Meritocracy

Is meritocracy intrinsically bad, or good for some things, not so good for others?

A recent book review in the New Yorker ruminated on the progress and defects of the meritocracy, a word born in sarcasm, now become an ideology and platitude. I am not sure that the review really touched on the deeper issues involved, so am motivated to offer a followup. The term was coined by a British sociologist, which is significant, as it describes a fundamental shift from the preceding system, the class system, as a way of allocating educational opportunity, professional work, military grades, and social status in general. It would be natural for someone of the British upper class to decry such a change, though the coiner, Michael Young, was generally a socialist and egalitarian, though eventually made into a Baron for his services ... ironically.

The book review focused mostly on the educational establishment, where the greatest sea change has occurred. Where elite schools used to lazily accept their students from elite prep academies, from certain rich families and class backgrounds, now they make a science of student selection, searching far and wide, high and low, for the most meritorious candidates. Are SAT scores useful? Not very, the new consensus has it, especially as such tests unconsciously reproduce various cultural biases, instead of rendering the true grail- a score of merit, whatever that really might be. But anyhow the slicing is done, higher education is now an intense, mostly meritocratic sorting process, granting opportunities and education on the basis of qualifications, intent on funneling the most capable people into the higher rungs of the ladder of professional activities and status.

One question is whether all this laborious sorting of students has been a good thing, overall. Do we get better staffed hospitals, better filled jobs throughout the economic system by virtue of this exquisitely and remorselessly selective weeding system? Yes we do, perhaps at the cost of some social serendipity, of finding CEO material in the mailroom, and the like.

But the deeper question is whether all this selection has been good for our society at large. There is answer has to be more guarded. If economic efficiency is the only goal, then sure. But it isn't, and some of our social atomization, and creeping class-ism and despair in the lower rungs of society comes from the intensification of meritocratic selection, which spills over to many other areas of society, directly through income and wealth, and indirectly through many other mechanisms of status, particularly politics. Much of Trump's support comes from people sick of the "elites"- those selected by SAT scores, course grades, and the like to rule over the working class. It is not clear that grubbing for grades and mastering standardized exams have done such a good job at selecting a ruling political class. That class has not done a very good job, and that poor performance has sapped our social solidarity. The crisis is most glaring in the stark cost of losing out- homelessness and destitution- the appalling conditions that are the mirror of billionaires also produced by this Darwinian system.

The problem is that we need areas of our lives that are not plugged into the rat race, for both psychological and sociological reasons. Such areas are increasingly scarce as this new gilded age gobbles up all our social relations under the rubric of the market, paticularly with its newly internet-extended capabilities. Religion has traditionally been a social locus where every one is worth the same- many classes come together to share some profound feelings, and occasionally explicit anti-establishment messages, (though also often a message of exalted status vs some other sect, faith, or unbelievers). But religion is dying, for good reason.

A town meeting

Civic associations and volunteer life have in the US been a frequent antidote to class-ism, with people of all classes coming together to make each others' lives better. But modern transportation has enabled the definitive sorting of classes by socioeconomic level, rendering civic activity, even when it occurs, poor at social mixing. No longer does a geographic community have to include those of all professions and walks of life to be viable. We can have lilly-white suburbs and gated communities, and have any tradespeople and retail employees commute in from far away. That is a problem, one caused ultimately by fossil fuels and the freedom that they bring. The civic sector has also been invaded by an army of vanity foundations sponsored by the rich- a patronizing and typically futile approach to social betterment. Volunteerism has also been sapped by lack of time and money, as employees throughout the economic system are lashed ever more tightly to their jobs, stores kept open at all hours, and wages for most stagnate. Unions are another form of civic association that have withered.

All this has frayed the local civic and social connections, which are the ultimate safety net and source of civic solidarity. While Republicans bray about how terrible government is at replacing these services with top-down programs, (with some justification), they have at the same time carried out a decades-long battle to weaken both government and civic life, leaving a smoldering ruin in the name of a new feudal overlordship of the "job-creators"- the business class. That is the ultimate problem with meritocracy, and while appreciating its role in spreading social justice in the distribution of educational and professional opportunity, (a promise that is far from fully realized), we need to realize its cost in other areas of our national culture, and work to restore community diversity, community institutions, and community solidarity.

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• Quote of the week:

Where love rules, there is no will to power; where power predominates, there love is lacking. The one is the shadow of the other. – Carl Jung

The Participation Mystique

How we relate to others, things, environments.

We are all wrapped up in the impeachment drama now, wondering what could be going on with a White House full of people who have lost their moral compasses, their minds. Such drama is an exquisite example of participation mystique, on our part as we look on in horror as the not very bright officials change their stories by the day, rats start to leave the sinking ship, and the president twists in the wind. We might not sympathize, but we recognize, and voyeuristically participate in, the emotions running and the gears turning.

Carl Jung took the term, participation mystique, from the anthropologist Lucien Levy Bruhl. The original conception was a rather derogotory concept about the animism common among primitive people, that they project anthropomorphic and social characters to objects in the landscape, thus setting up mystical connections with rocks, mountains, streams, etc. Are such involvements characteristic of children and primitive people, but not of us moderns? Hardly. Modern people have distancing and deadening mechanisms to manage our mental involvement with projected symbologies, foremost among which is the scientific mindset. But our most important and moving experiences partake of identification with another- thing or person, joining our mental projection with their charisma, whatever that might be.

Participation mystique remains difficult to define and use as a concept, despite books being written about it. But I would take it as any empathetic or identification feelings we have toward things and people, by which the boundaries in between become blurred. We have a tremendous mental power to enter into other's feelings, and we naturally extend such participation (or anthropomorphism) far beyond its proper remit, to clouds, weather events, ritual objects, etc. This is as true today with new age religions and the branding relationships that every company seeks to benefit from, as it is in the more natural setting of imputing healing powers to special pools of water, or standing in awe of a magnificent tree. Such feelings in relation to animals has had an interesting history, swinging from intense identification on the part of typical hunters and cave painters, to an absurd dismissal of any soul or feeling by scientistic philosophers like Descartes, and back to a rather enthusiastic nature worship, nature film-making, and a growing scientific and philosophical appreciation of the feelings and moral status of animals in the present day.

Participation mystique is most directly manipulated and experienced in the theater, where a drama is specifically constructed to draw our sympathetic feeings into its world, which may have nothing to do with our reality, or with any reality, but is drenched in the elements of social drama- tension, conflict, heroic motivations, obstacles. If you don't feel for and with Jane Eyre as she grows from abused child, to struggling adult, to lover, to lost soul, and finally to triumphant partner, your heart is made of stone. We lend our ears, but putting it psychologically, we lend a great deal more, with mirror neurons hard at work.

All this is involuntary and unconscious. Not that it does not affect our conscious experience, but the participation mystique arises as an automatic response from brain levels that we doubtless share with many other animals. Seeing squirrels chase each other around a tree gives an impression of mutual involvement and drama that is inescapable. Being a social animal requires this kind of participation in each other's feelings. So what of the psychopath? He seems to get these participatory insights, indeed quite sensitively, but seems unaffected- his own feelings don't mirror, but rather remain self-centered. He uses his capabilities not to sympathise with, but to manipulate, others around him or her. His version of participation mystique is a truncated half-experience, ultimately lonely and alienating.

And what of science, philosophy and other ways we systematically try to escape the psychology of subjective identification and participation? As mentioned above in the case of animal studies, a rigid attitude in this regard has significantly retarded scientific progress. Trying to re-establish objectively what is so obvious subjectively is terribly slow, painstaking work. Jane Goodall's work with chimpanzees stands as a landmark here, showing the productive balance of using both approaches at once. But then when it comes to physics and the wide variety of other exotic phenomena that can not be plausibly anthropomorphized or participated in via our subjective identification, the policy of rigorously discarding all projections and identifications pays off handsomely, and it is logic alone that can tell us what reality is.

• The Democratic candidates on worker rights.
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• Back when some Republicans had some principles.
• If all else fails, how about a some nice culture war?
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• #DeleteFacebook
• Graphic: who is going to tax the rich? Who is pushing a fairer tax system overall? Compare Biden with Warren carefully.

Thinking Ahead in Waves

A computational model of brain activity following simple and realistic Bayesian methods of internal model development yields alpha waves.

Figuring how the brain works remains an enormous and complicated project. It does not seem susceptible to grand simplifying theories, but has in contrast been a mountain climbed by thousands, in millions of steps. A great deal of interest revolves around brain waves, which are so tantalizingly accessible and reflective of brain activity, yet still not well understood. They are definitely not carrying information in the way radio stations send information, whether in the AM or FM. But they do seem to represent synchronization between brain regions that are exchanging detailed information through their anatomical, i.e. neuronal, connections. A recent paper and review discuss a theory-based approach to modeling brain computation, one that has the pleasant side effect of generating alpha waves- one of the strongest and most common of the brain wave types, around 10 Hz, or 10 cycles per second- automatically, and in ways that explain some heretofore curious features.

The model follows the modern view of sensory computation, as a Bayesian modeling system. Higher levels make models of what reality is expected to look/hear/feel like, and the lower level sensory systems, after processing their inputs in massively parallel fashion, send only error signals about what differs from the model (or expectation). This is highly efficient, such that boring scenery is hardly processed or noticed at all, while surprises form the grist of higher level attention. The model is then updated, and rebroadcast back down to the lower level, in a constant looping flow of data. This expectation/error cycle can happen at many levels, creating a cascade or network of recurrent data flows. So when such a scheme is modeled with realistic neuronal communication speeds, what happens?

A super-simple model of what this paper implements. The input node sends data, in the form of error reports, (x(t)), to the next, higher level node. In return, it gets some kind of data (y(t)), indicating what that next level is expecting, as its model of how things are at time t.

The key parameters are the communication speeds in both directions, (set at 12 milliseconds), the processing time at each level, (set at 17 milliseconds), and a decay or damping factor accounting for how long neurons would take to return to their resting level in the absence of input, (set at 200 milliseconds). This last parameter seems most suspect, since the other parameters assume instantaneous activation and de-activation of the respective neurons involved. A damping outcome/behavior is surely realistic from general principles, but one wonders why a special term would be needed if one models the neurons in a realistic way, which is to say, mostly excitatory and responsive to inputs. Such a system would naturally fall to inactivity in the absence of input. On the other hand, a recurrent network is at risk of feedback amplification, which may necessitate a slight dampening bias.

The authors generate and run numerical models for a white noise visual field being processed by a network with such parameters, and generate two-dimensional fields of waves for two possibilities. First is the normal case of change in the visual field, generating forward inputs, from lower to higher levels. Second is a lack of new visual input, generating stronger backward waves of model information. Both waves happen at about 8 times the communication delay, or about 100 milliseconds, right in the alpha range. Not only did such waves happen in 2-layer models with just one pair of interacting units, but when multiple modules were modeled in a 2-dimensional field, traveling alpha waves appeared.

When modeled with multiple levels and two dimensions, the outcome, aside from data processing, is a traveling alpha wave that travels in one direction when inputs predominate (forward) and in the opposite direction when inputs are low and backward signals predominate.

Turning to actual humans, the researchers looked more closely at actual alpha waves, and found the same thing happening. Alpha waves have been considered odd in that, while generally the strongest of all brain waves, and the first to be characterized, they are strongest while resting, (awake, not sleeping), and become less powerful when the brain is actively attending/watching, etc. Now it turns out that what had been considered the "idle" brain state is not idle at all, but a sign of existing models / expectations being propagated in the absence of input- the so-called default mode network. Tracking the direction of alpha waves, they were found to travel up the visual hierarchy when subjects viewed screens of white noise. But when their eyes were closed, the alpha waves traveled in the opposite direction. The authors argue that normal measurements of alpha waves fail to properly account for the power of forward waves, which may be hidden in the more general abundance of backward, high-to-low level alpha waves.

Example of EEG from human subjects, showing the directionality of alpha wave travel, in this case forward from input (visual cortex in the back of the brain) to higher brain levels.

"Therefore, we conjecture that it may simply not be possible for a biological brain, in which communication delays are non-negligible, to implement predictive coding without also producing alpha-band reverberations. Moreover, a major characteristic of alpha-band oscillations—i.e., their propagation through cortex as a traveling wave—could also be explained by a hierarchical multilevel version of our predictive coding model. The waves predominantly traveled forward during stimulus processing and backward in the absence of inputs. ...  Importantly though, in our model none of the units is an oscillator or pacemaker per se, but oscillations arise from bidirectional communication with temporal delays."

Thus brain waves are increasingly understood as a side effect of functional synchronization and, in this case, intrinsically associated with the normal back-and-forth of data processing, which looks nothing like the stream of data from a video camera, but something far more efficient, using a painstakingly-built internal database of reality to keep tabs on, and detect deviations from, new sensations arriving. It remains to ask what exactly this model function is, which the authors term y(t) - the data sent from higher levels to lower levels. Are higher levels of the brain modeling their world in some explicit way and sending back a stream of imagery which the lower levels compare with their new data? No- the language must far more localized. The rendition of full scenery would be reserved for conscious consideration. The interactions considered in this paper are small-scale and progressive, as data is built up over many small steps. Thus each step would contain a pattern of what is assumed to be the result of the prior step. Yet what exactly gets sent back, and what gets sent onwards, is not intuitively clear.

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• To each his own.. delusions.
• China gets some pushback.
• Full-on corruption.

High Intelligence is Highly Overrated by Highly Intelligent People

AI, the singularity, and watching way too much science fiction: Review of Superintelligence by Nic Bostrom.

How far away is the singularity? That is the point when machine intelligence exceeds human intelligence, after which it is thought that this world will no longer be ours to rule. Rick Bostrom, a philosopher at Oxford, doesn't know when this will be, but is fearful of its consequences, since, if we get it wrong, humanity's fate may not be a happy one.

The book starts strongly, with some well argued and written chapters about the role of intelligence in humanity's evolution, and the competitive landscape of technology today that is setting the stage for this momentous transition. But thereafter, the armchair philosopher takes over, with tedious chapters of hairsplitting and speculation about how fast or slow the transition might be, how collaborative among research groups, and especially, how we could pre-out-think these creations of ours, to make sure they will be well-disposed to us, aka "the control problem".

Despite the glowing blurbs from Bill Gates and others on the jacket, I think there are fundamental flaws with this whole approach and analysis. One flaw is a failure to distinguish between intelligence and power. Our president is a moron. That should tell us something about this relationship. It is not terribly close- the people generally acknowledged as the smartest in history have rarely been the most powerful. This reflects a deeper flaw, which is, as usual, a failure to take evolution and human nature seriously. The "singularity" is supposed to furnish something out of science fiction- a general intelligence superior to human intelligence. But Bostrom and others seem to think that this means a fully formed human-like agent, and those are two utterly different things. Human intelligence takes many forms, and human nature is composed of many more things than intelligence. Evolution has strained for billions of years to form our motivations in profitable ways, so that we follow others when necessary, lead them when possible, define our groups in conventional ways that lead to warfare against outsiders, etc., etc. Our motivational and social systems are not the same as our intelligence system, and to think that anyone making an AI with general intelligence capabilities will, will want to, or even can, just reproduce the characteristics of human motivation to tack on and serve as its control system, is deeply mistaken.

The fact is that we have AI right now that far exceeds human capabilities. Any database is far better at recall than humans are, to the point that our memories are atrophying as we compulsively look up every question we have on Wikipedia or Google. And any computer is far better at calculations, even complex geometric and algebraic calculations, than we are in our heads. That has all been low-hanging fruit, but it indicates that this singularity is likely to be something of a Y2K snoozer. The capabilities of AI will expand and generalize, and transform our lives, but unless weaponized with explicit malignant intent, it has no motivation at all, let alone the motivation to put humanity into pods for its energy source, or whatever.

People-pods, from the Matrix.

The real problem, as usual, is us. The problem is the power that accrues to those who control this new technology. Take Mark Zuckerberg for example. He stands at the head of multinational megacorporation that has inserted its tentacles into the lives of billions of people, all thanks to modestly intelligent computer systems designed around a certain kind of knowledge of social (and anti-social) motivations. All in the interests of making another dollar. The motivations for all this do not come from the computers. They come from the people involved, and the social institutions (of capitalism) that they operate in. That is the real operating system that we have yet to master.

• Facebook - the problem is empowering the wrong people, not the wrong machines.
• Barriers to health care.
• What it is like to be a psychopathic moron.