What is Darkness in Dark Patterns?

Scale of Darkness: From Annoyance to Deception

Do all dark patterns trick the users equally? Are all patterns equally deceptive? The article here tries to identify the parameters that can be assessed to identify how efficient a dark pattern is and yeah, how do we define that darkness.

Harry Brignull defines Dark pattern as “a user interface that has been carefully crafted with an understanding of human psychology to trick users into doing things they did not intend to.”

I was exploring through my daily reads when I came across an article on Dark Patterns. I read and explored the subject immensely. The most I could see was Harry Brignull’s site darkpatterns.org which defined dark patterns and categorised them. Further Brignull worked on creating a ‘Hall of shame’ for the companies that use these deceptive techiques. It is basically the twitter feed and threads of users sharing their experiences or interactions with dark patterns. I explored through those tweets.

Somehow, during that I realized, going by the definition, not all of these could be categorized as dark or deceptive. While some are certainly deceptive, there are many which are nothing but annoying patterns. They nag the user but not exactly deceive them. Further, there are some marketing techniques which can be categorized as smart tactics but not exactly deceiving.So, the first idea was to understand what is dark, deceiving, annoying, evil patterns that are being called out.This led me to believe that there is a need to draw a fine line to understand whether it’s just an annoying pattern or is it a dark one.

Further research into the subject matter gave rise to the question, once we identify that the pattern is dark, are all patterns equally dark? If yes, all should be hated equally and if not, how will one identify how dark/ evil/ deceptive a pattern is. So from then onward I decided to first define darkness and the question that if is it possible to quantify this darkness?

Further, my notion of strength of dark patterns was confirmed by Zagal’s work on Dark Patterns in Game Design as ‘shades of grey’ where he suggests that the patterns can vary in how strongly they effect the users. Although Zagal’s study is based on dark game patterns, the similar status of dark patterns in the web can be noticed as well. There were challenges in defining what can be the darkness of the pattern since there has been no solid previous work done on the same. In order to do that, instead of presenting an upfront definition for darkness of a pattern, I decided to evolve the definition with further understanding on the matter Starting with an initial definition and refining it in an iterative manner. Based on the literal sense of the concept, the initial definition I’d suggest:

Proto-definition 1: Darkness of a dark pattern is the efficiency with which the pattern is able to trick users into an unintended task.

The question rises that how is one going to determine the efficiency of the pattern and if one establishes a null hypothesis that all identified patterns are equally dark, on what metrics is one is supposed to test it? It is understood that a patterns efficacy is dependent on number of factors such as the context of use, their implementation, the creator’s intentions etc. The need to determine the efficacy led to the understanding that we need quantifiable metrics to calculate the efficiency.

The qualitative info and user’s perspective received from a study conducyed suggests that a no. of factors influence how strongly a pattern works. The level of impact these patterns have on users depend a lot on the way their creator has implemented them in their product. The subtlety of the patterns vary website to website. Not all interactions that take on these strategies are necessarily equally “dark” in terms of design intent and motivation. They do have the potential to produce poor user outcomes, or force users to interact in ways that are out of alignment with their goals.

Admittedly there is subjectivity in darkness of a pattern, it has been tried to generalize what most of the users consider dark based on certain identified parameters. Following were the factors that I could identify which can help determine the darkness of a pattern:

  1. No. of users falling victim (Or victimization rate of the pattern)

This parameter refers to the no. of users that have fallen in trap of the pattern and ended up performing the (un) intended task. This parameter is directly proportional to the efficiency of the pattern which means, larger the no. of people falling victim, more efficient the pattern is at deceiving.

  • Effect on task completion

If a user visits a site to perform a task and encounters a pattern during the process, the effect the pattern has on the task completion time is a quantifiable metric determining the efficacy. If the pattern hinders the task completion to a significant level to most of the users, the pattern can be given a score for darkness.

  • Noticeability and Identification

So here, two factors work. First, how easily a user notices the presence of the pattern and then whether they identify the trick. There are certain patterns which try to hide in plain sight and certain are very widely presented. While some are very easily identifiable, some are extremely difficult to notice no matter how cautious one is. The ease with which the user is able to notice and identifies the pattern helps determine the efficiency of the pattern. The easier it is to notice the pattern, the lesser efficient it makes the pattern considering it makes the user alert of it’s presence. Although the noticeability varies between websites based on the type of UI and the choice of colours, font, font size etc. It can be generalized if we consider larger sample of websites for the study.

Proto Definition 2: Darkness of a dark pattern is the efficiency with which the pattern is able to camouflage itself and trick users into a business intended task which might lead to known or unknown damage to the users.

  • Is there a way to escape the pattern without leaving the site?

There are certain patterns which are overly persistent and do not let you proceed unless you accept to their terms. They lead you either falling a victim to them or leave the site you first visited for attempting your desired purpose. If there is a possibility of exiting the pattern without leaving the task, it makes pattern relatively less evil.

  • How easy is the process to escape the pattern?

The ease with which a user can exit the pattern is also a determinant of it’s efficiency. Easier the process to escape, lesser dark it becomes.

  • Severity of the damage by the pattern

This factor is one of the primary determinants of the efficiency. The severity of the damage the pattern creates is directly proportional to it’s efficacy. Again, the severity of damage is subjective and may be different from person to person. One person might not consider it a damage if it’s only creating temporal damage based on their perspective. The damage contexts here have been categorized as:

  1. Temporal

The amount of time user has to put in, in order to tackle the pattern or the extra time consumed during the task completion due to encounter with pattern is categorised as temporal damage.

  • Monetary

Some patterns try tricking users into paying more than required or paying for undesired services. A pattern leading to certain monetary loss, makes it more evil and more efficient.

  • Social Capital

Social capital refers to the self-image, social relations and identity of the user being affected due to pattern. While this factor may seem superficial at first glance, it is in fact the very social and psychological behaviors these patterns basically feed upon. There are certain patterns which spam messages and adverts to your social circles making it look like it has been sent by you. Then there are patterns which send your contacts information about you booking tickets to a certain movie or trip or a hotel stay etc. which might create a negative impact of the user on their contact because of continuously deceptive naggings. Some patterns feed on your self-image and intend to make you feel guilty if you try to get yourself out of them. So social capital that gets influenced by the pattern is also the determinant of the darkness of the pattern.

  • Extent/ Type of Benefit business get from the pattern

The type of benefit a business gets from the pattern is dependent on the intention with which the pattern has been employed. While the intentions are extremely subjective, it can be quantified using the ratings. While intention is believed to be the most deciding factor for a pattern’s whether a pattern is dark or not, it is admittedly a deciding factor for the darkness as well.

  • How offensive user finds this pattern? (More offensive, more possibility of user leaving the product)

How offensive the user find the pattern is a reverse damage factor. It is basically the user experience which refers to the severity of impact the pattern has on user experience. It is to be noted that while the above 3 factors have direct relationship to efficacy, this one has inverse. If the presence of a certain pattern is spoiling the user’s experience, it is more likely that the user will gradually stop visiting the site or using their services which is a loss for the business. So higher the damage to user experience, more evil but less effective the pattern becomes..The above identified features gives a modification to the definition as

The way an aware user deals with the pattern is different compared to a naive user. If the pattern is dark enough to drive the user away from the product (website), then clearly the business need to understand that the pattern is dark not just for the user but for business as well.

To come to a conclusion of which of the pattern has highest efficacy we need a lot of empirical study. So far, the results are available with respect to victimization rate of the pattern. Through the analysis of user awareness of the patterns, it was observed that certainly, there are some patterns which are more recurring and more no. of users are aware of, compared to the other patterns. Clearly, not all patterns have showed equal efficacy which furthers our study to the point where we measure the scores of efficacy of the patterns.

I’ll continue with more articles detailing these parameters out soon. Thanks for reading. Open to suggestions/comments/ critiques.

Read it on Medium

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