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