Broken Symmetry

We are most free when we are most bound to others

Robert Jensen makes the case:

When bonds are created under conditions of mutual respect and shared power, our freedom is deepened by such interdependence. Our strength is not sapped by these bonds but is enhanced by the emergent properties of collective human action. The individual efforts of numerous people cannot simply be added together and plugged into an equation to predict the outcome, but rather their simple actions come together in a collective result that is novel and irreducible. The most creative force does not come from a power, centralized either in one person or one institution and its bureaucracy, which imposes its will on others and treats people as inputs whose energy can be plugged into a formula for production. The most creative force comes from distributed power that channels the contributions of many into ends that people define collectively.

Via the Omnivore at Bookforum -- the same that I have failed to cite on numerous occasions in the past because of the way I open and close tabs going through the links to those posts. Get yourself on the Omnivore feed!

Carol Mimura on the Nuances of Managing IP Rights

Since I recently complained about the culture in technology transfer offices, I thought it only fair to point out that there are indeed a few universities that have developed or are developing a healthier approach to university-industry relations. Carol Mimura at UC Berkeley recently posted a draft book chapter on SSRN:

[Tech transfer] is an ongoing relationship continuum, not just a single transaction. A relationship continuum spans many years. It results from many points of contact, and many engagement types. It is akin to building a pyramid or climbing a staircase, or contributing different sectors of a pie to create a whole. Our networks are essential. We cannot accelerate innovation on our own; rather, our public-private partnerships and product development partnerships demonstrate that we can expedite translational research and bridge funding gaps through creative partnering and flexible contracting.

Success under the relationship model consists of rights transfer and knowledge transfer in both directions (into and out of the university) to enable innovation acceleration, deployment, uptake, and translation. By many measures, the relationship model has borne fruit. By valuing corporate relationships more than any single transaction, utilizing our networks to advantage, and valuing research support as highly (if not more highly) than license revenue, the overall industry dynamic has changed. Cultural and negotiation biases have been reduced, industry and foundation funding have risen dramatically, collaboration types and numbers have increased, barriers to gifting into the university have been lowered, and greater numbers and types of contracts and strategic alliances have been formed. We have also enjoyed reputational gains as a campus that has improved its corporate relations and contracting units.

The high-bandwidth feedback loops established through what Mimura calls a "relationship-based" approach to tech transfer are an example of the integrated complex systems that are a theme for this blog. Like the neural networks of its individual members, the social networks established can learn over time, gradually building up tacit knowledge of the science and engineering problems that pose challenges both to public and private organizations.

A key cultural difference between UC Berkeley's IPIRA and other university tech transfer offices is that Mimura and her team first took the time to learn about the needs of every stakeholder involved in these complex, multilateral agreements. As a result, the deals she has closed -- including the pathbreaking BP-Berkeley deal and the Socially Responsible Licensing Program (SRLP) -- are nothing less than the future of the IP market. Although it might be inconvenient for some market participants to acknowledge, ultimately the highest value of IP rights is realized through the increased collaboration (and hence learning) that they promote.

Vintage Steve Blank

If you're not reading his blog, you are missing out. Every post is priceless. Here's a bit from his latest:

When I was at Zilog, the Z8000 peripheral chips included the new “Serial Communications Controller” (SCC). As the (very junior) product marketing manager I got a call from our local salesman that someone at Apple wanted more technical information than just the spec sheets about our new (not yet shipping) chip. I vividly remember the sales guy saying, “It’s only some kid in field service. I’m too busy so why don’t you drive over there and talk to him.” (My guess is that our salesman was busy trying to sell into the “official” projects of Apple, the Lisa and the Apple III.)

Zilog was also in Cupertino near Apple, and I remember driving to a small non-descript Apple building at the intersection of Stevens Creek and Sunnyvale/Saratoga. I had a pleasant meeting and was as convincing as a marketing type could be to a very earnest and quirky field service guy, mostly promising the moon for a versatile but then very buggy piece of silicon. We talked about some simple design rules and I remember him thanking me for coming, saying we were the only chip company who cared enough to call on him (little did he know.)

I thought nothing about the meeting until years later. Long gone from Zilog I saw the picture of the original Macintosh design team. The field service guy I had sold the chip to was Burrell Smith who had designed the Mac hardware.

The SCC had been designed into the Mac and became the hardware which drove all the serial communications as well as the AppleTalk network which allowed Macs to share printers and files.

Some sales guy who was too busy to take the meeting was probably retired in Maui on the commissions.

The Identification Problem and Revealed Preferences

Mankiw and Sumner put a gloss on the textbook explanation of the identification problem, which for the uninitiated is explained well-enough by the wikipedia entry here.

But even after reading what Mankiw and Sumner (and by the way, I love Sumner's fearless curiosity), I'm not particularly happy. This is what non-social scientists would call a mess! No wonder there has been a gradual shift within the economics field toward more direct measurements that avoid the most serious identification problems.

Here are a few observations from a non-economist trained in measurement theory by physicists:

The reason the identification problem is so difficult is because revealed preferences for the supply schedule and demand schedule cannot be measured simultaneously for the same population.

You have to measure one, then the other. Meanwhile you have to assume that neither schedule has shifted. Fat chance these days.

Why not start with a more direct measure of supply and demand and avoid the identification problem altogether? Look at the frequency distribution of buying and selling. Price is only a measure of short-term supply and demand -- hence stable only when the frequency distributions are stationary (i.e., when the system is "ergodic").

End of the Line for Financial Telemarketer Who Violated Do Not Call Rules

Who doesn't feel a bit of glee on reading this kind of news:

A financial services telemarketer who allegedly violated several requirements of the Federal Trade Commission’s Do Not Call Rule – from calling hundreds of thousands of consumers on the National Do Not Call Registry to failing to transmit accurate caller ID information – has settled the government’s charges and is banned from telemarketing to consumers for five years.

Only is five years enough?

Acoustically driven programmable liquid motion using resonance cavities

From Sean M. Langelier, Dustin S. Chang, Ramsey I. Zeitoun and Mark A. Burns:

Performance and utility of microfluidic systems are often overshadowed by the difficulties and costs associated with operation and control. As a step toward the development of a more efficient platform for microfluidic control, we present a distributed pressure generation scheme whereby independently tunable pressure sources can be simultaneously controlled by using a single acoustic source. We demonstrate how this scheme can be used to perform precise droplet positioning as well as merging, splitting, and sorting within open microfluidic networks.

Via Technology Transfer Tactics

Thoughts on High-Frequency Trading

I've been thinking about doing a longer post on this topic for a while since it fits so well with the idea of applying Fourier analysis to market regulation. Tyler Cowen blogs about it today:

The correct judgment of efficiency occurs at the system-wide level, not at the level of the individual trading strategy. The short-run story is that private profits exceed social returns but in the longer run the trading activity and liquidity brings increasing social returns and better communication of information.

Especially interesting was the comment from Matt Belcher:

I'm a high-frequency trader so take my comments on that basis. Prior to high-frequency trading and fully-electronic markets, the most trading profits went to the physically largest and most charismatic traders on the trading floors. By being large or gregarious they were more easily able to get the attention of brokers and get filled on their orders first, effectively front-running the other traders on the floor. On the NYSE, the specialist in charge of the book also could also extract profits at will. Since the advent of HFT, profits have moved from these traders to the ones with the best computer scientists. You can argue whether the new market is more efficient or fair, but you can't claim that the old one was somehow perfect and impossible to manipulate.

Putting aside fraud like churning and front-running (i.e., assuming the government is monitoring it!), from a social perspective HFT simply turns the fastest firms into the market makers by giving them a competitive advantage over other market makers in profiting on the spread. One could make a good argument, then, that the investments in HFT are a waste from a social perspective. Given the fact that the frequency of new information about public company stock, for example, becomes available on a time-scale much, much longer than the difference in time-scale between the last generation of market makers and the new generation of HFT market makers, this looks like a classic case of the croupiers on Wall Street taking another cut from the public.

But the argument is not so simple. A key empirical question is whether, in fact, the bid-ask spread has narrowed as a result of HFT. If so, then over a long-enough period of time, it may be that the social benefits of a narrower spread make up for the costs of investing in HFT.

A big picture issue is that the frequency of trading is dependent upon what sorts of information and analysis are done by the trader. If you're going to be day trading, then you ought to have access to HFT technology. If you're buying on fundamentals, then from an IRR perspective, whether you have HFT technology at your disposal will matter only when you're moving around a significant number of the total outstanding shares in a company.

Utility is Not a Monotonic Function

From Gretchen Rubin's Happiness blog, interviewee Karen Leland offers the following thoughts about happiness:

[I]t's not a constant condition, and it's not supposed to be. The amount of happiness I experience ebbs and flows and that's ok. Sometimes I'm super-joyful, sometimes content and sometimes down. It's a cycle, and it all changes.

Sorry economic theorists, homotheticity is an artifact of large averages.

Remembering Douglas McGregor

From the Economist:

Close to Abraham Maslow, and greatly influenced by him, McGregor became a significant counter to the thinking and influence of scientific management. His central idea is that there are two fundamentally different styles of management. One of them he called Theory X and the other Theory Y (see article). Theory X is authoritarian, assuming that individuals only ever work reluctantly. Theory Y is liberating and assumes that people will do almost anything if they are committed to the overall goals of their organisation.

Resonance and Neural Networks

A demonstration courtesy of Bobby McFerrin:

Via Cosmic Variance. Don't miss the earlier post (and linked PDF) on music and quantum mechanics here.

What is Wrong With Technology Transfer Office Culture?

Jon Sandelin from Stanford University's Office of Technology Licensing published an article in the Summer 2009 issue of an AUTM journal called University-Industry Relationships: Potential Risks. Perhaps unsurprisingly, the article is gated and available only to members. Already in the title you can see where Sandelin comes out on the idea of having more commercial ties with universities. One of the messages repeated on this blog over the past year has been that feedback loops promote innovation. The feedback loops between universities and industry are perhaps the most difficult to forge and maintain of any in our innovation pipeline. We should be promoting these feedback loops aggressively. Unfortunately, the tentative, preening, and antiseptic tone of this article is all too characteristic of tech transfer culture inside top-tier research universities.

Sandelin does a good job listing some of the benefits of tech transfer. But consider the "summary of risks" he comes up with:

1. That patenting and licensing by universities may inhibit rather than promote the progress of science and production of innovation
2. Of a loss of public trust in the university and/or its employees
3. Of unfulfilled commitments to research sponsors, students, or the university
4. Of bias when reporting research results or not reporting research findings that would be adverse to the interests of an industry patron
5. Of exploiting the work of students to benefit personal interests of their supervising professor
6. Of adverse and embarrassing reports in the media, whether actual or perceived, that affect the reputation of the university
7. That new discoveries made by university employees are not reported to the university or to a federal funding agency as invention disclosures, but are instead diverted to a company in which the employee has a financial interest

That's it. Wait. That's it?! Of these, only 4 is what I would consider an actual risk to the university. Look at the other six items on this list more carefully. What is really there?

First off, what on earth can he mean by one? If one is true, then why are we even bothering? The tech transfer experiment has been a wild success. As economist Kenneth Arrow noted recently, some of the best work results when academics are asked to work on a problem they've never thought about before. Tech transfer relationships work because universities get data from industry that is as valuable to academics as the theory that industry gets from universities.

Two just shows how little conviction Mr. Sandelin has in the fact that he is doing something important and beneficial for the university and its employees. Why would these people not trust the university if it is doing things that benefit society at large by cooperating and collaborating with private companies? Does he believe making money is inherently evil? If so, why not come right out and say that instead?

Three strikes me as very strange. Isn't the possibility of unfulfilled commitments to research sponsors a risk for the research sponsors? How is that a risk for the university? Similarly, why would students see more industry relationships as a risk? Students need jobs after they graduate, and somebody has to provide work.

Five would be hilarious if it weren't sad because it demonstrates how big a problem negotiating ownership rights is when it isn't done properly upfront. Universities love to ask graduate students to sign a thick contract when they start that gives away all of their rights. Most grad students, of course, never read the fine print and only find out how badly they've been taken advantage of later when somebody makes millions on their blood, sweat, and tears.

Six also makes me wonder. That's not a risk of relationships with industry. That's a risk of dysfunctional relationships with industry. Why would that be a problem for a university like Stanford, I wonder?

So of these seven risks, it is only four, the risk of bias caused by taking money from a particular group, that strikes me as very serious. But that risk is a risk for any institution, public or private, for-profit or not-for-profit. There's nothing really more difficult or challenging about solving that problem at a university. In fact, it's probably easier to solve that problem at universities, where most academics prize their professional reputations far above any particular grant money. Let the researchers themselves be the ones to decide whether it's worth risking their reputation on taking funding from some large corporation. Then just make sure that everybody can lookup and find out from whom researchers are getting their support. That's how we do things in this country.

It's very frustrating to see how backwards the thinking is at what is considered one of the best technology transfer offices in the world.

Conor Clarke Interviews Kenneth Arrow

At his Atlantic Correspondent's blog:

All these things change the economy and the economy changes itself. More capital changes how you supply goods, and this feeds back on investment. It's a complicated set of reactions and the equilibrium picture creates a favorable and smooth picture and, seemingly, more or less in balance. The trouble is that -- while it is a very important that things do balance and respond to fundamental changes -- we also are accustomed to the fact that things don't balance and that things will go array. In the medieval ages, things fluctuated -- but that was due to war. Our market cycles were due to the weather or wars or clinical circumstances, diseases and so forth. People got impoverished if soldiers were fighting in their territory. But things that happen under capitalism -- which was observed fairly early, maybe in the late 18th century -- well, those fluctuations are not because of outside influences but due to the market itself.

Quick Illustration of Rotational Symmetry

From the Built on Facts blog:

Why do mirrors reflect right and left, but not up and down?

After a conversation with a friend over the weekend about this, it occurred to me that this is actually a pretty good way to illustrate how broken symmetries may be hard to spot. You can click through to read the answer in the comments at Built on Facts.

As my friend pointed out, there is also a neurological component to this explanation. We know that our brains are pretty good at inversion -- the lens in our eyes is an inversion center, but we don't see everything upside down and backward. So why don't our brains simply undo the effects of a reflection in a mirror?

The answer is that they can. If you spend enough time studying organic chemistry, for example, you get pretty darn good at distinguishing right from left-handed symmetry. And when you look in a mirror, what you're seeing is actually your enantiomer. The trick is that most of us aren't a close enough study of our appearance to immediately notice the change in handedness. Most of the time, we assume we are looking at a 180 degree rotation of ourselves.

But when we see the reflection of an object without rotational symmetry -- such as English text -- our brain's rotation strategy runs into a snag. We read text from left to right and from top to bottom -- i.e., with z axis pointing out of the page. In a mirror, the same text reads from left to right and from top to bottom, but with z-axis pointing into the page. There's no rotation that will get you into that space.

Huh? Why would the Efficient Market ignore synergies?

More very strange analysis from Fama and French:

Firms often pay a substantial premium to the market price when making acquisitions. Does their willingness to pay a premium suggest the shares of target firms were mispriced?

EFF: The empirical evidence says that all the gains from mergers are eaten up in the premiums paid to acquire firms. On average, the acquiring firm gets nothing. This doesn't necessarily imply that the shares of the acquired firm were mispriced since there can be synergies (real business gains) from mergers.

KRF: Takeover premiums do not imply that the target firms were mispriced. Since we do not expect the market to accurately forecast every acquisition that will create value, we should not be surprised that prices rise when tender offers and mergers are announced.

Either the price is right or it ain't, right? Why would "synergies" matter if not to price?

Firms are subsystems embedded in a larger economic ecosystem. Synergies do matter. Beyond certain thresholds, otherwise linear correlations can go nonlinear, with concomitant consequences for growth or decay. But F&F are equivocating here. If synergies matter, then why wouldn't they be reflected in pre-announcement price? Shouldn't "the efficient market" be able to price in the probability of a merger and its resulting synergies?

As usual, a close look at the temporal dynamics suggests problems with EMH.

Neuroaesthetics

From Jonah Lerner at The Frontal Cortex:

Mark Rothko painting might be nothing but perplexed neurons in the V4 area of the visual cortex, or abstract art might be nothing but the peak shift effect. That, I think, is reckless hyperbole. The beauty of art is that it needs to be explained at multiple levels, from the action potential of retinal photoreceptors to the cultural shifts of 19th century France. Each of these descriptions is valid and important and essential. There is no privileged kind of discourse when it comes to understanding why we stare at Pollock's colorful drips of paint, or Cezanne's mostly empty watercolors. What intrigues me about neuroaesthetics is that it's another (and mostly novel) way to understand art.* But that doesn't mean it's the only way.

The senstivity of a set of symbolic rules and procedures to the context in which they are communicated could be described as a continuum from thin to thick -- i.e., from mathematical equations that are contextually invariant to English, for example, which can express multiple nontrivial messages to different (or even the same) audience simultaneously. There is a tradeoff between economy of information and adaptability with context.

Why I love Paul Graham

Check out his latest essay here.

But there's another way of using time that's common among people who make things, like programmers and writers. They generally prefer to use time in units of half a day at least. You can't write or program well in units of an hour. That's barely enough time to get started.

When you're operating on the maker's schedule, meetings are a disaster. A single meeting can blow a whole afternoon, by breaking it into two pieces each too small to do anything hard in. Plus you have to remember to go to the meeting.

The humor and sincerity of his essays is rare.

Another Reason Why Regulators Should We Looking at the Frequency Spectrum

From Zero Hedge via Abnormal Returns:

The three HFT horsemen are C, BAC and CIT. These three stocks traded 860 million shares today which is 10% of all US Equity volume. Think about that: 3 stocks in a universe of over 5000 U.S. stocks represented 10% of the volume. How could this be? Look at the intraday chart of all three of these stocks and you will see a something in common: an early morning move followed by a flatline with a very tight range (around .05). Meanwhile, while these stocks were flatlining the market was heading higher. The S&P 500 gained around 10 points in the afternoon (or 1%) but these 3 stocks did not move. There was a constant bid to these stocks yet anytime they wanted to lift there seemed to be a constant offer just a few pennies higher. This is what HFT looks like. The HFT’s made a killing in these 3 names today – in addition to the .01-.02 spread, they collected about .005/share in liquidity rebates. Not a bad day for a supercomputer.

The linked discussion explains how this is illegal "churning" or "painting the tape" under current regulations. The anomalies that signal this kind of trading are more easily observed when you look at the frequency spectrum of buying and selling, but very difficult to see looking only at time series.

Joseph Stiglitz on Sustainable Capitalism

From Adbusters:

A healthy economy involves using our time efficiently and getting enjoyment out of our time. Spending two hours commuting is not a good use of anybody’s time. There are many ways in which we are very inefficient. We have not thought through efficient land management. I was in a meeting recently in France where in the central city they were talking about how to redesign the whole city to make it environmentally more efficient, to make sure there is less waste, that the energy that is put out is captured and used and reused. So there are lots of things we can do to increase our overall efficiency.

I couldn't have said it better myself:

Creative capitalism can stand for the idea of a capitalism that respects and promotes profit that is sustainable in view of the rhythms of life. Both profit and time can be measured quantitatively. By building institutions that measure and are accountable for how they handle both, we can build better institutions.

As resource constraints become more important per capita, the measuring and managing of the frequency spectrum of human activities over time and space must become more important.

Hayek vs. Keynes Round 42

Posner takes sides with Keynes in considering the need for additional stimulus:

Their argument is that because government expenditures must be paid for one way or another, a dollar of deficit spending subtracts a dollar from private investment, and so there is no net increase in output. The argument is unconvincing. If private demand falls, investment geared to production of goods and services for private consumption will fall. People's savings (other than cash savings) will be invested, but in assets such as Treasury securities and money-market accounts that do not generate productive activity, or much such activity. Even investments in equities and commercial bonds have only an indirect, and often long-delayed, effect on production.

Hayek had the more sophisticated understanding of both micro and macro. His shortcoming was in finding a rigorous quantitative foundation -- a shortcoming of Keynes's theories also. The explanation for why Keynes is in ascendance now is simply that his is seen as the alternative to laisse-faire attitudes that prevailed under Reagan, Bush, Clinton, and Bush.

Hayek might say that these effects can be understood as a result of the heterogeneous structure of capital. What Hayek lacked was a rigorous quantitative method for analyzing such heterogeneities.

One possibility for introducing a more rigorous Hayekian theory of capital is to analyze capital in terms of liquidity -- i.e., the amount of time that it takes for a given quantity of cash to turnover. Thus, advocates of spending have a point in that the liquidity in government capital is right now much higher than private liquidity. But their conservative critics have a point in that at some piont that trend is likely to reverse, and when it does inflation is going to take off.

Either way, the EMH folks have no theory for what's going on -- and neither do the Keynsians except for this vague notion of how "animal spirits" can cause liquidity characteristics to change over time.

A key here is to observe how the liquidity of different types of assets changes over time. And the method for observing such changes is to look at the distribution of how long, on average, each type of asset is held before being sold. Time and frequency are related quantities, but heterogeneities in liquidity aren't going to be obvious looking only at time averages. One needs to look at the frequency spectrum in liquidity.

Weighing in on the EMH Debate: Does Behavioral Analysis Resolve the Problems?

See comments from the Economist, DeLong, Yglesias, and Hansen.

The problem with EMH is with its interpretation of the principle of revealed preferences. Unfortunately, the same problematic interpretation often applies to behavioral critiques of EMH. Here's an excerpt from an article I have forthcoming in Intellectual Asset Management:

There are two catches to using preferences "revealed" by market prices to measure individual preferences. The first catch is that one has to watch over a period of time to see the preferences revealed, which means assuming that the preferences do not change during the period of observation. The second catch is that in practice, no large data sets have recorded the revealed preferences of individuals. Only aggregate data, such as consumer price indexes and average household spending over several decades, has been available. Taken together, these catches mean that empirical tests of the rational hypothesis take as a given that preferences do not change in time and that only information about the average preferences of a group is necessary to measure and predict individual preferences.

But preferences do change over time. New books are written, new paintings are painted, new inventions are conceived and reduced to practice. Moreover, no actual person may exist who embodies the average preferences of a large group. Especially if there are outliers, the average preferences of the group may be quite different from the preferences of most individuals within the group.

Unfortunately, many advocates of “behavioral economics” and “bounded rationality” seem to have made the same mistake as the EMH by interpreting the rational hypothesis as a hypothesis about individual behavior. Although it is true that individual behavior often deviates predictably from what might (mistakenly) be called “rational” given certain individual preferences, observations of individual psychology cannot usually provide a proper test of the rational hypothesis. In practice, it has been difficult to verify clear violations of the rational hypothesis. There is often an argument over whether what might be called irrational behavior results instead from rational preferences specific to a particular time and place. For example, although it might seem irrational for a group to demand higher payment for a good already owned than the same group would be willing to pay for the same good not owned, this asymmetry might be explained as rational in view of the consumer surplus in ownership for the group. Because the mechanism traditional economic theory uses to measure preferences is the observation of group behavior, arguments about whether the behavior of a particular group is rational or irrational can quickly devolve into circularity.

This is not to say, of course, that psychology offers no insight to economics. In fact it seems quite likely now that evolutionary psychology and neurology will offer insights into the origins and explanation of observed group behavior. Such insights are not as relevant, however, to the problem of measuring and managing large groups over long periods of time. Systems theory takes a different approach to rehabilitating economic theory.

So the answer is not really. Theories of psychology are very useful and important for business people and leaders in general. But they are not the kind of theories designed to address large-scale, long-term behavior of groups. This is what economics and rational expectations theory has done for the past few decades. It has failed us because behavior that was once uncorrelated, and hence gaussian, has become more interdependent, and hence fat-tailed.

The way forward for us is to recognize that rational expectations are correct only at certain limits, namely, of ergodicity and uniformity in individual preferences. Rational expectations theory is a mean-field approximation. But when we have more granular data about individual dynamics, there's no reason for us to be content with mean-field approximations. Micro and macro theorists need to build nonequilibrium statistical models that are capable of producing both the gaussian and the fat-tailed dynamics that are observable in real markets. Systems theory represents the set of mathematical models that are most narrowly tailored to this goal.

Anachronism of the Day

In any event, positive-feedback trading is likely to increase volatility substantially. If one wants to design regulatory interventions that will decrease volatility, one must think about measures that will discourage positive-feedback trading rather than negative-feedback trading. Positive-feedback trading is substantially discouraged when traders using that strategy suffer massive losses, which is what one observed after the crash. Everyone who had been pursuing positive-feedback strategies bought more and more as the market went higher and higher, thinking that their portfolio insurance would enable them to get out. They were wrong. It's clear that the crash reduced volatility by reducing the attractiveness of positive-feedback trading.

That's Larry Summers writing in... 1988. Seems to me like he was ahead of the game while his physics training was still fresh in his head. Found via abnormal returns.

The Topology of Knowledge

From Joho the blog:

In the Age of Links, we still use credentials and rely on authorities. Those are indispensible ways of scaling knowledge, that is, letting us know more than any one of us could authenticate on our own. But, increasingly, credentials and authority work best for vouchsafing commoditized knowledge, the stuff that’s settled and not worth arguing about. At the edges of knowledge — in the analysis and contextualization that journalists nowadays tell us is their real value — we want, need, can have, and expect transparency. Transparency puts within the report itself a way for us to see what assumptions and values may have shaped it, and lets us see the arguments that the report resolved one way and not another. Transparency — the embedded ability to see through the published draft — often gives us more reason to believe a report than the claim of objectivity did.

Consider the following possibility: Maybe transparency was objectivity all along, but it simply took much, much longer for feedback loops in analog social networks to discredit overreaching authorities than it does in digital social networks.

A corollary is that credentials and authority aren't going anywhere. Their relative importance in the offline world just went up precipitously at the same time that it declined precipitously in the online world.

What do Music and Quantum Mechanics Have in Common?

Time and frequency are a Fourier pair:

The key to using music to teach modern physics, in my mind, is harmonic analysis. Harmonic analysis is nothing other than Fourier analysis, a tool which is highly valued in physics and engineering. It is not widely known by the non-scientist, yet it is easy to explain in the musical context—when someone looks at a graphic equalizer on their stereo they are looking at a real-time Fourier amplitude analysis of the music that is being played. One can explain how the synthesis of harmonics affects the timbre of musical sound—how the coefficients in a Fourier series can describe different real functions. A very simple example is the comparison between the organ pipe and the piano string. The ‘stopped’ organ pipe has only odd-numbered harmonics and the piano has all harmonics. (Because the ‘stopped’ organ pipe has a pressure node at one end and a pressure antinode at the other, whereas a string has nodes at both ends.) The different symmetry of the boundary conditions accounts for a major aspect of the difference in the timbre of the organ and the piano.

That's from The birth of the blues: how physics underlies music by J.M. Gibson. Via Physics and Physicists

If you're a regular Broken Symmetry reader, then you should know already that it is not only music that can be understood better with Fourier Analysis, but any time-series that can be decomposed into ocillations of different frequency, including cash-flows. The balance sheet is sort of like the graphic equalizer, except that the frequency of the accounts is not rigorously ordered in terms of liquidity. If it were, then the analogy would be complete.

Goldratt, Lean, Flow, and Financial Statements

Over at Evolving Excellence, Bill Waddell writes about how Lean Theory and Eli Goldratt's Theory of Constraints are part and parcel:

That focus on flow is at the very heart of excellent manufacturing - not merely finding tidbits of waste and eliminating it. The final step in the logical thought progression is that the most fertile ground in the effort to accelerate the flow of products across the fixed costs within the value stream is to know what is limitingthe flow - and that is where Eli Goldratt comes in. He said that an hour saved at the bottleneck (constraint) is an hour saved for the system (in lean terms, an hour saved for everything within the value stream). An hour saved anywhere else is a mirage.

Both theories focus on the frequency spectrum of activities within the firm rather than a time-averaged picture of costs. That's why lean is such a pain for cost accounting, which is based on time-averaged measurement of costs.

As mentioned in an earlier post here, what Goldratt calls "throughput" could also be called flow. Both are quantities per unit time.

If balance sheets included frequency-averages (i.e., turnover rates) for each account, would accountants be able to move assets or liabilities on and off the accounts without there being a trace on the financial statements? Right now, an asset moved on and off the balance sheet betwen the period of financial statements may not show up in the income statement or cashflow. These are time-average pictures of income and cash, and by definition an asset moved on and off within the period of time produces no net effect on the time-average.

We have blinded ourselves by excluding information about flow from our financial statements.

How the University of California Could Make Up for the $800 Million Budget Cut

As an alumni of UCSD, I am dismayed to see this letter circulating, which comes across as some of the most ungrateful whining that I have heard in a long time. Of all of the people and institutions that have been hurt by this recession, I do not think that academics or students are among the most hurt. And of all the institutions that are truly suffering as a result of the crisis, I do not think that the University of California, much less its most prestigious schools, are among the most hurt. So what's with the swipe at the younger sister schools? The faculty from UCSD, in particular, ought to be ashamed of themselves. Isn't this exactly the attitude they've been fighting at UCLA and UC Berkeley over the last few decades?

As one of the few people who might have a broad enough perspective to weigh in on the economic and political viability of their proposals, I feel an obligation to speak out with my opinion. Putting aside the whining and sibling rivalry, there are a few proposals in the letter that I agree with, and a few that I disagree with. Further, there is a proposal not in the letter that would potentially resolve all of the problems here and do even more to improve UC's relative position with respect to private institutions, which are its main competition.

• Out-of-State Enrollment:
This is a wonderful idea. Having a more geographically diverse student body has provided Stanford, for example, a competitive edge over UC Berkeley for many decades. So the charter won't allow us to imitate Stanford in this regard. Maybe we don't want to go to that extreme anyway. But enrolling more out-of-state students over the short-run would at least be an interesting experiment as well as a source of additional revenue. This should be a no-brainer.
• Generate More Data:
This is the kind of idea you get when you ask academics -- especially from the natural sciences -- to make policy proposals. Sure more data would be great. But it's going to take time and money to generate it, and there are things that could be done now, today, with the information that is already available.
• Redistribute Funds from Weaker Siblings to Stronger Siblings:
Bad idea on so many levels. First, the strength of UC compared with other institutions has been its ecosystem of multiple campuses. Maybe redistributing funds to fostering closer ties among the campuses would be in order, but cutting off the newer campuses while they're still in their infancy would be like pulling the plug on the LHC right before it goes operational. How do scientists, who are always talking about how basic science has long time horizons and needs stable funding, not get this point? How can professors from UCSD try to cut off funding from UC Merced because it's new? Some people at UCSD were part of the founding group of professors there. Where is their shame? If opening UC Merced was a good idea last year, it's a good idea this year. Everybody has to share the burden of budget cuts, nobody deserves to be singled out this way. How dysfunctional.

Now for the creative solution: Technology Transfer. IBM spent $5 billion a year on R&D every year for a decade and managed to squeeze out about $1 billion a year in technology licensing revenue over the same period. That's 20%. What's UC seeing from its Technology Transfer Office right now? Maybe 2%.

Why so low? The answer is because tech transfer is being done by salaried employees who will never be as aggressive or work as hard to make the connections and close the deals that are necessary to make these complex, multilateral negotiations work.

Last year, I made a pitch to a person with strong UC affiliation to startup a private equity fund to do technology transfer with top-tier universities like UC. No dice. The sense is that this would have an adverse effect on university culture. Really? Did AT&T Bell Labs have an adverse effect on Shannon or Mandelbrot? Did IBM's ARC have an adverse effect on Don Eigler or W.E. Moerner?

If UC wants a positive way to deal with its budget crisis, then the best way would be to embrace the rest of the economy, settle its internal squabbling, and start building on its strength -- which is turning out some of the most creative and brilliant artists, authors, and inventors in the world.