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The day before the UK general election, and there’s a lot of political communication flying about on social media. There are positive persuasions (“Vote Labour!”), negative persuasions (“Don’t vote Tory”), and a curious kind of message which interests me now: “Tories are evil”. Here’s an example:

The first curious thing about this quote is the logical content, which is either ridiculous or sinister. The Conservative Party got 13.6 million votes in the last election, more than any other party. Brooker’s claim is weirdly specific, and if we assume the number of “toffs, money-minded machine men and faded entertainers” is small, we are forced to conclude that Conservative voters are either “bigots” or “selfish, grasping, simpletons”. Either Brooker has made a mistake about what Conservative voters are like, or millions of ordinary people are bigots or simpletons. This view leads two places: First, to the conclusion that people who aren’t as insightful as Brooker shouldn’t be allowed to vote. Second, that there is no point trying to persuade most people honestly – bigots and simpletons can’t understand the evidence and arguments.

The second curious thing about this quote is the intent. The kind of contempt seems unlikely to work on anyone voting Conservative. Nobody would recognise themselves in Brooker’s list of villains, or – if they did – be motivated to weigh his values highly. It’s persuasive currency for the political opposition is zero. It might even be worse than nothing, since any Conservative voter is likely to be incensed, rather than dissuaded.

Messages like this, from simple slurs to more complex arguments that assume the irrationality or stupidity of people who vote differently, don’t exist to persuade. They are cheerleading for political partisanship, playing to the home crowd. Social media is rocket fuel to this kind of performative tribalism, which has it deep roots in our psychological capacity for groupness.

By ‘groupness’ I mean our tendency to identify social groups and use these to navigate our informational worlds. It means that we make decisions about who to believe and who to help based on which group we think they belong too first, using this group membership to filter all other information about them, including what they say or do.

This tendency is usually on on a high trigger, as demonstrated by a phenomenon called the ‘minimal group paradigm‘. I saw a nice demonstrate of the phenomenon recently from David Hauser on twitter:

In case you are teaching social psych soon, know that it is easy to replicate the minimal groups paradigm effect in class if you replace "which art do you prefer" with "is a hotdog a sandwich?" pic.twitter.com/95QCRx17rn

— Dave Hauser @davehauser.bsky.social (@DavidJHauser) December 5, 2019

Let’s just walk through this, since a seemingly trivial classroom demonstration of the minimal group paradigm has important implications for understanding political tribalism.

First, Dave asks the class “is a hotdog a sandwich?”. Question one can be any question, as long as the there are two different answers which are both chosen by some of the class, and as long as the those answers are of no relevance to question two. Some classic research used people’s art preferences. Dave asks if a hotdog is a sandwich. 69% of the class think Yes, 31% think No.

Next, Dave asks people to pick from two options

A: Give $3 to everyone who agrees with me and give $4 to everyone who disagrees with me.

B: Give $2 to everyone who agrees with me and give $1 to everyone who disagrees with me.

Most of the class, 71%, pick B.

Take that in for a moment. Most people are choosing less money for themselves ($2 rather than $3), and less money for many other people in the class – which is bizarre, or at least at odds with economic rationality in itself – and they are doing it because of social groups which didn’t exist until moments before, and have been conjoured out of the air by the instructor asking a stupid question about hotdogs.

Based on this arbitrary grouping, people would rather those who disagreed with them get less ($1 rather than $4) even to their own cost and the general cost of everyone who agrees with them! The are controls you could run to confirm that the effect is driven by the grouping induced by the first question, but the general conclusion must be that tribalism is a hell of a drug, and dangerously easy to invoke.

This helps us understand the attraction of “They Are Evil” messaging. These messages are not persuasive. Thinking like this is the opposite of persuasive – it is polarising, driving people further apart in their views and making communication across the divide harder. We do it because it feels good, awarding us and our tribe the moral equivalent of $2 when we could have had £3, but at the vindictive gain of awarding the opposing tribe $1 rather than $4. Collectively it diminishes us, and encourages a view that people who disagree are biased, selfish or otherwise beyond redemption and persuasion.

Please don’t give in to this kind of thinking. And please be careful of creating new tribes by asking unnecessary questions with binary answers.

I take lots of photos on my phone, a daily record of the mundane and notable. These photos sit in folders, mostly unlooked at. Here’s one way to grok what you’ve been taking pictures of: make a video which shows them at a rate of 3 per second.

Cribbing from this:
superuser.com: How to transform all the images from the current directory to a video in FFmpeg?
and this:
superuser.com: Resizing videos with ffmpeg/avconv to fit into static sized player (comment)

The thing that makes this slightly more complex is that the photos are different sizes (some are portrait, some are landscape) and I want them to maintain their aspect ratio in the video, which means padding the portrait photos with some black space for the output.

In a terminal define output height and width variables (so, for photos from my phone):


width=3264
height=2448

Then

ffmpeg -framerate 3 -pattern_type glob -i '*.jpg' -vf "scale=iw*min($width/iw\,$height/ih):ih*min($width/iw\,$height/ih), pad=$width:$height:($width-iw*min($width/iw\,$height/ih))/2:($height-ih*min($width/iw\,$height/ih))/2" video.mp4

Click here to get a breakdown of what this is doing via explainshell.com. People with longer attention spans may want to reduce the framerate (3 per second is nice if you have lots of photos of the same scene, but a bit quick for single photos).

Obviously I have assumed you are using linux and have ffmpeg installed

Dezfouli, Lingiwi and Balleine (2014) advocate hierarchical reinforcement learning (hierarchical RL) as a framework for understanding important features of animal action learning.

Hierarchical RL and model-free RL are both capable of coping with complex environment where outcomes may be delayed until a sequence of actions is completed. In these situations simple model-based (goal-directed) RL does not scale. The key difference between hierarchical and model free RL is that in model free RL actions are evaluated at each step, whereas in hierarchical RL they are evaluated at the end of an action sequence.

The authors note two features of the development of habits. The concatenation of actions, such that sequences can be units of selection, is predicted by hierarchical RL. The insensitivity of actions to the devaluation of their outcomes is predicted by model-free RL. Here they report experiments, and draw on prior modelling work, to show that hierarchical RL can lead to outcome devaluation insensitivity. This encompasses these two features of habit learning under a common mechanisms, and renders a purely model-free RL account of action learning redundant. Instead model-free RL will be subsumed within a hierarchical RL controller, which is involved in early learning of action components but will later devolve oversight (hence insensitivity to devaluation).

Hierarchical RL leads to two kinds of action errors, planning errors and action slips (for which they distinguish two types).

Planning errors result from ballistic control, meaning that intervening changes in outcome do not affect the action sequence.
Action slips are also due to ‘open-loop control’, ie due to a lack of outcome evaluation for component actions. The first kind is where ballistic control means an action is completed despite a reward being delivered midsequence (and so rendering completion of the action irrelevant, see refs 30 and 31 in the original). The second subcategory of action slip is ‘capture error’ or ‘strong habit intrusion’, which is where a well rehearsed completion of a sequence runs off from initial action(s) which were intended as part of a different sequence.

I don’t see a fundamental difference between the first type of action slip and the planning error, but that may be my failing.

They note that model free RL does not predict specific timing of errors (hierarchical RL predicts errors due to devaluation in the middle of sequences, and habitual intrusions at joins in sequences, see Botvinick & Bylsma, 2005), and doesn’t predict action slips (as Dezfouli et al define them)

EXPT 1

They use a two stage decision task to show insensitivity to intermediate outcomes in a sequence, in humans.

Quoting Botvinick & Weinstein (2014)’s description of the result, because their own is less clear:
“they observed that when subjects began a trial with the same action that they had used to begin the previous trial, in cases where that previous trial had ended with a reward, subjects were prone to follow up with the same second-step action as well, regardless of the outcome of the first action. And when this occurred, the second action was executed with a brief reaction time, compared to trials where a different second-step action was selected.”

The first action, because it was part of a successful sequence, was reinforced (more likely to be choosen, quicker), despite the occasions when the intermediate outcome – the one that resulted from that first action – was not successful.

EXPT 2

Rats tested in extinction recover goal-directed control over their actions (as indicated by outcome devaluation having the predicted effect). This is predicted by a normative analysis where habits should only exist when their time/effort saving benefits outweigh the costs.

The authors note that this is “consistent with a report showing that the pattern of neuronal activity, within dorso-lateral striatum that marks the beginning and end of the action sequences during training, is diminished when the reward is removed during extinction [37]”

Discussion

They review evience for a common locus (the striatum of the basal ganglia) and common mechanism (dopamine signals) for action valuation and sequence learning. Including:
“evidence suggests that the administration of a dopamine antagonist disrupts the
chunking of movements into well-integrated sequences in capuchin monkeys [44], which can be reversed by co-administration of a dopamine agonist [45]. In addition, motor chunking appears not to occur in Parkinsons patients [46] due to a loss of dopaminergic activity in the sensorimotor putamen, which can be restored in patients on L -DOPA [47].”

My memory of this literature is that evidence on chunking in Parkinsons is far from convincing or consistent, so I might take these two results with a pinch of salt.

Their conclusion: “This hierarchical view suggests that the development of action sequences and the insensitivity of actions to changes in outcome value are essentially two sides of the same coin, explaining why these two aspects of automatic behaviour involve a shared neural structure.”

REFERENCES

Botvinick, M. M., & Bylsma, L. M. (2005). Distraction and action slips in an everyday task: Evidence for a dynamic representation of task context. Psychonomic bulletin & review, 12(6), 1011-1017.

Botvinick, M., & Weinstein, A. (2014). Model-based hierarchical reinforcement learning and human action control. Philosophical Transactions of the Royal Society B: Biological Sciences, 369(1655), 20130480.

Dezfouli, A., Lingawi, N. W., & Balleine, B. W. (2014). Habits as action sequences: hierarchical action control and changes in outcome value. Philosophical Transactions of the Royal Society B: Biological Sciences, 369(1655), 20130482.

I am teaching a course, where I ask students to critically review papers reporting psychology experiments. It is making me question how you try and teach a skill as fundamental as critical thinking. I am trying to do it by example, walking the students through my reading of each paper, showing them what I do and consider when looking at it, and then providing them with a model answer (which is identical in structure to the final coursework I will require of them).

Reading a few practice questions students have handed in, I’m struck that there is a habit I want my students to acquire, which they haven’t quite got yet, and which I don’t even know the name of. Which I why I write this here, to ask you – Kind Interwebs – if you know what it is I am about to talk about and how I can convey it best to people taking my course.

This habit is that of asking the skeptical follow up questions to every proposal they make. So, for example, most undergraduate psychology students will have up their sleeve a well rehearsed list of possible flaws in experiments. Things like: was the sample representative of the population? Are there confounds in the experiment which prevent you cleanly inferring the causation?

It is nice, but inadequate, to write a review of a paper listing flaws like this. Doing so does not constitute a useful or interesting critical review (or, on my course, a gradeworthy one).

What I would like to encourage is my students to go the extra mile and, having spotted a potential flaw, assess it for plausibility, and consider what it would mean if the flaw was a significant one (i.e. how does it limit our interpretation of the current experiment, and what does it mean for future possible experiments?).

Here’s a concrete example: one paper I am teaching is one of my own, that looked at how students’ use of a course wiki predicted final exam score. A student suggested that because students knew their wiki use was being monitored, demand effects may have played a role (demand effects are a classic psychology experiment confound: participants distort their behaviour according to what they think you want to find). Now this is fair enough, but there are a number of follow up questions.

What is required for this to be the case? That students were able and willing to alter their final exam score based on their wiki use, but not because of it, perhaps. This seems implausible

What is implied if it is the case? If the demand effect did hold, would it even mean that the wiki use wasn’t effective? For example, we might decide that since students can’t easily score higher on exams at a whim, even an effect via demand was an effect worth having

How could I test if it is the case? Demand effects may hold, but how could we tell if they do hold?

What if it isn’t the case? What are the differences between the two situations Imagine two worlds with and without demand effects. What are the crucial differences between them, and what implications do these differences have for our experiment interpretation or further research? If there are no major differences, maybe we don’t need to worry about demand effects.

I pick demand effects because I wanted to use a specific example, but my aim is to encourage students to deploy these questions about every possible flaw or improvement that they suggest. My question today, though, is is there a general principle which students could follow to guide them in asking these kind of skeptical follow up questions? It seems like there isn’t anything too domain specific about this, so even if you aren’t an expert in psychology experiments you could semi-independently develop this skill of probing the logical structure of claims about an interpretation. It also seems that, cognitively, such thinking puts a heavy demand on your working memory, since it consists of layers and iterations of hypotheticals and counter-factuals. This makes it extra hard, is there any way to make it easier?

If there is no general principle, it may be that me (and my students) are stuck with going through worked examples. I’m seeking short cuts up the mountain.

Anyone can learn to have lucid dreams, and this ebook tells you how. Lucid dreams are those dreams where you become aware you are dreaming, and can even begin to control the reality of the dream. Adventure, problem-solving and consequence-free indulgence await! And for those interested in the mind, lucid dreams are a great place to explore the nature of their own consciousness. The ebook is written as a sort of travel guide, telling you what you need to take on your journey and what to expect when you start to lucid dream. It finishes off with a quick review of the scientific literature on lucid dreaming and links and references for further reading if you want to continue your exploration of lucid dreaming.

I wrote this with friend, and lucid dreamer, Cat Bardsley. My wife Harriet Cameron provided some beautiful illustrations which you can find throughout the book (and on the cover you can see here). The book is Creative Commons licensed so you can copy it and share it as you will, and even modify and improve (as long as you keep the CC licensing). It’s available on smashwords on a pay-what-you-want-basis (and that includes nothing, so it is yours for free if you’d like).

“Control your dreams” is my second self-published ebook. You can also get “Explore your blindspot” from smashwords (which is completely free, and also CC licensed). The wonderful folk at 40k books published my essay The Narrative Escape last year (and after doing all the formatting and admin associated with these two new ebooks I am more and more in awe of what they did).

Sweet Dreams!

(Cross-posted at mindhacks.com)

…I may venture to affirm of the rest of mankind, that they are nothing but a bundle or collection of different perceptions, which succeed each other with an inconceivable rapidity, and are in a perpetual flux and movement. Our eyes cannot turn in their sockets without varying our perceptions. Our thought is still more variable than our sight; and all our other senses and faculties contribute to this change: nor is there any single power of the soul, which remains unalterably the same, perhaps for one moment. The mind is a kind of theatre, where several perceptions successively make their appearance; pass, repass, glide away, and mingle in an infinite variety of postures and situations. There is properly no simplicity in it at one time, nor identity in different, whatever natural propension we may have to imagine that simplicity and identity. The comparison of the theatre must not mislead us. They are the successive perceptions only, that constitute the mind; nor have we the most distant notion of the place where these scenes are represented, or of the materials of which it is composed.

David Hume, in A Treatise of Human Nature, Book I, Part 4, Section 6, ‘Of Personal Identity’

Baby, I’ve been waiting,
I’ve been waiting
Night and day
I didn’t see the time,
I waited half my life away
There were lots of invitations
And I know you sent me some,
But I was waiting
For the miracle,
For the miracle to come

Waiting for the Miracle, Leonard Cohen

Sometimes I don’t know where this dirty road is taking me
Sometimes I can’t even see the reason why
I guess I keep on gamblin’, lots of booze and lots of ramblin’
It’s easier than just a-waitin’ ’round to die

Waitin round to die, Townes Van Zandt (and the Be Good Tanyas)

It might be the case that, while exploratory factor analysis isn’t a generally reliable tool for causal inference, for some reason it happens to work in psychological testing. To believe this, I would want to see many cases where it had at least contributed to important discoveries about mental structure which had some other grounds of support. These are scarce. The five-factor theory of personality, as I mentioned above, is probably the best candidate, and it fails confirmatory factory analysis tests. As Clark Glymour points out, lesion studies in neuropsychology have uncovered a huge array of correlations among cognitive abilities, many of them very specific, none of which factor analyses predicted, or even hinted at. Similarly, congenital defects of cognition, like Williams’s Syndrome, drive home the point that thought is a biological process with a genetic basis (if that needs driving). But Williams’s Syndrome is simply not the kind of thing anyone would have expected from factor analysis, and for that matter a place where the IQ score, while not worthless, is not much help in understanding what’s going on.

…

The psychologist Robert Abelson has a very nice book on Statistics as Principled Argument where he writes that “Criticism is the mother of methodology”. I was going to say that such episodes cast that in doubt, but it occurred to me that Abelson never says what kind of mother. To combine Abelson’s metaphor with Harlow’s famous experiments on love in monkeys, observational social science has been offered a choice between two methodological mothers, one of the warm and cuddly and familiar and utterly un-nourishing (the old world of linear regression, analysis of variance, factor analysis, etc.), the other cold, metallic, hurtful and actually able to help materially (statistical methods which are at least not definitely unable to do what people want). Not surprisingly, social scientists, being primates, overwhelmingly go for the warm fuzzies. This, to me, indicates a deep failure on the part of the statistical profession to which I am otherwise proud to belong. It is never a good sign when your discipline’s knowledge is the wire-mesh mother all the baby monkeys avoid if at all possible. Less metaphorically, the perpetuation of these fallacies decade after decade shows there is something deeply amiss with the statistical education of social scientists.

Cosma Shalizi, ‘g, a statistical myth’