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“Likes” defeat better decision-making

Facebook is making many  people miserable, and that tells us a lot.  The Atlantic asked “Have Smartphones destroyed a Generation?” a few weeks ago.  One way to see the problem is social media is making people much more anxious to fit in with the herd, because peripheral status is so much more visible.  Pursuit of “Likes” substitute short-term immediate social popularity for developing your own path in any depth. That usually requires an ability to defer immediate gratification, gumption and often an ability to resist conventional expectations – the exact opposite of ephermal triumphs on social media.

That means it’s all very well to think about cognitive bias and Bayesian probability models and expected utility, as conventional policymaking does. But most people most of the time mainly care about how they fit in with other people, which is why a billion people are on Facebook and very few study statistics or Kolmogorov criteria. “Bias” thinking is mostly irrelevant to this pattern.

Indeed, one prominent scientific view argues that humans evolved larger brains in the first place to manage all the complexities of small group dynamics. We’re wired to think about status and reputation and pecking order,  in-groups and alliances, who gets credit and blame, and who is ostracized or ignored.  That, and cat videos, it seems.

There’s also some evidence that human culture has evolved to make us prone to imitate those with current high status in the group. For most people for most of slow-moving history, imitation  and “liking” the correct things has been a better survival strategy than uncertain adaptation or change.

Social media as human catnip

Social media is all about these deep social instincts. Getting “likes” on Facebook is a very shallow reward, but it is instantaneously visible and quantified. It’s like catnip to our inbuilt mental software. Not getting validation from the peer group can make people disproportionately miserable.  Similarly, Twitter has frequently deteriorated into hostile shaming and tweetstorms, making people fearful about saying anything at all.

There are strong forces in small group dynamics which push towards conventional thinking to please the groups’ vision of itself. Saying “we’re great” is guaranteed to get likes. Trying to divert attention to things that might rock the boat doesn’t attract many thumbs up.  People instinctively resist things that don’t validate the group, and try to enforce conformity with group norms.

Groups also tend to become small and exclusive and inert, however. They have an inherent tendency become maladaptive and mediocre because they validate conventions instead of adaptation. They tend to become fixated on internal alliances and factions rather than adapting to change.  Indeed, once a company or organization grows past a very small size, much of its energy starts to get absorbed by internal bickering, protecting existing territory, rivalry and gossip. People have a remarkable ability to fragment into competing small factions.

Stronger tools need to resist “like-“ability

Trying to impose a rational, neutral, dispassionate point of view has been the main way leaders have tried to cope with the fractiousness of our inbuilt software. But it usually does not work for long, as groups learn to express their factional interests in terms of universalistic language and high-minded ideas. People pay lip service to principles and go back to Twitter wars or ostracism campaigns. Indeed, it is gradually becoming apparent just how little durable success the social sciences have had in changing how people think and behave.

One of the only ways to do it is to pinpoint a few things in specific situation that don’t fit with the “”liked”conventional view   and get people to try to pay occasional attention to those few limited anomalies, like grit in an oyster that can become a pearl. I call them “markers.”

 

2017-09-05T08:39:31+00:00 September 5, 2017|Adaptation, Decisions, Uncategorized|

Faction as the “the mortal disease” of Democracy

The media, as usual, are missing the point. Like a set of nested Russian dolls, it’s still not clear how far the Russia scandal afflicting the Trump administration will go. But regardless of eventual outcome, it is dominating media and political attention to the exclusion of almost everything else in Washington.

If you’re a Trump supporter, of course the Russia allegations are a witch hunt and an outrage. If you’re a Democrat, they are a courageous attempt to stop the integrity of democracy itself being undermined by hostile foreign powers. But Democrats also saw the Clinton e-mail scandal as a ridiculous witch-hunt. Republicans saw it as a fundamental issue of character and fitness for leadership.

It doesn’t mean scandals shouldn’t be investigated. The real issue is how much attention the media obsession with political scandal drains from other issues. As Walter Russell Mead argues,

For both the Left and the Right, the ever-Trumpers and the never-Trumpers, the scandal is a bright shiny object that distracts. Our national house is on fire, and we are all focused on a particularly challenging level of a hot new video game.

Scandals  are a symptom of factionalism.  The Founding Fathers were acutely aware of its dangers, as Madison explained in The Federalist No. 10 in November 1787.

AMONG the numerous advantages promised by a well-constructed Union, none deserves to be more accurately developed than its tendency to break and control the violence of faction. The friend of popular governments never finds himself so much alarmed for their character and fate, as when he contemplates their propensity to this dangerous vice. … The instability, injustice, and confusion introduced into the public councils, have, in truth, been the mortal diseases under which popular governments have everywhere perished;

There was no way to avoid faction, Madison argued. “Liberty is to faction what air is to fire, an aliment without which it instantly expires.” However, he hoped it would be contained by having a (small-r) “republican” form of government, with decisions delegated to those with fit character (such as himself,) instead of pure democracy, Factionalism would also be diluted by the larger Union.

The trouble is the contemporary Washington scene is a small, tightly-knit interpenetrating network of elites who are notoriously often surprised by the world outside the beltway.

Factionalism isn’t diluted, it’s concentrated inside the Beltway.  Professional politicians and interest groups live and die by factional outrage.  Media coverage tends to turbocharge partisan and factional feelings.

The Madisonian fixes no longer work. And worst of all, instead of factionalism being driven primarily by disputes over income distribution, as Madison believed, they are increasingly a matter of divisive identity and racial groupings.

So we need different checks and balances that dilute factionalism. We need a better error correction loop, based more on recognizing when something is not working. I’ll come back to this.

 

 

2017-07-17T13:39:55+00:00 July 17, 2017|Decisions, Politics|

Abstract Principles Lead to Failure

Fixation on universal timeless principles necessarily has a tendency to produce catastrophe, because people become desensitized to exceptions, problems, flaws and change.

Take the current plight of the left in the US, for example, full of outrage against alleged Russian ties to Trump – but out of power. Conor Friedersdorf  recalled Richard Rorty’s 1998 book on what was wrong with the left in the Atlantic the other day: According to Rorty (who himself was a very leftish postmodern philosopher, of course,)

The contemporary academic Left seems to think that the higher your level of abstraction, the more subversive of the established order you can be. The more sweeping and novel your conceptual apparatus, the more radical your critique…

Recent attempts to subvert social institutions by problematizing concepts have produced a few very good books. They have also produced many thousands of books which represent scholastic philosophizing at its worst. The authors of these purportedly “subversive” books honestly believe that they are serving human liberty. But it is almost impossible to clamber back down from their books to a level of abstraction on which one might discuss the merits of a law, a treaty, a candidate, or a political strategy.

This is a style of thinking you can watch for, and it doesn’t just afflict the left.  It also helps explain the excessive faith in markets and deregulation that helped produce the 2008 collapse.

One cure is to ask the question “how would you test that assumption?”, followed by “what are the limits, boundary conditions or exceptions?”  A deeper cure is you need an entirely different mindset.

2017-07-11T14:58:55+00:00 July 11, 2017|Adaptation, Politics|

A Weakness in Artificial Intelligence

Here’s an interesting paradox. Expertise is mostly about better mental representation, say Ericsson and Pool in the book I was discussing earlier.

What sets expert performers apart from everyone else is the quality and quantity of their mental representations. Through years of practice, they develop highly complex and sophisticated representations of the various situations they are likely to encounter in their fields – such as the vast number of arrangements of chess pieces that can appear during games.  These representations allow them to make faster, more accurate decisions and respond more quickly and effectively in a given situation. This, more than anything else, explains the difference in performance between novices and experts.

This is an extension of Newell and Simon’s concept of chunks, which I talked  about before here.  (Ericsson worked with Simon at one point.)

Importantly, such representations are not at all the same as the parsimonious mathematical models beloved by economists, either. An expert may know tens of thousands of specific chunks in their field. But we still often know very little about exactly what that means, or how it works.

Now consider what this means for artificial intelligence.  AI mostly abandoned attempts to develop better mental representations decades ago.  Marvin Minsky of MIT advocated “frames” in 1974, but didn’t follow up with working systems.   To be sure, the 1980s era expert systems had many  simpler “if-then” type encoded rules, but faltered in practice. And today there is a great deal of attention to semantic networks to represent knowledge about the world. One example is DBpedia, which tries to present wikipedia in machine-readable form. A company called Cyc has been trying to hard-code information about the world into a semantic network for twenty years.

But semantic networks are flat and relatively uncomplicated. They are simple webs: graphs and links without much emergent structure.  As for vector models for things like machine language  translation, there’s almost no representation at all. It’s a brute force correlation, reliant on massive amounts of data. Recent advances in machine learning owe nothing to better representations. Chess programs effectively prune search trees efficiently, rather than use representations.

Meanwhile, the main data structures in  machine learning, like ndarrays in the Python Numpy scientific module, or Dataframes in the Pandas module which is commonly used by data scientists, are essentially glorified tables or spreadsheets with better indices. They are not sophisticated at all.

So the most important thing in expertise is something that researchers struggle to reproduce or understand, despite all the hype about machine learning.  Correlation is not the same thing as representation or framing or chunks. That’s not to say AI can’t make much more progress in this area. But there’s an enormous gap here.

Future advances are likely to come from better kinds of data structures.  There’s little sign of that so far.

2017-06-23T09:56:14+00:00 June 23, 2017|Expertise, Quants and Models|

When to dump a leader (Pelosi edition)

Many “leaders” have a tendency to  think that they ought to keep doing the same thing, but with more “passion,” or intensity, or resources. As I said in the post below, however, optimizing is not the same as adapting to a changed situation. There are many situations in which more persistence and determination just get you more trapped in doing the wrong thing. It’s essential tor recognize them. Most people don’t.

The unfortunate consequence is that change then requires a change in leadership as well. Maybe the Democratic Party is realizing that after multiple defeats: “Pelosi’s Democratic Critics Plot to Replace Her.” If things are persistently not working, try someone with a fresh look.

That also means that if you’re a leader it’s better to look for ways to adapt or change your mind before people plot to remove you after a massive setback.  The oldest danger of leadership is woodenheadedness. Yet most leaders hire consultants to put a theoretical or quantitative veneer on what they already think.

2017-06-22T15:33:53+00:00 June 23, 2017|Adaptation, Decisions, Human Error, Organizational Culture and Learning|

Two very different kinds of expertise

Faith in experts has been faltering, as populists attack many established political and academic elites. So it is more important than ever to recognize genuine expertise. The trouble is that is often hard to do, despite how credentials are so important in most areas.

Many studies of expertise don’t help that much. Take Anders Ericcson’s new book, Peak: Secrets from the New Science of Expertise. Ericsson is best known for his interesting research into “deliberate practice.” Malcolm Gladwell popularized the idea by talking about “ten thousand hours”  necessary to pick up any advanced skill, but Ericsson is adamant that the kind of hours matter just as much as the amount. Experience alone is not going to improve your skills unless you push yourself outside your comfort zone, he says.  It’s all interesting stuff, and it’s worth reading.

The trouble is this approach applies almost entirely to fields where knowledge is cumulative, and where there are established teachers and teaching methods. You can practice similar situations over and over again. Examples include playing the piano or violin to a very advanced level,  and many games with set rules like chess, golf or soccer.

Most of the most important fields are not like this. As Ericsson notes in a brief aside,

What areas don’t qualify? Pretty much anything in which there is little or no direct competition, m such as gardening or other hobbies, and many of the jobs in today’s workplace – business manager, teacher, electrician, engineer, consultant and so on.  These are not areas where you are likely to find accumulated knowledge about deliberate practice, simply because there are no objective criteria for superior performance. (p98)

That excludes most of the main areas in which decision-making skill is required. But people have a tendency to ignore the boundary conditions for this kind of research, its limits of applicability.

There’s a deeper problem lurking here as well, if you think about it.  Those other fields are more difficult because the underlying factors that lead to success keep changing, partly because competition in them means people develop new techniques or approaches. What worked in selling computers in 1950 will not work so well now – but the skills required to be a top notch ballerina or violinist are almost the same. The rules of the game stay the same, even if competition grows more intense and training techniques alter over time.

The root of the issue is people generally confuse optimizing with adapting. They are not at all the same thing. Practicing the same skill over and over may optimize but it is much less likely to lead to adaptation.

Where does this leave us? Expertise in an existing field or game is not the same thing as dealing with changes in the rules of the game. That is a wholly different kind of problem.  Indeed, experts may be some of the last people to recognize that the rules are changing, as they have so much invested in existing interpretations. That explains why scientists rarely change their minds, but science slowly evolves without them.

Standard decision science, and most standard economics and economic policy, is about optimizing rather than adapting. But adaptation is necessary to success, and lack of adaptive skill is one reason why even the most credentialed experts often seem out of touch or wrong. To say so is not to deny expertise or science; instead it is to advocate a different kind of expertise and science.

There’s some other points to make, which I will come to shortly.

 

2017-06-22T15:12:35+00:00 June 22, 2017|Adaptation, Expertise|

Another strike against prediction and following formal rules

I was talking in the last post about how inappropriate and outdated some of the economics discussion about monetary policy has become, especially the whole debate about policy rules, credibility and commitment.  Nothing has been learned from the great crisis, and the field is mostly a dusty backwater twenty or thirty years behind most of the rest of the economy,

Idealized planning, prediction and forecasting had its heyday in the 1960s and 1970s in Western business (and before that the Soviet Union put its faith in planning.) It turned out to be a disaster. Formal forecasting didn’t work, and most such economists were shown the door in the private sector in the 1990s. But the approach is still going strong in economic policy, as if the clock stopped twenty years ago.

Here’s a contrast. Take the announcement that Amazon is buying Whole Foods yesterday. Amazon is, of course, wildly successful as a business. But Jeff Bezos does not try to forecast or predict. Instead, according to Farhad Manjoo in today’s NYT:

Yet if there’s one thing I’ve learned about Jeff Bezos, Amazon’s founder and chief executive, after years of watching Amazon, it’s that he doesn’t spend a lot of time predicting future possibilities. He is instead consumed with improving the present reality on the ground, especially as seen through a customer’s eyes. The other thing to know about Mr. Bezos is that he is a committed experimentalist. His main way of deciding what Amazon should do next is to try stuff out, see what works, and do more of that.

If you can’t reliably predict, then you have to think and act very differently.

2017-06-17T14:59:15+00:00 June 17, 2017|Adaptation, Central Banks, Economics, Federal Reserve, Forecasting|

Lack of Fresh Thinking among Academic Economists

The intellectual weakness of much recent thinking on monetary policy is very disappointing. Actually, to call it “recent” thinking is a distortion.  The debate seems stuck somewhere around 1996. Here’s John Taylor complaining about “post-panic” monetary policy at a Congressional hearing in March:

In many ways this whole period can be characterized as a deviation from the more rule- like, systematic, predictable, strategic and limited monetary policy that worked well in the 1980s and 1990s.

It’s as if the last ten years just went down the memory hole as an unfortunate aberration from elegant theory. He just doesn’t seem to occur to Taylor that the consequence of those policies was also massive asset bubbles, volatility and ultimately the most catastrophic financial crisis in seventy years.

That’s because the supposed benefits of policy rules come from oversimplifying the task that policymakers face. There may be a case for comparing policy decisions to a rule, but it elides into pretending that a policy rule can replace policy.

I don’t necessarily hold with the various unconventional monetary policy options that have been used since 2008, or believe that they were as effective as the Fed sometimes claims. However, policymakers had to improvise because nothing else worked. And they at least deserve some credit for that.

At best, the rules school can lead to an appropriate restraint about what policy can achieve. Give policymakers one simple thing to do and maybe they will at least achieve that. But it achieves that simplification by ignoring the interconnections and complexity of the actual economy.

This is much more than the usual discretion versus rules/ time consistency debate. If I had to summarize it in a sentence, I’d say look for balances, not principles or fixed goals.

2017-06-13T08:27:54+00:00 June 13, 2017|Central Banks, Economics, Federal Reserve, Monetary Policy|

Democracy works by suppressing hubris

Another election, another huge surprise. Teresa May’s historic electoral catastrophe last week was actually foreshadowed by plunging opinion polls this time, so the pollsters are not to blame for once. But the exit poll on Thursday night still came as a vast shock, as the scale of the collapse of Tory hopes became clear. Andrew Rawnsley of the Guardian blamed overconfidence and hubris for the disaster:

She conducted a campaign that combined vanity with incompetence and had learned nothing from the now myriad examples from around the democratic world of what happens when a politician behaves as if they are simply entitled to power.

There is something strangely magnificent in this episode beneath the shrieks and journalistic drama and personalities. Democracy is a messy, awkward, short-sighted system of governance. But it has a better error control loop than autocracy or bureaucratic planning.  Democracy is impatient with failure, as I noted before,  and fixes mistakes relatively quickly.  It may be terrible at long-term thinking and elegance, but it is good at throwing overconfident and arrogant planners out.

That is actually a good thing, and it means people are wrong to see all the turmoil of the last two years only as a departure from some idealized global liberal ideal, as a car crash on the way to utopia. The system is messily rebalancing in response to problems that had been ignored. Overconfident elites get punished, and underserved groups get an (occasional )voice.  The process not ideological. It happened to Progressives in the US last November. It just happened to Conservatives in the UK.   If would be worse if the system got stuck – and that may be the case in continental Europe.

 

 

 

2017-06-13T08:06:49+00:00 June 13, 2017|Europe, Politics|

How academics and practitioners think differently

Here is an excellent article at The American Interest on the differences between how policymakers and academics think about international relations in the US. Some of these differences carry very important implication for policy. In general, scholars have (not surprisingly) drifted away from practical concerns which limits their influence, author Hal Brands says.

International relations scholars—particularly political scientists—increasingly emphasize abstruse methodologies and write in impenetrable prose. The professionalization of the disciplines has pushed scholars to focus on filling trivial lacunae in the literature rather than on addressing real-world problems.

But practitioners and scholars also take very different positions on some substantive issues.  Practitioners are more concerned with American interests, while academics think more as “global citizens” or the stability of the system as a whole.  Interestingly, one particular point of difference is attitudes to credibility.

Since the early Cold War, U.S. policymakers have worried that if Washington fails to honor one commitment today, then adversaries and allies will doubt the sanctity of other commitments tomorrow. Such concerns have exerted a profound impact on U.S. policy; America fought major wars in Korea and Vietnam at least in part to avoid undermining the credibility of even more important guarantees in other parts of the globe. Conversely, most scholars argue credibility is a chimera; there is simply no observable connection between a country’s behavior in one crisis and what allies and adversaries expect it will do in the next.

This is clearly extremely important.  I have more sympathy with the scholars on this one: many of the worst policy errors have been caused by “domino theories” of credibility.

It is also interesting that there is a gap at all between practitioners and academics in foreign policy. In economic policy, the academics largely captured policy, certainly in the US, in the last two decades. That naturally carries with it a certain style of thinking – and the outcome has been anything but encouraging, with enormous financial crises and volatility.

2017-06-06T14:26:46+00:00 June 6, 2017|Decisions, Expertise, Foreign Policy|