (not summative) assessments, and by relieving time pressure.
There was a lot in the course that I could easily agree with, in particular the idea that ethics is not something that can be generalized, deduced from rules, or programmed. I understand better now how the term ‘ethics’ is being used in this way that was alien to me (456), and why the consequentialist view is loaded with so much historical ballast (453).
The large module on Care Ethics was especially interesting. On one hand, due to the parallels with connectivism (455 and 461). On the other hand, it inspired more thorough thinking about vulnerability and dependence (457), and the delicate relationship between the one-caring and the cared-for (458).
It is here where my skepticism of AI starts, and it was good to engage with the topic and go beyond the mere unease.
One objection is that the relationship with a robot cannot be the same as with a human, even if it is a good fake, just because we interact differently when we know it’s a faked human (455, 460). (The tempting solution would of course be to betray the dependents about the robot’s true identity (450), and I think we must be very clear that this would violate any ethics that objects dishonesty as an abuse of the privileged position of being a better cheater.)
Another objection is about growing independent, as it is expected for higher ed students. This does not only require trust (above objection), but also learning to transfer one’s knowledge to different domains and to come up with associations beyond the narrow subject matter at hand. But realistically, AIs will be limited to one specialized domain each (445 , 458). Furthermore, students who avoid independent work might indulge in the comfort of the machine. Of course that’s just my speculation.
Finally, there was plenty of opportunity to think about the political dimension. The tree vs. mesh structure of society (444), the power on the labor market (447 ), the power distribution between end users and those who pay the development (462), and whether it will be the poorer students who will be fobbed off with faked teachers (460). All of this suggests that we should be very wary.
The course interactivity was a bit disappointing for me because there was almost no blogging and commenting which I would have preferred over the oral synchronous sessions.
After 13 videos and more than 10 hours of watching I realized that I may have misunderstood who does the training of an AI model.
I thought that training an AI by supervising and reinforcing its learning and creating a model is one thing, and that using it by interacting with it is another, later, thing. Now I learned that there no such simple division of labor between developers and users, and that the end user’s specifications count as training, as well: for example giving Feedly’s Leo examples of posts that I liked to read.
But now I am left wondering how far my influencing the model may extend. There must be some limit somewhere? If I am being cared for by a care robot and tell him that plenty of sweets are best for me, will he believe this and bring me ever more sweets?
And I suppose that here is the border between a personalized service and a fully personal one, and here is also the response to my doubts in week 2, and similarly, the response to my suspicion of a One Way relationship that I raised here at the beginning of module 7.
What I particularly liked in the last video is that, again, a very extreme alternative thought was carried through, a scenario of a very mutual relationship between human and AI:
“if we treat the AI as, you know, a person that feeds back into the training of the AI, the AI eventually begins to regard itself as a person and treat itself as a person in its own decision making. So, I don’t think this is such a hard philosophical conundrum as it might seem” (1:18:59)
“interaction with artificial intelligence and analytical engines is ongoing and dynamic and doesn’t end and our major role in these interactions is to train them. If we train them, well, they will become reliable responsible, ethical partners.” (1:20:59)
Here, the ‘we’ seems to include both the developers and the end users, but I am not sure about their distribution of influence and power. Unless we get some sort of ‘Indie AI’, the capital paying for the costly production, will probably have more say.
Now that the negative thoughts from the previous post are out of my way, I can turn to this week’s topic.
In the Monday’s introduction, there was a lot of talking about “society as a whole”. In particular, the ethics of the whole society. As 10 years before with the knowledge of a whole society, I had my difficulties to get my head around that. So I’ll first revisit how it became easier for me to understand it then after Stephen’s comment.
I considered approaching the ‘knowledge’ of a profession or discipline xxx as a newcomer, namely learning how ‘they’ think and speak and how it may ‘feel like’ to be one of them. First I might encounter ‘them’ as some individual new colleague, a ‘you’ in the singular. Then gradually, the commonalities and patterns of their ‘being an xxx professional’, become ever more familiar, and the borders between them begin to blur, and I see them as a ‘you’ in the plural. At the end of this process, the xxxs’ collection ‘as a whole’ contains, strictly speaking, all of them except myself. Then it is only a small step to get from the ‘they’ or ‘you’ to the ‘we’. We all.
Now ethics is similarly learned. From individuals in one’s close proximity. Via ‘ripple’ effects or, as I expressed it in my first vague post, via contagion. Later I learned that this is compatible with connectivism, see ebb and flow. And it has a lot to do with decentralisation, as opposed to central authorities and templates.
Both with knowledge and with ethics, it seems like the ideas ‘spread’ across the interface, or more precisely, grow at the interface, between human and human. That’s why it is so dangerous to poison the trust at this interface with fakes.