Clickbait bandit problems

Skinnerian human behaviour control, limbic capitalism

The science of treating consumers of modern news media like what they, for practical purposes, are; to whit, near-passive objects of surveillance and control. Relying on peoples’ rationality and/or agency to get things done has a poor track record in recent history.

What I’m specifically interested in here is the use of, e.g. bandit models to model consumers and their interactions with the media, because it’s especially rich in metaphor. This is probably a superset of the gamification idea; in that area there are a particular subset of ways to addict people that we foreground.

The “bandit problems” phrase comes, by the way, from an extension of the “one armed bandit”, the poker machine, into a mathematical model for exploring the world by pulling on the arms of a poker machine.

Pseudopolitical diversion: There is a pleasing symmetry in that modern poker machines, and indeed the internet in general, model the customer as a metaphorical poker machine upon whose arm they pull to get a reward, and that this reward is addicting the customer to pulling on the arms of their literal poker machine. It’s a two-way battle of algorithms, but one side does not update its learning algorithms based on the latest research, or have nearly the data set.

Recommended reading before you blame someone for having no attention span. Michael Schulson, if the internet is addictive, why don’t we regulate it?

As a consultant to Silicon Valley startups, Eyal helps his clients mimic what he calls the ‘narcotic-like properties’ of sites such as Facebook and Pinterest. His goal, Eyal told Business Insider, is to get users ‘continuing through the same basic cycle. Forever and ever.’

[…] For a tech company in the attention economy, the longer you’re engaged by variable rewards, the more time you spend online, and the more money they make through ad revenue.

Yet we keep blaming people.

Stupid rats, running the mazes we set them, instead of dotcom startups.

Hooked: how pokies are designed to be addictive is a datavisualisation of poker machines, based on Addiction by Design by Natasha Dow Schüll and How electronic gambling machines work, by Charles Livingstone.

François Chollet argues

…social network companies can simultaneously measure everything about us, and control the information we consume. And that’s an accelerating trend. When you have access to both perception and action, you’re looking at an AI problem. You can start establishing an optimization loop for human behavior, in which you observe the current state of your targets and keep tuning what information you feed them, until you start observing the opinions and behaviors you wanted to see. A large subset of the field of AI — in particular “reinforcement learning” — is about developing algorithms to solve such optimization problems as efficiently as possible, to close the loop and achieve full control of the target at hand — in this case, us. By moving our lives to the digital realm, we become vulnerable to that which rules it — AI algorithms.

François Chollet, What worries me about AI

The TikTokWar examines an interesting escalation where we are removing the need for human personal leverage.

This is where it is important to understand the history of ByteDance, TikTok’s Chinese owner. ByteDance’s breakthrough product was a news app called TouTiao; whereas Facebook evolved from being primarily a social network to an algorithmic feed, TouTiao was about the feed and the algorithm from the beginning. The first time a user opened TouTiao, the news might be rather generic, but every scroll, every linger over a story, every click, was fed into a feedback loop that refined what it was the user saw.

Meanwhile all of that data fed back into TouTiao’s larger machine learning processes, which effectively ran billions of A/B tests a day on content of all types, cross-referenced against all of the user data it could collect. Soon the app was indispensable to its users, able to anticipate the news they cared about with nary a friend recommendation in sight. That was definitely more of a feature than a bug in China, where any information service was subject to not just overt government censorship, but also an expectation of self-censorship; all the better to control everything that end users saw, without the messiness of users explicitly recommending content themselves.

In other words, “soon you will look back fondly on when the social graph was how you got your fake news instead of direct from the remorseless grinding mill of state infowar”.

Rob Horning, I write the songs

Apologists for TikTok often tout how fun it is. Whenever I see something described as “fun,” I reach for my Baudrillard to trot out his passages about the “fun morality” — the compulsory nature of enjoyment in a consumer society. Fun, as I interpret the word, is not just a synonym for having a good time; it’s an “aesthetic category,” in Sianne Ngai’s sense of the term, that captures a structure of feeling peculiar to the way capitalism subjectivizes us. It indexes the degree to which our capacity to experience pleasure has been subsumed by consumerism. That is, “fun” marks how effectively we’ve been produced as an audience.

“Fun” often evokes the kinds of pleasures typified by the “experience economy,” in which retail is conflated with tourism, saturated with an “authenticity” that deconstructs itself. It also includes media “experiences” as well — on-screen entertainment, often presented serially in feeds. (Channel flipping and “doomscrolling” are fun’s inverted cousins.) It conceives of pleasure as a commodity, as an end that can be abstracted from its means. It presumes — or rather prescribes — a sense of time as a uniform emptiness, a blankness that must be filled with various prefabricated chunks of spent attention. “Fun” is when we defeat boredom; being bored by default is fun’s prerequisite.

Louise Perry, How OnlyFans became the porn industry’s great lockdown winner – and at what cost:

The historian David Courtwright has coined the term “limbic capitalism” to describe

a technologically advanced but socially regressive business system in which global industries, often with the help of complicit governments and criminal organisations, encourage excessive consumption and addiction. They do so by targeting the limbic system, the part of the brain responsible for feeling…

Limbic capitalism is the reason the most successful apps are brightly coloured like fresh fruit and glint like water. Our primitive brains helplessly seek out the stimuli we have evolved to be attracted to, and the beneficiaries of limbic capitalism have become wise to these instincts, learning over time how best to capture them.

Hmm. I wonder if that book is any good? I have not read it.

Social media and depression

Social media and television use — but not video games — predict depression and anxiety in teens

[…] playing video games was not a predictor of either depression or anxiety, which may be because gaming has become more of a social activity. “Compared with their forerunners 15 to 20 years ago, the average video gamer is not socially isolated. It has been shown that more than 70% of gamers play their games with a friend, either physically together or online,” the researchers noted in their study.

The researchers also found some evidence that interacting with media that promoted upward social comparisons was associated with reductions in self-esteem, which in turn was associated with increases in depressive symptoms.

Controlling people

See Dezfouli, Nock, and Dayan (2020), wherein the following diagram is explained:


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Becker, Mark W., Reem Alzahabi, and Christopher J. Hopwood. 2012. “Media Multitasking Is Associated with Symptoms of Depression and Social Anxiety.” Cyberpsychology, Behavior, and Social Networking 16 (2): 132–35.
Boers, Elroy, Mohammad H. Afzali, and Patricia Conrod. 2019. “Temporal Associations of Screen Time and Anxiety Symptoms Among Adolescents.” The Canadian Journal of Psychiatry, November, 0706743719885486.
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Dezfouli, Amir, Kristi Griffiths, Fabio Ramos, Peter Dayan, and Bernard W. Balleine. 2019. “Models That Learn How Humans Learn: The Case of Decision-Making and Its Disorders.” PLOS Computational Biology 15 (6): e1006903.
Dezfouli, Amir, Richard Nock, and Peter Dayan. 2020. “Adversarial Vulnerabilities of Human Decision-Making.” Proceedings of the National Academy of Sciences 117 (46): 29221–28.
Evans, David S. 2017. “The Economics of Attention Markets.” SSRN Scholarly Paper ID 3044858. Rochester, NY: Social Science Research Network.
Lin, Liu yi, Jaime E. Sidani, Ariel Shensa, Ana Radovic, Elizabeth Miller, Jason B. Colditz, Beth L. Hoffman, Leila M. Giles, and Brian A. Primack. 2016. “Association Between Social Media Use and Depression Among U.s. Young Adults.” Depression and Anxiety 33 (4): 323–31.
Primack, Brian A., Ariel Shensa, César G. Escobar-Viera, Erica L. Barrett, Jaime E. Sidani, Jason B. Colditz, and A. Everette James. 2017. “Use of Multiple Social Media Platforms and Symptoms of Depression and Anxiety: A Nationally-Representative Study Among U.S. Young Adults.” Computers in Human Behavior 69 (April): 1–9.
Sunstein, Cass R, and Richard H Thaler. 2003. “Libertarian Paternalism Is Not An Oxymoron.” SSRN Electronic Journal.

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