Babak Bagheri

We know very little about how our brains work. Only recently have we begun to learn what goes on inside the cells and connections that make up the brain. These are good first steps, but the real challenge is to understand the network effects that actually lead to behaviors and how these network arrangements are formed. One group made a splash recently by claiming to have simulated the brain of a cat on a computer. This heroic computational effort needed one of the largest and fastest multi-processing computers on the planet. Even so, the simulation was limited and abstracted away from the real cat brain.

The RoBoard RB-100, a nano-itx board

Given this state of relative ignorance, can one take a practical engineering approach to construct an “artificial brain?” My contention is that this is possible. We need to combine insights from what little we know about the brain and complex computation in general. To these insights we should add something like the Nike tag line: “Just do it.” Fortunately, off-the-shelf processors are now powerful enough and networks are fast enough that we are less constrained by computational power than ever before. The key, as has been pointed out here before, is to avoid direct simulation of biological brains and think creatively about  computational kernels and network arrangements that can learn.

Engineering efforts of this kind will not only have direct benefits, but they will also enhance our understanding of biological systems. We should keep in mind though that these are only first steps. Ray Kurzweil’s singularity will not suddenly materialize tomorrow.

So what is your attention worth? In our attention-driven economy, this is a fairly fundamental question. For any product or service to do well, it has to attract attention. More and more, this attention has to be bought in one way or another. To make the right attention buying decisions, one has to have some notion of what attention is worth.

Eye (by Andrew James McNulty)

A few recent “market valuations” give fairly direct hints about the value of attention. The most recent valuation was the large investment, about $180 million, in a “social gaming” company. The company is private and secretive about revenues, but they do like to mention the size of their user base. Apparently, they have about 60 million “active” users. It’s hard to tell what percentage of the company this investment has bought. Let’s be generous and say 15%, that values the company at about $1.2 billion. So in this online social entertainment business, a pair of eyeballs is worth about 20 dollars. Another relevant piece of public information about this situation is that only 3% to 4% of this user base actually spends any money and the amounts being spent per month are small (less that three figures).

It would be interesting to push this exercise and guesstimate eyeball values for different kinds of businesses and contexts, especially how “engaged” the eyeballs are and how much the attached brains spend. But already it tells us something about how much it makes sense to spend on buying attention. If you can get 3% or so conversion and $20 or so per month in expenditure, it makes sense to spend a fair amount on acquiring those eyeballs. This is a little counter-intuitive given the current craze about “free viral and social” advertising. Of course, this bodes well for those who already have the eyeballs (ad inventory and distribution channels); if the trend holds, they can sell at a premium.

The “sales funnel” has been an important marketing concept. Together with market segmentation, it’s part of the common marketing diet. Interactive media give us pause about how valid these two classic concepts are. Is reaching customers still as simple as dividing the audience into appropriate segments, then sifting through the buckets over time to see who is willing to buy what?

There are, at least, new complications because of the new feedback loop of interactivity. Suspects, prospects and customers can talk back both to you and to others. So their interests and sales “responsiveness” are shaped by many more voices than before. The main effect is that the market buckets and funnels become leaky. A “qualified” prospect can become “unqualified” (and vice versa) because of a few “posts,” “comments” or even “tweets.” And changes like this reinforce each other because of the interactive feedback loop.

A Basic Feedback Loop

The upshot is that the entire buy/sell system becomes more volatile. A small whisper, if it triggers the right feedback loops, can have big consequences. What’s more, this sort of thing can happen almost silently. This is because the number of voices is becoming so large that  opinion feedback clusters can incubate without being noticed until they reach an audible threshold. A small-world network together with this kind of circular interaction can throw the usual segmentation and funnel calculations into disarray.

So what does this mean in practice? It means expecting and insisting on “planned outcomes” is becoming outdated. Instead we need dynamic arrangements that can react quickly in a volatile environment. The right kinds of reactions can dampen and steer the system. As usual, this is easier said than done.

Attention is a scarce commodity. This is strange given the fact that there are now over 6,000,000,000 of us humans on this planet. Surely, there should be a sizable audience for almost anything. Well, there is but not all that sizable. There are many reasons for this, but the core reason has to do with the limitations of the human brain. Yes, you read right; that magnificent instrument we all have in our skulls is limited. The important limitation here is our capacity to analyze and remember. We cannot possibly evaluate and recall the value of everything even a small fraction of humanity produces. So we rely on others’ judgments.

Small World Graph with Hubs

Not only do we rely on others’ evaluations, but we simplify even these second-hand judgements. The upshot of this human tendency is that we’ve created a world of “hubs” of attention. A very few people and groups, “hubs,” dominate our collective attention. Not only do the hubs dominate, but away from the hubs attention falls off exponentially.

In other words, points of attention form a “small world” graph with very big hubs. This power law of attention can be a boon for those who make up the hubs. So how do you become a hub? You’ve probably been given one answer by marketers: Niche Thyself. Basically, become a hub in a small group, then parlay that into becoming a bigger and bigger hub. The niche advice is probably the soundest one there is. But there are other things you can do.

Here’s a partial list:

• Do something stunning (good or bad doesn’t matter, but good is better).
• Do something encyclopedic (create a point of reference).
• Do something helpful (indispensable is even better).
• Connect others together (this is very popular these days).
• Ignore the hubs and go for the “long tail” (if you’re feeling clever).

You may want to make your own list along these lines.

Network effects had been neglected for quite a long time. The classical “reductionist” view of the world was simply this: if we understand the rules that govern the pieces of the universe, then we can easily deduce large-scale behaviors. The past century has shown that this is wishful thinking at best.

Much has now been said about the level of complexity that interconnections among simple components introduce. This appreciation for network effects has not yet been exploited for engineering purposes fully. The old reductionist views still dominate in most engineering disciplines. The same is true about other practical arts; we do not yet have good ways of purposefully exploiting network-introduced complexity.

The reasons for this neglect are deep. To exploit the kind of complexity that network connections bring about we need to look at design differently. We need to view design as guidance instead of control. Complex systems do not respond well to direct control; they can, however, be guided and steered. We know very little about techniques to do this kind of guidance and control effectively.

Japanese Zen Garden (National Geographic)

There is one group, though, that has been struggling with these methods for some time: teachers and trainers. Living systems, especially people and groups of people, present exactly the kind of complexity that requires guidance and steering. Unfortunately, the track record for teaching and training is not stellar.

Perhaps the most effective of trainers have been spiritual teachers, for example Zen masters. Zen spiritual leaders have instinctively understood that guiding a complex mind requires meticulous attention to the environment. These environments are arranged to evoke the proper frames of mind that encourage the right mental changes.

We should start thinking of the machines we build as potential trainees and students. Our task is to design into them the kind of complexity that can be guided as we need. If a machine is simple enough to be controlled directly (“programmed”), then it’s probably too simple to do anything really interesting.