BJ Fogg established a discipline. A business model was developed in Silicon Valley. The majority of the internet currently resides in the space between those two things.
Nearly every great idea has a period in its early history when it is still small enough to be cautious. B.J. Fogg was a Stanford researcher in the mid-1990s who worked in a lab that most of his coworkers thought was a little strange. He was investigating whether computers could alter people’s thoughts and behaviors through design rather than coercion or overt persuasion. Through a button’s position on a screen, a sound’s arrival at a specific time, or the real-time updating of a number. For a while, the study of this phenomenon was an academic curiosity that he dubbed “captology,” an acronym derived from Computers As Persuasive Technologies. It was a curriculum after that. Afterwards, it served as the model for the attention economy.
Persuasive Technology, written by Fogg in 2003, has received over 4,000 citations. The number is practically irrelevant. The locations of those citations—in design patents, app development frameworks, and internal documents of businesses that went on to create products that are used by billions of people every day—are more important. The Fogg Behavior Model, which contends that motivation, aptitude, and a trigger that appears at the appropriate time are necessary for behavior change, is now so ingrained in product design that the majority of UX designers apply its reasoning without being aware of its name. That is either a warning about what happens when a framework leaves its ethical context or an indication of significant intellectual achievement. Most likely both.
The purpose of Captology was never to maximize engagement metrics. One of Fogg’s early examples was a computerized doll named Baby Think It Over, which was intended to mimic infant care and deter adolescent pregnancy. The same persuasive mechanism—an unpredictable trigger requiring instant attention—would later drive social app notifications that resembled slot machines. It was used as a public health intervention in one instance. In another, it was a feature intended to increase the stickiness of a platform. The science was identical. The intention was entirely different. The moral history of captology resides in that gap.
Working out of the University of Oulu in Finland, Harri Oinas-Kukkonen spent years attempting to construct the ethical safeguards that Fogg’s foundational work had left somewhat open. His Persuasive Systems Design model made a careful distinction between systems that assist users in accomplishing their own objectives and those that subtly incorporate a designer’s objectives—often commercial ones—into the user experience. A key component of the moral architecture of the field is the distinction between endogenous intent, in which an individual uses technology to transform themselves, and exogenous intent, in which a platform is intended to transform an individual for its own advantage. In reality, most users who navigate the interfaces designed around it hardly notice it at all. Reading this literature gives the impression that the researchers saw what was going to happen, meticulously documented it, and then watched it happen nonetheless.
In his more recent work on digital therapeutics and human-computer interaction, Simon D’Alfonso has attempted to expand the use of captology into the field of mental health, where the potential for harm is high and the ethical stakes are particularly obvious. The question of where persuasion ends and exploitation begins is not abstract when an algorithm targets emotional states to keep a user engaged and that user is experiencing anxiety or depression. It’s clinical. D’Alfonso’s work makes the case for explicit ethical safeguards incorporated into therapeutic digital systems, which may seem apparent until you take into account how infrequently the industry as a whole has applied comparable standards to products that reach much larger populations.
The body of work produced by the academic discipline of captology is truly impressive; it is rigorous, multidisciplinary, and frequently prophetic. As early as the 1990s, the Persuasion Handbook chapter co-authored by Fogg observed that the study of computers as persuasive technologies was “only beginning to gain momentum,” accurately predicting that interest would grow significantly. The speed at which the commercial applications would surpass the ethical frameworks being developed in tandem with them was something it was unable to fully predict. The same empirical rigor that early captologists applied to their more optimistic research is now applied to the study of dark patterns, which are deceptive interface designs that fool users into making decisions they did not intend. In a way, the field is examining the effects of its own initial success.
Whether captology’s academic moral framework will ever fully catch up to the scope of its commercial deployment is still up in the air. The researchers continue to write. The papers continue to accumulate citations. Additionally, someone is probably applying the Fogg Behavior Model to a notification system, checkout process, or content feed in a product meeting at a company with hundreds of millions of users—probably without reading the intent footnotes.
