Why Attention Economics?
We live in a gold rush, with digital entrepreneurs building businesses on mountains of users and trying to mine (then monetize) every second of attention invested on their site. We will see continued hyper-specialization as new social networks emerge and seek out audiences with untapped needs. As we improve our attention management software, we may see a freezing in network growth as global available attention pools decrease. What happens then?
Mass reciprocity is one trend I find particularly fascinating on social networks. The #FollowBack is used across networks as a signal of willingness to reciprocate any proffered social link. I used this tactic for gaining followers until recently, when I pulled a Chris Brogan and unfollowed over 7000 users. It occurred to me that I was diluting my attention to the point where I was sacrificing individual relationships in favour of amplifying of my own content. So I limited myself to follow no more than 1,000 accounts at any one time.
I wanted to understand what kind of differences you might observe in populations that distribute attention with low selectivity compared to those with higher selectivity. After some research, I found that a number of scholars had already examined some of the theoretical and philosophical underpinnings of an ‘attention economy.
Defining Attention Economics
Since many of the links I’ve provided within this post have their own definitions of an attention economy, I’d like to clarify how I will be using the terms. Where a node represents an object or individual that can receive and/or invest attention:
- Attention Economy = any network where attention is exchanged between more than one node
- Attention Economics = the study of the flow of attention within a network and the systems that organize and redistribute this attention between nodes
It follows that almost anyone who uses a social network is an attention economist, making daily decisions on how they will consume the attention of their audience.
The Attention Economists
There are several researchers and scholars that have examined the flow of attention from an economic perspective, inspired by a 1971 speech by Nobelist Herbert Simon. who identified the scarcity of attention as a major driving force in a new economy:
”… a wealth of information means a dearth of something else – a scarcity of whatever it is that information consumes. What information consumes is rather obvious: it comes the attention of its recipients. Hence a wealth of information creates a poverty of attention, and a need to allocate that attention efficiently among the overabundance of information sources that might consume it.”
The rest of Simon’s article focuses on the importance of early adoption of computing technology as a recipe for success. It would seem his foresight was flawless, although maybe not on the timescale he recommends in the paper.
Michael Goldhaber’s The Attention Economy and the Net was one of the first clear elucidations of the internet as a space to trade attention, although he first to used the term ‘attention economy’ (despite many sources falsely citing Prof. Herbert Simon) in a talk that was published in Education and the American Dreamin 1989. Jonathan Beller followed suit when he wrote about an “informal economy [of] (attention)” in a footnote of a paper in 1994 and would much later publish the book The Cinematic Mode of Production: Attention Economy and the Society of the Spectacle.
In 1999, Georg Franck added to Goldhaber’s definition by elucidating the importance of de-materialization and virtualization as driving forces towards an attention economy, since they stand to decrease the demand for a range of careers that focus on physical creation of objects, freeing up more “attention workers.”
The first book about the attention economy by Davenport and Beck was published in 2002, but the (very over-priced) text reads like a guide to the importance of earning and organizing attention, with outdated website examples and some limited descriptions of predicted “attention-monitoring technologies.”
While they’ve assembled an interesting set of references, they completely neglected the ongoing conversation that followed Goldhaber’s first article about attention economics in First Monday and Telepolis, and only gave him two scant mentions in their preface! Maybe if they had written a section on crimes of the attention economy, they would have recognized their own citation-skulduggery.
Alex Iskold’s four articles at ReadWriteWeb from 2007 outline examples of websites functioning as attention economies. Iskold also pointed out that we need to develop attention standards and “each silo that captures a users attention needs to provide an interface to access it.” He predicted consumers would eventually demand open access to their attention data, although the movement has been lacklustre and so has the response from the big players in social media.
On the heels of Beller’s book, English Professor Richard Lanham published The Economics of Attention: Style and Substance in the Age of Information in 2007. Although similar to the Davenport and Beck book in many regards, it reads like high level guide to creating attention-earning content strategy on the internet. Goldhaber didn’t particularly like this book (maybe because Lanham also failed to reference his work?), and makes it very plain, with his review entitled, “How (Not) To Study the Attention Economy.” At one point, Goldhaber brings up the fact that neither he nor his fellow attention economists had any formal training in economics:
“The fact that three such disparate people hit on more or less the same idea at similar times might just be conincidence, or it might suggest there is something to it. What does it mean then that none of us are professional economists? Perhaps it was necessary. If you are proficient in a discipline, you have learned to reject thoughts that are outside the box.”
“If attention economics were mathematizable, it would certainly require a rather different mathematics.”
“Attention is not standardized and measurable like a commodity; you can’t give or trade away all the attention you have accumulated, as would be possible with currency and the goods bought with it, nor can you barter attention for something else.”
Some of this ‘mathematization’ has already been published by Josef Falkinger, a career researcher and Dean of economics at the University of Zurich. His 43-page working paper suggests that anything that allows the sender to increase the strength of their signal within a network will decrease the overall reach of any individual sender, since users will begin to focus their attention on increasing their own local diversity. Said differently, an attention economy will encourage users to shift their attention away from celebrities or major nodes within a network (non-reciprocal relationships) as they recognize the value and importance of finding connections that guarantee returns on their attention investments (reciprocal relationships).
Since then, there have been a number of researchers who have studied the flow of attention while incorporating mathematical, with HP’s Senior Research Fellow Bernardo Huberman standing out as a clear authority in the field. Just shortly after Goldhaber published his original article on attention economics in 1997, Huberman was first author on a paper entitled, “An Economics Approach to Hard Computational Problems“ and has co-authored a number of papers relating to information exchange within networks.
There have also been several examples of applied attention economics research. Seriosity Inc. patented an attention economy for messaging within a business environment and more recently Fan and Zhao proposed a system for modelling collaborative activities using attention as a core consideration. Also, Kawano et al. revealed that they were working on a prototype for simulating attention exchange on Twitter.
While I’ve neglected to mention lots of really interesting research and writing, I hope to cover more in future blog posts.
The State of Attention Tracking Technology
From Clicking to Gestural Interaction to Gaze Control
Currently, we track attention as the bounce rate, number of unique visitors or views, and many websites and search engines sell attention to advertisers using cost-per-click or cost-per-impression metrics. Tablet devices such as the iPad offer a new range of gestural data for tracking interactions and this will likely mature as we develop gloves that allow Minority Report-like gestural control of technology.
Right now, for anywhere between $7-40K, you can invest in a hardware/software combo system that will track a user’s gaze as they stare at a target, such as a website. Our increasingly efficiency-focused workplaces will likely require us to adopt Project Glass-like visors or weardisplay-ready contact lenses in the near future, which would allow employers to track how their employees invest their work time. While this might seem restrictive, I think many people would trade transparency about they spend their work time for increased flexibility on working hours and location. Why even have a specific location for work when your supervisor can simply tune in to live spectacle-mounted cameras or review a daily video digest of your work?
The Future: Limited Emotional Categorization with Affective Computing
Attention has many layers and determining the intensity of how it is being spent will be important to furthering our ability to track it. Affective computing is one potential future solution that currently involves two fields of sub-research, as suggested by Xiangyang Li and Qiang Ji:
- Sensory data and measures: information regarding your physiology and speech that are sampled and compared to other datasets in order to try to infer emotional state
- Graphical facial and gestural data: information from photos and videos taken of you can be compared to other data sets to try to infer emotional state
Rosalind W. Picard pointed out the major shortcoming of affective technology: “No one can read your mind.” However, in this review paper she goes on to outline how universal recognition of emotional states by any technology was irrelevant, provided that technology could learn to infer emotional state based on past individual data.
“The experiments in identifying underlying sentic state from observations of physical expression only need to demonstrate consistent patterning for an individual in a given perceivable context. The individual’s personal computer can acquire ambient perceptual and contextual information [...] to identify autonomic emotional responses conditioned on perceivable non-emotional factors. [...] The priorities of your agent could shift with your affective state.”
If we had reliable affective computing technology, we could potentially pick out a spectrum of standardized emotions and try to use ‘personal agents’ to try to set up an individualized intensity metric based on your typical responses, but the system’s success would be largely dependent on the agent software.
The Further Future: Jacking into Neurons
In 2009, University of Wisconsin Biomedical Engineers developed an EEG cap that allowed them to tweet by brain activity. Prof. Justin Williams:
“And what your brain does is, if you’re looking at the ‘R’ on the screen and all the other letters are flashing, nothing happens. But when the ‘R’ flashes, your brain says, ‘Hey, wait a minute. Something’s different about what I was just paying attention to.’ And you see a momentary change in brain activity.” “
See the quicktime video over at their website. Brain-computing interfaces (BCI) have been a staple of science fiction, but they don’t appear to be on our short-term scientific horizons. The conclusion section of a brain-computer interface review by 11 researchers in the Journal of Neuro Engineering:
“Why is it that, in all these years of development, not more progress has been achieved? We believe that in each of the steps of the BCI cycle major improvements are needed. Yet, expectations concerning BCI’s potential use easily runs high, especially in the popular media. It is important, both for the research community as well as for potential users, to make a clear distinction between currently feasible and potentially possible applications in order to prevent unrealistic expectations.”
So unfortunately, we’re probably not getting nanites in the brain, or caps for thought-controlled devices in the near future.
One day we might tap into the kinds of data we receive from brain-scanning equipment (such as the EEG, MEG, PET and fMRI) in a much more mobile, and permanent manner, we could then begin to define the intensity, or completeness, of attention as it is being spent.
“Dan moved to block the bedroom door. “Wait a second,” he said. “You need rest.”I fixed him with a doleful glare. “I’ll decide that,” I said. He stepped aside.“I’ll tag along, then,” he said. “Just in case.”I pinged my Whuffie. I was up a couple percentiles—sympathy Whuffie—but it was falling: Dan and Lil were radiating disapproval. Screw ’em.”
This set-up he describes is based not only on a regular neuronal jack to measure where Dan and Lil were paying attention, but also the precise type of attention and emotions associated with that attention. Doctorow’s Whuffie seems to have some complicated conversion system that generates positive transference of Whuffie for positive emotions, and loss of Whuffie when receiving negative emotions. Taking into account the earlier section of this post that discusses brain-computer interfaces, I doubt even the most optimistic futurists would predict this kind of technology on the foreseeable horizon.
Thus, I would respectfully disagree with Michael Goldhaber when he says:
“… attention is not absolutely quantifiable and never will be.”
As I wrote about earlier in this post, we are already on the path to developing improved attention-tracking technology, meaning we are coming closer to measuring attention in an ‘absolute’ manner. I think Aiyer-Ghosh summarized the semantic argument best:
“To conclude, given the validity of the core economic concept of scarcity, “information economy” and “knowledge economy” are inappropriate to describe the “new” economy – if taken at face value rather than as convenient placeholders. “Attention economy” is closer to the truth, being tied to the truly scarce resource of cyberspace, its human inhabitants.”
In the same paragraph, Aiyer-Ghosh recommends we just stick with ‘economics,’ but I think this seriously risks confusing a wider readership. Falkinger’s work demonstrates some of the major fundamental divergences between our transactional economy and an attention economy, it seems to make sense to me that Goldhaber’s original term does indeed deserve its distinction.
Recently, I’ve seen social media speculators refer to a number of alternative economies such as, the ‘data,’ ‘knowledge,’ ‘reputation,’ and ‘intention‘ economies. However, I would argue that most of these would have to rely on some measurement of attention in order to accurately determine value. Any system that measures the flow of attention and creates an algorithm or interactive system to transform it into another value, at the very least, will benefit from an understanding of this flow.
A system designed to value data or knowledge might, for instance, try to reflect the usefulness or popularity of a particular item. Since certain items will inevitably receive different amounts of attention in a crowd-sourced scoring system, their value would be directly related to the amount of attention received. One might argue that Google’s search is a knowledge, or data economy, since it creates a ranking system for all information surrounding a particular keyword. However, the information it uses to generate these scores is based on attempts at measuring attention flow: backlinks, provided they don’t get picked out by Google’s Penguin algorithm as paid links or for ‘keyword stuffing’ their website. In Google’s opinion, paying or using content-devaluing tactics to elevate your perceived attention revenues from their algorithm is a crime of the attention economy.
Increasing immersion in cyberspace will provide us with endless opportunities to understand ourselves from the waves of data left in our wakes. Whereas marketing used to be most about creativity and intuition, it will become a data-heavy field in need of informaticians and in pursuit of the most quantifiably sound methods for selling products. I’m not convinced that an zero-sum game, with organizations endlessly chasing new attention-getting memes and adverts is sustainable. More ‘users’ are levelling up to digital native status and the marketplace already offers a number of attention-sensitive strategies for website and product design, represented well by the global shift to simpler, mobile-friendly, user-centric design. With some of the aforementioned advancements in technology, I think we’ll see the researchers that study the flow of attention become absolute necessities for many organizations.
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- Abecassis, D., Cheng, H., Philips, M., Read, L., Reeves, B., Roy, S., and Atherton, R. (2011). US Patent: 7,918,388 B2. United States Patent to Seriosity Inc.
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- Fan, S., and Zhao, J. L. (2012). Attention-Aware Collaboration Modeling. E-Life: Web enabled-convergence of commerce, work and social life.
- Franck, G. (1999). The Economy of Attention. Telepolis. Retrieved May 17, 2012, from http://www.heise.de/tp/artikel/5/5567/1.html
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- Simon, H. (1971). Designing Organizations for an Information-Rich World. Computers, Communication, and the Public Interest.
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