A wrong diagnosis: our story 

‘What is the chance our child will be normal?’
‘Hmmm … a very low probability.”
             - conversation with Dr O.

Intense emotion often sears the memory with incidental details. Two years later, I can still remember every inch of Dr M.’s office. His chair sat under a window that had regal views over Hyde Park; his desk was an enormous, darkwood affair that contrasted with the compactness of the Mac computer that lived  on top of it. There was a large, garish piece of modern art on the right hand wall, showing a Picasso-esque mother holding a baby; a small bookshelf that held stacks of paper and a variety of medical supplies and gloves; and in the far corner of the room behind us, an adjustable bed and a small ultrasound machine with its display screen.

Dr M. was our obstetrician, and he had a reputation as one of Sydney’s best. His fees – a flat fee of a few thousands, and hundred dollars each for consultations that often took less than five minutes – seemed to confirm that. Like most first-time parents, we felt that we were doing the right thing by seeing him. By having a specialist of our choice involved in the pregnancy, we were offering our new child the best of medical care. We were vaguely aware of the alternative – going through the public health system and seeing whichever doctor happened to be free at the time – but as people with some disposable income, it seemed a no-brainer. We had the money so we would “go private” and see our own doctor.  

Dr M. used two offices, so that he could line up patients in quick succession and waste no time waiting in between appointments. Our consultations with him were usually quick and pleasant. A simple scan to check the growing baby, then general enquiries about my wife’s health and a promise to see us again in a few weeks. 

But in the fifth month of the pregnancy, something went wrong.

Arjun in the womb at 22 weeks

It all began with the 22-week scan, a standard, detailed ultrasound examination of the fetus that is now a routine part of prenatal care. While we were mesmerised and delighted by the pictures of our (literally) bouncing little baby boy, our sonographer seemed more circumspect. She waited until the very end of the examination to tell us that something had “not measured right”. We had noticed her using a computer cursor during the examination to measure different parts of the baby’s body – bone lengths, head circumference, size of organs and so on – but now we suddenly paid a lot more attention. What did she mean not “right”? What had she seen? Was there something wrong with our baby?

“It is probably best,” she told us as she ushered us out, “to see your doctor.”

We left the examination in a daze. We had tickets to the Caribbean the next day for a four-week holiday; we knew that there was no chance of us getting an appointment with Dr M. before that. As we drove home, our anxiety grew as we began to feed off each other’s apprehensions. What made it worse was not knowing any details. It seemed stupid that we had not asked the sonographer for more explanation, but it had not occurred to us at the time. The shock of hearing that all may not be well with the baby had temporarily paralyzed our thought processes. Now, by the time we had recovered from the initial shock, it was far too late. We couldn’t see our doctor, and it would be four weeks before we would next get a chance.

We flew to the Caribbean with a bittersweet taste in our mouths. We convinced each other that is was probably nothing, and that worrying would not get us anywhere. But  at the airport, we used international roaming on our mobile phone to call Dr M. There was no answer, and we left a message. Every new country where we disembarked, I would turn on the phone and watch the little screen in hope, waiting for a return message. In the plane, my wife’s little bump suddenly had a significance and a poignancy that it had not had before. 

Finally, in Miami, the message came. The baby’s long bones [arms and legs], Dr M. told us, were a little short. No big deal right now; come back next month and we would review it then.

It was enough, this little nugget of reassurance bounced to us on the other side of the world. We enjoyed our holiday in relative peace, reassuring each other that it was all a false alarm. We watched cricket, drank rum and lay on the beach. On a boat cruise, fellow tourists exclaimed at how small my wife was for a second-trimester pregnancy.  I told myself it meant nothing – she was a small girl anyway, so what did they expect? The sun was shining and all was well with the world. We lay at night in the tropical dark and pretended to each other that we weren’t thinking about it. 

But we were. And in a spare moment of weakness, I logged onto the Web at our resort and searched Google for “short long bones fetus” - and stumbled onto a chamber of horrors.

Skeletal dysplasias are abnormalities of bone growth that typically lead to what is commonly termed “dwarfism”. Although the most common and milder forms such as achondroplasia are often compatible with an active and long life, many of the more severe forms are very disabling and lead to death at or shortly after birth. It turns out that abnormally short long bones in the fetus are a prime prenatal marker for skeletal dysplasias. Everything I read pointed to the same conclusion: that these results at this stage of the pregnancy put our baby at real risk of having a form of skeletal dysplasia. As I scrolled through pages and pages of diagrams and graphs, research papers and photographs of crippled children, it really hit me for the first time that there was a possibility that my boy would be very visibly abnormal. That all the dreams I had about his first steps, playing cricket in the park and walking him to school would have to be shattered and rebuilt. That the future that once lay bright and undisturbed in front of us now bubbled with uncertainty and fear. 

We returned to Sydney, and went to see Dr M. as soon as we could get an appointment. I was relieved to see that he seemed unfussed. Google had not lied to me; there was a possibility of skeletal dysplasia, but at this stage it was nothing more than a suspicion, he told us. The only way to know was to follow the baby’s growth over the next few months. If his little arms and legs grew at a decent pace, we could be reassured that everything might be okay. If, however, we saw the growth dropping off the graph, then there was some cause for concern.

The  next few months were a  merry-go-round of medical appointments. There were bi-weekly meetings with Dr M., and ultrasounds scans both at his office and at the ultrasound center that did more detailed scans.  Time dulled our initial anxieties, and we went into a kind of holding pattern of hope and fear. Our appointments were as jovial as ever, but the banter was now forced. I watched the ultrasound screen with feigned disinterest, waiting for the new measurements to appear every week and mentally calculating the rate of growth as soon as it appeared. Our baby was reduced to points on a graph and a percentile reading on a growth chart. And though I tried to fight it, at nights I would sometimes pore over our ultrasound pictures and surf the Web for information, looking for reassurance but also afraid of what I might read.

Things came to a head in late July, just a month before our baby was due. Dr M. had danced around the truth for months, but now he told us straight out: our baby had a skeletal dysplasia, and he was referring us to a geneticist to start the process of “management”. The cubist art beside us now took on a sinister air; the doctor put on a professionally compassionate face; and in that moment our carefully constructed defences crashed down around us. In the waiting room as we paid our consultation bill, my wife wept openly and drew sympathetic stares. This was what we had desperately hoped to avoid. For the first time, we felt stripped bare and alone - and unprepared to face the future. 

My online research became obsessive. What might be the exact diagnosis, given the prenatal measurements that we had? What was the prognosis for our baby’s life? What was the chance that the diagnosis was false? I spent hours on the Web reading everything I could find, even spending money to get access to medical journal papers and specialist material. I began to read up about people with dwarfism and their lives and how they fared. I read about achondroplasia, the most common form of dwarfism, and the medical complications it could bring. I read the blogs of people with dwarfism and saw how normal they were, despite the many hurdles they faced. I looked up the American TV show “Little People, Big World” and laughed along with their stories. 

And meanwhile our little baby kicked and squirmed, ready to come into the world.

The appointment with the geneticist was the most nerve-wracking day of my life. His name was Dr O., and he was an expert in the field. He was the one, we thought, who would give us a definite diagnosis for our baby’s condition. I remember the fetal medicine department as being the darkest, shabbiest, most depressing part of the entire hospital. We sat in the waiting room surrounded by a sea of glum faces, each mother-to-be trying to guess why the others were there. The receptionist laughed and joked with her friends over the phone, oblivious to our private tragedies. Dr O., when he finally came to call us, turned out to be a small, obese man with close-cropped hair and womanly hands. His solicitious tone suggested that he was used to dealing with anxious parents. He ran the ultrasound monitor over my wife’s belly, and I watched with my heart in my throat. The examination couldn’t have taken more than a few minutes, but it felt like hours. My wife gave me a questioning look; I squeezed her hand for reassurance. When I couldn’t take it any longer, I asked Dr O. what he thought. He hummed and hawed and scrutinized the computer monitors.

 ‘It’s hard to say. There is definitely some kind of skeletal dysplasia. But I don’t think it is lethal.’

Oh, how I had hoped for a different reaction! A dismissive wave of the hand, perhaps – ‘Nothing to worry about!’. Or a puzzled look - ‘Why are you even here? He’s normal!’ Normal, normal – those were the words I had so wanted to hear. Instead - he didn’t think it was lethal! To hear that your baby will not die is not something that a parent should take lightly, but I hardly focussed on that. What Dr O. had told us was being measured against our expectations, not against any absolute reality. On our scale of possible outcomes, I could see both the best-case and worst-case scenarios slipping away. And those words – “definitely a skeletal dysplasia” … 

‘What is the chance he might still be normal?’ I asked. Dr O. furrowed his brow in reply, as if calculating the odds there and then.

‘Very low probability,’ he said.

Our baby would not be normal. I tried my best to internalize this new reality. A definite diagnosis would only be possible after birth, and we went home to wait it out. We told our families the news, and although they lived interstate we hid nothing from them. My parents tried to reassure us with anecdotes of short people in our family history; how so-and-so aunt or uncle had hardly reached five feet and still become a success. My father-in-law railed at the “know-nothing” doctors and their new-fangled machines. They all booked tickets and flew to Sydney to be with us. Like a lotus flower, our family closed itself protectively around us. 

And then in late August, our son arrived.

He was in a rush – it was a two-hour labour. Things progressed so fast that there was no time to hook up the monitoring equipment that Dr M. had recommended be used. Little Arjun appeared and was whisked off to have his lungs cleared. I was thrilled and thankful. Under the bright lights of the labour ward, I looked into his gorgeous blue and brown eyes and almost forgot all the dramas of the last few weeks. 

Almost - but not entirely. I couldn’t help but notice his limbs, which were short; but not unusually so. A little flame of hope that I had kept kindled inside burst alight. When Dr M. arrived he was, despite his thousand dollar fees, more than half an hour late.

‘What do you think?’ I asked him.

‘I think you have a healthy baby boy,’ he said – ‘enjoy him.’

We did. There were some minor complications over the next few weeks – many of them a result of over-officious medical care – but it gradually became clear that the prenatal diagnosis of skeletal dysplasia was wrong. Dr O. came for a look in Arjun’s second week. He held our baby at an arm’s length, inspecting him as dispassionately as a meat inspector at an abattoir. Nothing seemed obviously wrong, he admitted grudgingly. That’s as close as his kind would get, I suspected, to admitting he is wrong. 

In September we were finally discharged from hospital. Putting Arjun into the car for his first trip home brought with it an exquisite feeling of relief. It was as if by physically removing him from the hospital was to finally extricate him – and all of us – from an enormous machine that had held us all captive for so long.

I still believe that feeling was accurate, for that is what we had done.

We would have loved Arjun, no matter what shape his skeleton or how short his stature might have been. We know that now. But I won’t deny the stress, worry and fear that I went through with my wife as a result of his misdiagnosis. For those parents who go through the same thing with a less fortunate outcome, I can only express empathy and an infinite admiration. And the memory of our ordeal gives us a reason – as if we need yet another, in addition to the little man himself – to thank God for the gift that He has chosen us to receive.

Measuring the unborn child

At this point it is worthwhile going over Arjun’s diagnosis in some detail. Not because it is inherently interesting, but because it illustrates some general features of prenatal diagnosis which I believe are fundamentally flawed. Although this discussion is somewhat technical, it is important to go over the details to get a good understanding of what those flaws are.

Arjun’s diagnosis of skeletal dysplasia was based on what is called prenatal biometry. This basically means measuring the dimensions of a fetus’ body. Because the actual lengths of a baby’s body vary according to genetics and stature, measurements are plotted on a standardized curve and often expressed in terms of percentiles. Measurements that fall out of a “normal” range are used  as markers for particular conditions. Doctors also look for gross features, such as malformed bones or organs or certain fetal behaviours. A diagnosis is usually made on the basis of the aggregate of all this information; but in the case of skeletal dysplasias, biometric measurements make up the most important evidence in support of the diagnosis.

Let’s look at a specific example. In Arjun’s 22-week scan, his femur [thigh bone] measured 34.6 mm in length, while the “average” length for a 22-week old fetus is 38.0 mm (more on the calculation of “averages” later). This places Arjun at roughly the 3rd percentile, which means that he is in the bottom 3% of fetuses when ranked by femur length. It is this percentile ranking which is used as a metric rather than the actual measurement. Thus, although Arjun’s femur was only 3.4mm smaller than the “average”, his ranking in the bottom 3rd percentile immediately singled him out as being “of concern”. 

(Statistical note: 3rd percentile puts him almost two standard deviations below the mean (-2SD). Note that because the distributions are approximately normal, mean and median coincide in this case.) 

In general, this is the pattern followed by prenatal testing and diagnosis: if measurements fall sufficiently outside the “normal” range, that in itself is taken as prima facie evidence of a problem.

Once singled out, Arjun was measured at regular intervals throughout gestation and his femur length was plotted on a  graph. Over time, this created a “growth curve” for Arjun that could be compared to the “average” growth curve. Similar graphs were made for the length of the other “long bones” – the humerus [upper arm bone], radius/ulna [lower arm bones] and the tibia/fibia [lower leg bones].

Arjun’s femur length in utero compared to the 50th percentile “average” curve

On all these graphs, Arjun’s growth was below the average and dipped away as he approached birth. In the case of his femur, his measurements stayed below the 3rd percentile and even dropped to the 1st percentile at a later stage. Often, these growth curves are shown with a 95% interval around the mean which is deemed as the “normal” range. Arjun’s long bone measurements fell outside of “normal” strip. At birth, his femur was almost 10mm shorter than what it would be “expected” to be.

These were the graphs that Dr M. and Dr O. looked at. It is on the basis of these graphs that they made the diagnosis of an “unspecified skeletal dysplasia”. There were no other indications of bone deformities apparent. In a nutshell, they were saying: Arjun has a skeletal dysplasia because his long bones are too short for a “normal” baby.

Arjun’s diagnosis of skeletal dysplasia turned out to be wrong. But so what? False diagnoses happen all the time and are acknowledged to be a risk in any diagnostic procedure. In itself, the misdiagnosis may not have any significance at all. Medicine is an imperfect science. It may well have been “one of those things” and nothing more. 

But I don’t believe so. Arjun’s case in itself doesn’t matter, other than being a part of our personal history; but it is a good illustration of something fundamentally flawed in the way statistics are used in medicine. Remember, this was not a case of human error. Throughout the entire process, the doctors involved did not do anything “wrong” – they followed procedure. Any geneticist or obstetrician would have come to similar conclusions when looking at the evidence. 

Nothing “went” wrong. But something “is” wrong with the procedure itself. 

In the next few sections I will explore the two fundamental flaws in the system of prenatal diagnosis – and, more broadly, in much of medical science - that I believe are illustrated by our particular case. The first, relatively minor flaw is the misapplication of statistical testing: using the wrong data and not understanding the limitations of the testing itself. The second and deeper flaw is the mistake that permeates so much of medical science: the false analogy between people and numbers. 

What is “average”?

Growth curves are made by collecting data from a large number of people and then fitting a mathematical formula that best describes a “middle path” through all the data points. The sample of people used is drawn from a “population”. If a sample is large enough, it is assumed that repeating the sampling process on the same population will yield almost the same results. However, different populations can give very different results. And here lies the rub: the growth charts used during prenatal diagnosis are assumed to be universal, but they are not - they are specific to a particular population.

Take the femur length chart shown before. It is based on a sample of over 1000 fetuses taken from a primarily European and American population. Now, it may well be that European and American babies (majority Caucasian in race) measure the same as Indian babies; however it may well be that they don’t. At least anecdotally, Indians feel that their babies are smaller. Is it possible that some of the variation seen in Arjun’s case was due to racial factors?

It turns out to be surprisingly difficult to find out. Femur length charts from an Indian population are not available to me, so as an analogy we can look at the work of Shinozuka who has published  growth curves for Japanese populations. Shinozuka’s femur length chart is follows a significantly lower trajectory  than the  standard chart used in the West. His Japanese babies end up with femurs that are about 4.0 mm shorter than their Western counterparts. In fact, using Shinozuka’s chart Arjun’s measurements fall mostly within the normal range, although they are still well below the average. 

We don’t know if Indian populations are comparable to the Japanese, but it seems likely that they would be. If Arjun’s race had been taken into account, he probably would have been close enough to normal to have caused no concern.

Arjun’s femur length in utero compared to the Shinozuka data

Casting the net too wide

Diagnosis is in many ways a mechanical science - doctors often do no more than follow rules. When Dr M. referred Arjun to a geneticist with a suspicion of skeletal dysplasia, he was following a rule as faithfully as a computer program: look for femur length at or less than the 3rd percentile. By definition, about one in thirty fetuses will fall into this range. Although exact figures are hard to estimate, the birth prevalence of skeletal dysplasia is probably around 1 in 5,000. This means that of all the people who are “suspected” of having the condition, 99.4% of them will not have it!

It’s simple maths, but it makes you wonder. The usefulness of this prenatal marker must be compromised by the large number of people who are suspected without cause (“false positives”). On the other hand, almost all people with skeletal dysplasias do indeed have very short femurs in utero – less than the 3rd percentile. So the question is, should we test a lot of healthy babies for this condition to find the few who do indeed have it? 

In statistical parlance, these concepts have names: “specificity” and “sensitivity” . Specificity measures how good a particular test is at finding positives within a population without catching a whole lot of irrelevant guff. Sensitivity measures how good the test is at finding positives and not missing other positives that might be floating around. In fishing terms, you might say that a harpoon is highly specific but not sensitive, and that a trawler net is sensitive but not specific.

The prenatal procedures for detecting skeletal dysplasias are a trawler net; they have good sensitivity (most skeletal dysplasias will be caught this way) but very bad specificity (most babies who are suspected are free of the condition).  Large numbers of babies (and parents!) are scooped up and run through the mill of testing, but only a very few of them are actually found to have needed intervention. 

In my experience, the doctors involved in prenatal testing do not have a good understanding of these statistical concepts. They operate as if their testing procedures had both high sensitivity and high specificity. But testing involves a trade-off between these two measures, and usually both cannot be high. The truth is, almost all prenatal testing has good sensitivity but low specificity. They are often good at finding those babies with problems; but they also catch a lot of false positives and put a lot of parents through a lot of stress for nothing.  This is something that people know anecdotally, even if they do not understand the technical reason.

It’s not surprising that the medical profession is willing to sacrifice specificity for sensitivity. In this litigious age, the potential “cost” of a false negative is far greater than that of a false positive. The worst a parent like me is likely to do is write a long-winded article to vent my frustration. The parent of a baby who is declared normal but is then born abnormal, however, is far likelier to  take things a lot further. This is one reason the culture in diagnostic medicine in general has become one of extreme risk-aversion: 

“Let’s test the lot so we don’t miss anything; because if we do, we could be in for a lawsuit.”

And finally, an even more cynical observation. Low specificity in diagnosis leads to a lot of healthy babies (or patients) being put through a lot of tests that they don’t need – and someone paying for it. In our case, we shelled out at least an extra two thousand dollars over the course of three months to keep an eye on Arjun’s femur. Surely there is a commercial imperative at work here, even if no one will openly admit it. I am not suggesting that individual doctors are thinking about money when suggesting monitoring. But the fact remains that anxious parents  - and a fetus that is being kept under strict observation -  is undeniably good for business. 

People and numbers: the false analogy

The whole time we were in Dr O.’s office, his eyes hardly left the computer screen that showed Arjun’s growth graphs. In fact the consultation could easily have been done remotely; as far as the doctor was concerned, the only important thing was those graphs. We could have sent them to him via an internet link. He hardly looked at us or dealt with us as people. For him, Arjun was not a growing baby but a set of points on a Cartesian plane. 

This is how modern medicine often works. The individual patient is abstracted to a set of data; then that data is compared to a body of global population data to draw conclusions about the condition of the patient. Thus cancer patients are nowadays told their chances of survival in terms of probabilities: a 80% chance of surviving five years, for example. What has actually happened is that the patient’s cancer has been converted to a set of data and then classified (say, as Type II); then historical data is consulted which shows that 80% of Type II cancer patients live for five years after diagnosis. This is then projected back onto the individual patient and expressed as a prediction about his future.

And this, I believe, is the fundamental flaw that is at the heart of the misuse of mathematics in medicine.

It is a flaw because the practice rests on false assumptions. To do medicine this way presupposes that a narrow abstraction of a human being can serve a useful purpose in isolation from the individual himself. It is an artefact of the reductionist, mechanistic view of science that has ruled the roost for so long; a model that has all but broken down in other branches of science but is still dominant in medicine. To look at such narrow abstractions is to treat a person as a sum of his parts alone. There is a false analogy at work: the analogy between a real, breathing human being - with all his history, personal traits and particular conditions – and a set of numbers that describe a very specific part of that person’s phyisiology. To believe the analogy is, I think, an absurd extreme of reductionism. In reality, a person is much , much more than the sum of his parts. We look at one small part in isolation and lose the holistic view of that individual as a working system.

Coming back to Arjun, was his femur really that small? Yes, if you measured it and placed it next to the particular population distribution that was available. But what if he were to be treated in context as an individual? A baby of Indian stock, who was small all around – even his head and torso were at the very small end of the scale – and who comes from a family where most of the older generations were stocky and short. A baby who had no other signs of any skeletal problems, was active and did not exhibit any of the other in utero signs of skeletal dysplasia. What would be the diagnosis then?

Surely not a “very low probability” of being normal?

The false analogy is used in both directions. Not only is the individual reduced to a string of data, but statistical data is often treated as if it represented something real. For example, the “average” biometric values are always used as a point of reference; yet there is no such thing as the “average” baby. There is no baby who has an exactly “average” length femur, an exactly “average” circumference of head, an exactly “average” bloodflow reading etc. Every individual baby, will exhibit some variation from the “average”. The “average” has a real existence in the abstract, mathematical world. But it is a human construction and an artefact of our mathematics. We have theories about its connection to the real world, but it does not live a “natural” existence. Yet, philosophically at least, the idea of the “average” being real in the world does strongly exist. And that is why we are so quick to compare someone to the “average”, and so concerned when the deviation is found to be “large”.

And what does it mean when someone is far from the “average”? Why are we so ready to take that as evidence of disorder or pathology? The “average” is simply the mathematical centre of the data what has been measured to date. Think about it: where else in life do we put such store in the abstract and the aggregate at the expense of the individual case? Do we tell a student about to sit his exam that he has a 20% chance of failing? Do we tell a batsmen as he steps out of the pavilion that he has a 7% chance of scoring a duck? Do we sign insurance policies at our wedding to cover the 30% chance of divorce?

We don’t, because in each of these cases we see the individual as possessing qualities that may place him or her outside of the normal historical range. People are different in ways that regular normal distributions know nothing about. You simply cannot project large-scale statistical measures onto individuals and call them predictions.

One last point. To compound the problem of the false analogy, there is also the phenomenon of “the more you look, the more you find”. If each of us, as adults, was put through the regime of pinpoint biometric measurement that fetuses undergo, I would guess that most of us would come up with some measurements that would be well outside the normal range. And yet most of us are “normal”. There may indeed be a vicious cyle at work here: the more testing your baby  undergoes, the more likely that something of “concern” will pop up; which means more follow-up testing, and possibly more “concerns”. And so on.

“Anything can be proved with statistics”

I realize this has all sounded something like a rant, but I am not bitter about what happened with our son. I don’t, in general, doubt the good faith and intentions of doctors. I am not a doctor myself; but I do understand maths, and I think the way medical science uses statistics is wrong and harmful. Folk wisdom say that “anything can be proved with statistics”. A combination of risk-aversion, mathematical illiteracy and  false assumptions has produced a system in which the everyday is becoming pathologized. My particular example is in prenatal diagnosis, but it is happening in other fields too. It is a dangerous trend, and it should be arrested.

Permit me one last piece of cynicism to finish on. I don’t think things will change easily because there are real economic barriers in the way of change. To overturn the false analogy between people and numbers would mean treating patients as individuals and doing qualitative work; in other words, getting to know them as people. That would make medicine less efficient and less lucrative for everyone. Dr M. and Dr O. seemed like nice enough people, but I doubt that they would ever vote for that. 

If the World Wide Web was a real place, what would it be? A vast library, packed to the rafters with books? A newsroom, a marketplace or a coffee shop? Probably all of those things, depending on your point of view. But there is another analogy which is more accurate: the Web as an exclusive club – one where the majority of the world’s people can’t come in.

That might be surprising. The Web has grown so fast, so quickly – it celebrates its 20^th birthday this year, if you go by the day it was first conceived in a research paper – that it seems that it has reached almost everyone. But it hasn’t. Even today only about a quarter of the world uses the Web. In Africa and some parts of Asia, it is even less; you could collect twenty people and be lucky to find even one who has ever opened a browser or clicked a mouse. The Web as a technology is still “shallow” – though it covers the globe, it does not penetrate very deeply beyond the affluent top layer of humanity.

The good news is that this is going to change over the next few years, and quickly. Mobile phone and broadband technology are making big strides in developing markets. For example, India alone adds ten million new phones a month, and the government there intends to roll out an internet kiosk into every one of its 100,000 villages. Mobile handsets are rapidly evolving towards having Web access as a standard feature. As result, over the next few years, large numbers of poor people across the globe will gain access to the Internet for the first time – perhaps doubling the global Web population in just five years.

This is a good thing, because the Web can potentially make a real positive difference to the lives of people in the Third World. Because these users typically have such little access to information, even a small window to the world can have huge impacts on their livelihood. This has already been demonstrated in some specific contexts through innovative programs that allow farmers to check crop prices, provide medical diagnoses for remote residents, or open up new learning possibilities for school children.

However, there is a barrier to this dream of a “deep” Web: most of these users will hardly be able to read. Even those who are literate are unlikely to be proficient in English, the de facto language of the Web. And because the interfaces that now make up the Web – web pages, hyperlinks, menus and so on – are so heavy in text, for these people they will be almost completely unusable.

Not only will these new users find it impossible to surf the Web, they will probably find it unpleasant to even try. To get an idea of what I mean, try this experiment: search for a Japanese news website (or Arabic, or another language with a script that is unfamiliar to you) and force yourself to spend five minutes clicking through it. You will find it a stressful experience. The text will of course be unintelligible, but you will even find it hard to make sense of other visual elements such as images and icons because they lack context. Would you use the Web if it was written in Japanese?

So here is the challenge for those of us who build the Web: to create new types of interfaces that are more accessible and easier to use. It’s not exactly clear what this new look Web might look like. It would certainly make a lot of use of symbols, audio speech and pictures. It might prove a very difficult task to develop it. But we won’t know until we try, and not many people have. There are countless researchers working on smarter, prettier and “cooler” features for the Web. But there are very few who consider how the Web might be made simple and usable for people with low literacy.

Perhaps that’s not surprising, because the next billion Web users will have much less money than the first. As a market, they are not important to the commercial interests that fund so much of the research and development. But we have a chance to do more than just follow the dollar signs. Technology, and those who build it, should help people. A real, democratic World Wide Web is just around the corner, if we are willing to take a broader view and make it happen. 

See also Symbolyze:Text-Free Web 

One argument that Kudlow and friends make is that executive bonuses are needed to retain talent in the financial system at a time when it is needed the most. It is this particular argument that interests me the most. I want to examine that statement from first principles, because I believe that some simple, plain thinking on this particular issue will bring clarity to the broader debate about the financial crisis and what is to be done about it.

That statement about bonuses is interesting because it rests on a stack of assumptions, at least five tortoises deep. They in turn are interesting because they are mostly unspoken and unexamined. So even listing them out is a learning exercise, because we are bringing something hidden out into the light.

So here they are, starting from the top tortoise:

1)   bonuses attract talented people

2)   running a finance company requires talent

3)   a finance company’s performance depends on the people who run it

4)   the financial system responds to and rewards human intervention

5)   the financial system is controllable and non-random

I’ll come out and say it: my contention is that all of these assumptions are wrong. Because each tortoise stands on the other’s back, it really only means that the most basic assumption that is at the bottom of the tower is wrong – if you can turn him over, all the others will topple. But I’d like to start from the top, because each of these assumptions reveals something about the way we have been trained to think about risk, control and the institutions that often run our lives.

Tortoise number one is easy enough. Bonuses attract people who are talented at making bonuses. If bonuses are offered routinely, without regard to actual performance, then the only talent you are selecting for is the desire to make money through a bonus. When you can get big bonuses even if the company is doing badly, then you are probably selecting for people who want to make money and are particularly shameless about having it delinked from performance. Which is pretty much what has happened – AIG being only the latest float in this sad parade.

Which brings us to tortoise number two – does it even matter who runs a finance company? If the best and brightest really were running AIG and others, why have they all failed at once? Nassim Nicholas Taleb has talked about replacing stockbrokers with random number generators and replicating their performance. A similar experiment with finance companies has never actually been performed, but we can do it as a Einstein-esque “thought experiment”. AIG, Freddie Mac, Bear Stearns – all being run by a two line computer program. Every decision, no matter how big or small, being made by an electronic version of a coin toss. What would happen?

I would say they would compare quite well. They might not have avoided a financial crisis, these little computer-virus-executives, but would they have done worse? Worse than losing a trillion dollars* and destabilizing the entire system to the point of collapse? I really don’t see how they could have. Trading versions of our imaginary executive cabal (with the addition of a chimpanzee) have out-traded the best of Wall Street. In analogy, at least, we could say that our computer programs would not have under-performed our real, flesh-and–blood finance executive class over the last year.

But in the interests of rigour, let’s say that we can leave this tortoise half-toppled, on his side. This issue really is  intertwined with our next assumption, and they stand or fall together.

The question is can a finance company be “run” at all, the same way that other companies can be run? I say not. Finance companies depend on the ability to predict the future, much more than real companies. Their health depends directly on the state of the sharemarket. And as the events of the last year have shown, no one can predict the sharemarket at all. So, as an executive of a finance company, you are in the position of a gambler at the roulette wheel. We don’t say that gamblers are “running” their casino campaigns, and neither are the finance executives running their companies. They can choose where to put their chips, but I would say we need to use different language to describe that level of control. 

We are approaching the real issue, the grand-daddy tortoise at the bottom of the stack. I’d like to stick with the casino analogy, and take it through to the end. The point about a casino is that it is a well-marked, separate domain which we understand as being completely artificial. Casinos play games with people’s money. For some reason, we don’t think of the financial system in that way – it is supposed to be far less arbitrary. But it is not. The random stochastic process that drops a roulette ball into a particular slot has its analogy in the financial world as the output of an immensely complex, chaotic system known as the sharemarket. I won’t tour the mathematics here, but essentially the output of a chaotic system is as random and unknowable to the observer as a “real” random process. Next year’s share price is as likely to go up as a bet on red.

So what about our second-last tortoise, the one about human intervention? Human intervention counts for approximately nothing . Humans in casinos are only there to deal the cards and serve the drinks. The results of the games don’t depend on the humans. They make decisions and may have the illusion of control, but there is no such thing as a skilled gambler – only lucky ones.

Just a side-point about the “artificiality” of finance. I believe that the finance world may have exacerbated the inherent problems of a chaotic system by creating an elaborate, artificial super-structure on top. The weird and wonderful financial “products” that preceded the crash – such as derivatives, futures, credit swaps and the like – have all the ingenuity in design of casino games; they were mostly constructed to hide the nature of the underlying system and mask the real nature of the risk. Of course, they enriched their architects, which is why they were created in the first place. Modern finance is an artificial industry. Finance companies produce nothing real; they use money to make money. They know it themselves, which is why they try the sleight-of-hand of labelling their schemes as “financial products” to make them seem more concrete. Finance is entirely man-made with no connection to nature. There is nothing wrong with that in principle, but people do not recognize its artificiality. They think of finance as just another industry, as real as building or education or medicine. But it is fundamentally different, because it is not organically connected to reality - and by treating it as if it is, we have made a grave error.

The fattest tortoise is on its back, and we can work our way back up and watch them fall. The financial system is chaotic-random and not controllable. No one can predict the future of the market and no one can “analyze” the system beyond recognizing that it is chaotic. People created the system but are now at the mercy of it. On a small-scale, human intervention can have some local effects, but over time scales of interest their contributions do not bring any patterns to bear. Finance executives might as well play solitaire, and do less harm. In the big picture, their companies "run" themselves. No one “surfs the waves in” – everyone is a just a cork bobbing around. Not only does a finance executive not require talent, but talent is irrelevant. And paying bonuses that are delinked from performance simply adds another layer of stupidity on top of the dung-heap by selecting an executive class that is especially indifferent to the idea that money should come from work.

Can we spy an even plumper tortoise at the bottom of the stack? If the sharemarket - and its dependent systems - are a thrashing, chaotic double-pendulum, why have we based a civilization around it? Perhaps the world would be better off without a financial industry as we know it. I can hear Kudlow and friends gnash their teeth – Commie bastard! But this is not a Marxist critique. It is only this particular model of capitalism, with a casino as its engine room, that is on the nose. Maybe we can buy and sell real things and work for each other quite well without the sharemarket. In fact, if real capitalism is about private enterprise, then why shouldn’t my little going concern be unshackled from this complex, unpredictable beast? A little bit of credit, money in the bank, no usury and a system that rewards work. As one of my university professors used to say, just some “common-f***ing-sense”. How did we get to the point where that seems radical?

*That is my estimate. No one knows the actual figure, and it doesn’t make a difference to the argument

Is it possible that this will endure?
When we look out past the barricades into the city,
We see a sky painted in cruel greys,
We see the tyranny of Man set in concrete,
And we dream of Israel.
Our own walls are pierced with small kindnesses,
And I tell David:
Discard everything,
But do not forget your mother’s smile.

History has been condensed:
Forty hundred years of suffering  
In my baby’s eyes.

I can tell him stories
Of prickly rabbits and their wiles,
A story of my own youth
(though my milk is almost gone).
I put him into the tale:
‘Brer rabbit, my friend,
One day I will meet you,
In America.’

But how can I save him?
My own lips are at my breast,
Sucking at nothing but yellow skin.
We are in decay.
Outside, the old ones die
And are taken in wooden carts
Through the snow.

The last notice:
Another cut in rations;
We are too tired to cry.

Go - I tell him, in a whisper,
Relieved that there is no more doubt.
I will throw him to the mercy of the world,
And he will float amongst the reeds,
Right into the mouth of the enemy
And out the other side.

‘And when you see him, my son,
You too can say:
I was born and bred
In a briar patch.’

I have been thinking about this, and what an individual NRI can do in these times to make some kind of difference. The terrorists who attacked Mumbai had many aims, but chief amongst them was to cast a shadow over the modern story of India and to damage the economy. This is where we NRIs have the most to contribute. Amidst the sadness and the anger I get a flash of resolve: that we must reply by redoubling our commitment to our country.

So here is my humble three point plan for the Indian NRI:

1) Be an advocate for India. Write to your local politicians and ask them to strongly support India in her time of need. Support local Indians - go to see that Bollywood movie or cultural show, buy Indian products and food, talk to Indians on the street. Engage with others in a positive way about your culture and explain to them the context of what happened in Mumbai. All of us are ambassadors for India, and now that role is more important than ever.

2) Do business with India. If you were thinking of investing, do it. If you already invest there, double your investment. If you were thinking of working with an Indian company, call them and make the deal. The India story will continue, but we can make a difference by showing our belief in the future of India in a tangible way. Terrorism is not just about blood but also money, and it is through our money that the NRI community can make the most emphatic statement.

3) Go to India. Make plans to visit whenever you can for work or for pleasure. Call your relatives and tell them you will visit. Book a ticket to Mumbai. When the Taj is rebuilt, go to the Sea Lounge; order a vodka martini with someone you love; sit back, look out onto the Arabian Sea and make a toast to India and her people.  

"There is a physical difference between the white and black races which I believe will forever forbid the two races living together on terms of social and political equality. And inasmuch as they cannot so live, while they do remain together there must be the position of superior and inferior, and I as much as any other man am in favor of having the superior position assigned to the white race"