Memetics and Applications: A Brainstorm Exercise
Memetics as It Stands
Presently, memetics is arguably merely a proposed science, not actively a research field. Although, inarguably, memetics now has a large (and disconnected) body of empirical work. Memes provide a datafied discussion across areas of communication, linguistics, cognition, education, data science, and so on. This also includes their inspiration to existing sciences, humanities, and philosophies. Yet for some reason, the two main theories of memetics, the neo-Darwinian paradigm developed in line with Dawkins and the communication and media theory of Internet Memetics, have yet to convince many outside of their research area that memetics provides an adequately predictive or descriptive science of culture. Rather, often the theoretical results remain fodder and development in digital humanities.
However, there are some ways in which this could move towards being something of a science with a little ingenuity. In particular, memetics research would need to take a leap into discourse which is a little more intellectually risky than describing one-off media events as being descriptive of some construction of digital platforms or wonders and nightmares of humanity.
While I may need to ask forgiveness from my fellow experts, memetics needs to develop more pragmatic applications. Many would perhaps argue that investigating alt-right rhetoric developed under the study of Pepe memes is a worthy ethical development, and it is, it does not pragmatic. Any survey of the policy suggestions of this literature or related interest suggests a lack of agreed upon solutions. Instead they offer critiques and developments of rhetoric around these concerns. That is, we have created more academic jargon that might one day go viral by being mentioned on CNN, but having learned of these terms has yet to develop real actions to stop the theft of otherwise harmless iconography by right wing nationalism. It is rhetorically descriptive, but it offers no acceptable solutions or mechanisms of response except reactionary and ambiguous policing of rhetoric and the ambivalent technologies of internet protocols.
So okay, Alex, what can we do since memetics is supposedly so impractical?
Towards a Pragmatic Memetics
Well, if I am allowed a response, I will give it a shot. Namely I will point in two directions which might seem counter-intuitive at first. The first is a restructuring of theory to answer different questions. This is the program that I have been developing within information science. The other direction is to point towards existing empirical areas which offer material justification to strengthen the pragmatic development of theory. These material applications are not yet possible as almost all of them mean stepping into material research areas that so far have been delegated to non-culture oriented theory spaces, but never the less are cultural.
Notice, these two spaces are not distinct, but rather they speak to each other with more pragmatic honesty. Doing this, I believe, offers memetics its best shot of gaining a genuine status of descriptive or predictive science. So what are some examples of these. I will start with some spaces which speculatively could gain from a memetic perspective.
A Theory in Search of Application
Maybe, let us start with some more obvious points. Internet memetics, mostly, is the study of connected images. How they are connected are not precisely clear. Shifman suggests rather loosely that they are a collection of images across the internet which share content, form, and stance. While elsewhere I have suggested nuance and redevelopment of what these terms mean, they are not without their value. I might say in the spirit of these terms, images have meaning qualities that are dependent upon how people use them. Upon having decided a group of images belong together as a meme, we are then tempted to define what their meaning is, for example by giving the meme a name, or investigating how it is used in communication.
However, a critical issue with this approach is that these are all from the perspective of researchers. To say otherwise, the researcher must suggest that their data, a collection of images, represents an obvious clustering describing a cultural idea. That is, it presumes some nature of how similar ideas organize together. I have suggested elsewhere that this is assuming the conclusion, and I think this is fairly obvious in how memetics has come to describe arbitrary cultural criticisms that do not tend to agree with each other.
That is, agreement in application often means application to an ideology rather than a materially agreeable solution. So what would make something a materially agreeable solution? Well, convincing someone to act in some capacity other than as a rhetorically ideological way, I suppose. It requires scientific impact outside of citation to put it bluntly. It needs to show application to technological development or provide solutions to policy concerns that move in the directions we expect.
So, let us return to our common form of data: collections of digital images. Given these images, as I have argued, so far most have only made rhetorically descriptive arguments about normative claims. What if instead memetics focused on something like the impact of specific icons in their dispersion across the internet. If this could be done with some level of precision, then we could practically speak about the level of impact of an icon in social networks.
So far, however, this proves difficult. There is a reason for this. Consider the technologies required in a simple way. An easy way to find a collection of images with a particular icon might be to search for them on Google Images. So say we look up images of Jesus, brand logos, or the face of Pete Davidson. Obviously, we are not going to get images that look identical, but rather images with distinctions. We will see different colors, different facial angles, different geometric layouts, and so on. We have moved from a unitary problem a particular image, to that of icons within an image. While Google might have figured this out for themselves to some degree, our problem is that in each of these searches, many of the results might need disambiguation. For example, searching for Jesus will likely provide images with something as simple as a cross which does not include Jesus at all. While in some cases, these might be valuable, they are not for our case.
Thus, first we must parse each image for what is in it, get those icons out of them, and then find out where they are online. Fortunately, Google does provide this information. All images found through Google search do include the indexed location, that is the webpage which contains that image. Then let us say we could use that to hyperlink to that page. Now we are faced with another problem. This problem is the context of use. That is, what is the icon of Jesus used for? When was it used? Perhaps I could do this quickly for one, two, or even a dozen images. But is this systematic or statistically relevant? No, it is not. This is where I lose many of the close textual researchers, but again, it is not that this work is meant to undermine what they have done. This work is meant to decide which of their theorizing claims are pragmatically more appropriate. However, every webpage can be scraped in the raw so long as it does not overwhelm the website infrastructure or trigger protocols that block us from getting that data, so getting data can be done more effectively to explain the contexts of a meme in a variety of ways that would prove useful, and perhaps would explain more broadly what policies could be considered for specific kinds of speech without such a myopic view from a particular platform. Alternatively, it might provide a more predictive trajectory for specific kinds of cultural usages of icons that could be understood through replication that does not yet exist in memetics.
The previous example is decidedly more in line with the interests of current Internet Memetic research. Perhaps most of the iconographic studies of icons vaguely gesture towards a policy concern or content management for platforms broadly. So far these claims have been so weakly predictive or descriptive that it would be unrealistic to see these studies as providing systematically useful solutions for platforms. However the method I just offered does, for better or worse.
That is to say, I just suggested a pretty strongly cybernetic approach to manage public actions which is very often an attempt to control cognitive frames which might be considered viral through the use of symbolic speech acts. However, some, reasonably may have serious ethical concerns with this application. Those who have these concerns, I empathize. I have mostly avoided the communications approach to memetics, for exactly this reason. Whether or not the authors of Internet Memetic studies would agree, the body of research there appears to sum to a greater goal of policing the public instead of understanding bodies and boundaries of cultural lineages. So, let us consider a different example, one that is outside of the realm of the usual kinds of policy and platform management. That is, let us look at an example of a generative memetics.
Let us, this time, consider the metadata surrounding searches instead. Let us say, I perform a search, but the response is not so great. I receive almost no images which answer my interest. This is a fairly common response with some searches, images or not. I almost never get precisely the answer I want when I am searching Stackoverflow for example. This is an example of how recommender systems fail technologically. Frequently, when this occurs a librarian or an educator might suggest I learn to use the platform better. If the data are there, and I simply did not find it, it is easier for me to learn to search better. Yet, if I am a developer for Stackoverflow, I might see systematic failures in search to be something which needs generative development.
As a developer, I might create more documentation suggesting how to do searches. For example, clarify how to use logical operators, key terms in programming languages, and so on. That is, I can make instruction manuals more bulky. Of course, as we know, people are terrible at following instructions. So instead the developer might realize value in memetic failures in search. Common search failures might simply be a failure in design, not cultural information.
That is, a developer might recognize that the systematic failure of search is a memetic search behavior that is harder to fix than predicting the memetic search behavior through cues. For example, I frequently will search for something like how to perform a specific for loop. But let us say I have never learned of for loops. Instead, I am likely to use language that is synonymous to my own pre-programming literate speech. In fact, whenever I am learning any new programming terminology, I often find myself being told to learn the language before I can even learn what I am asking for. This reminds me of a relatively simple analogy to dictionaries. My mom, an English teacher and high school librarian often used to refer me to a dictionary if I could not spell a word. But I frequently griped that looking up a word in the dictionary implies I already know how to spell it. While this is not entirely true, sometimes not being able to spell a word made looking up how to spell the word hilariously difficult.
Imagine how long it would take a child to learn to spell gnat without knowing if it started with a g. At some point, upon realizing that culturally, many people would perhaps look through all of the N words, then if they knew the word knight, they may go to the Ks before someone their mothers would laugh at them and tell them the error. Instead of being a laughing stock, imagine if the dictionary could respond to this issue by seeing where I stopped looking in the Ns and giving me suggestions. Certainly, some websites do this to some degree. However, I forever feel this difficulty with Stackoverflow. Furthermore, especially with visual media, I find searching is near impossible more than half the time. Have you ever tried looking up a video with almost no text description? It is a foolish game. Tiktok is incredibly difficult to to text searches for. Meme names on Know Your Meme equally so. Google attempts to resolve this with reverse image searches, but it also can be infuriating. Understanding the connectedness of the materially mediated world and our culturally internal cognitions about these recommender systems would offer us a much more fluid method of communicating with technology that often communication and education scholars consider to be a lack of literacy. Really, to my mind, this is less a lack of literacy, and more a power struggle for what things culturally mean. Proclaiming we must teach literacy is often the polite way to say that you must become acclimated to the culture of the educator in order to make sense of the world. Development of tools to approach this differently would likely provide us with a much less patronizing digital culture, and a more generative than repressive culture.
With this second development, a person in memetics currently might suggest that this is not memetics, but rather a different field. To this I would answer, yes, but only because we have made memetic theory impractical almost with intention to remain abstractly ideological despite what its researchers might proclaim. To move forward, we must restructure theory.
Applications in Search of a Theory
Frequently, when I mention systematic cultural disconnects from technology, people will point to Human-Computer Interaction (HCI), or applications of psychology, or horrendously literacy studies to solve the problem. While certainly, these are connecting spaces which can do something about this problem in varieties of highly applied practices, it is a pragmatic theory of replicated culture which addresses systematic issues more quickly. That is, a somewhat better development of memetic theory would perhaps be more practical at pointing out errors in technological design than stretching existing theories to attempt to explain thoughts and behaviors totally outside of their domain.
Perhaps the closest space to how I have been describing memetics is HCI. HCI, when done well, attempts to close the gap between diverse human cultures and technologies by developing technology for those cultures. However, HCI when it does this, is less science focused, and more design focused. Further, it is a fast-paced, conference oriented publishing culture. That is, it solves minor problems relatively quickly in the short run, but it has no clear long-run development of theory, and it seems opposed to doing so. It was developed as an engineering and design approach, not a theory of culture. Memetics, on the contrary, was and continues to be a theory of culture which contains within it the ability to explain how those cultures evolve for new contexts.
Memetics, however, could pick up a couple of core ideas from HCI despite the distinction on theory interests. Firstly, picking up on materially clear problems. Starting from an obvious technological issue rather than an abstract rhetorical issue would be more fundamentally impactful. Secondly, as I have been saying, using pragmatic approaches as opposed to the naturalistic of the neo-Darwinian approach, or the post-modernist, ideological, or constructionist approach that Internet Memetics pursues. That is, borrowing from the way design fields recognize cultural icons, symbols, and signs as carrying inherent material meanings in design would help memetics to know how memes are used as opposed to what researchers idealize their meaning to be. Memetics are relational, differentiating semiotic objects when interpreted this way. They are not loose ideological dog whistles or inaccessible secret codes all the time as Internet Memetics would have us believe. They have material connections to pragmatic interpretations that have affordances that can be seen in use rather than in abstractly interpreted ideologies.
In summary, memetics could gain from Pragmatism and looking to material frameworks to develop a datafiable empirical study. Eventually memetic structures which can be relational between technology and culture will systematically be found by doing this which are not specifically naturalistic or as abstract or scientifically elusive as design constructions of platform policies and software. In order to see the value of such an approach will likely happen in seeing better technology designs as well as more ethical approaches to managing digital policies and culturally contextual platform updates. And furthermore, the ethics of these ideas will not merely be delegated to abstractions of ideological frameworks of a select few disconnected researchers and their personal ethical interests.
Image Attribution: Know Your Meme
