The Essentials of Epistemology

The Essentials of Epistemology (the study of how to discover the truth):

Now we See Through a Glass, Darkly

How can we tell the difference between truth and error, between fact and fiction, between conspiracy fact and conspiracy theory? Naturally, the best solution is to become an expert. But unfortunately you can't become an expert without first learning what information to trust, and what information to ignore. Furthermore, it is impossible for everyone to be experts on everything. So we all eventually have to trust the advice of others. But whose advice should we trust? These questions are becoming increasingly important in the world of the internet, where everyone has been given a printing press, and where false (and even dangerous) ideas spread like wildfire. 

I do research in statistics, which is the study of how to determine truth from data and make rational decisions based upon this data. So I naturally have some opinions on the matter. But explaining these principles to others outside the field of statistics can be a challenge. And it is not reasonable to expect everyone to get a degree in statistics before they try to sort through the difference between truth and error. 

So, how should the average person determine truth from error? There is no magical approach that will guarantee that you are never deceived or mistaken. But I believe that there are a few simple principles that will lead you to the truth more often than other approaches. They are: 

1. Simplicity: The simplest theory is to be preferred over the more complex theory, all other things being equal (which has bearing on #4 as well).

2. Data over Dogmatism (be willing to change your mind): Let the data speak for itself as much as possible, don't assume that the answer must match some ideological or dogmatic assumption. Be as dispassionate and rational as possible. Allow your opinions to change when the data contradicts your initial opinions.

3. Avoid Confirmation Bias: People naturally tend to seek out data that confirms their initial opinions (this is called confirmation bias), while reacting to new data that contradicts their original belief with even more fervent adherence to the original belief (the backfire effect). This means that the luck of the draw for what you believed first has an unfair advantage. Therefore, be sure to actively look for data that contradicts your initial opinions, and do your very very best, as hard as it can be, to treat such new data fairly. (Conservatives should watch PBS, CNN, and BBC, while liberals should watch Fox News). It is only after you have read and understood the opinions of those that disagree with you, that you can be confident that you are actually right. 

4. Avoid Conspiracy Theories: Although real conspiracies do exist (usually very small ones), assuming that all data counter to your initial belief is due to a vast conspiracy to hide the truth is problematic, because first, it vastly over simplifies the reality where each person has their own (often contradictory) goals and motivations, which generally limits the real conspiracies in size and scope; second, most people want to do good, and those that do evil usually do it because they have convinced themselves that it is the right thing to do; and third (and most important) it creates a situation where your opinion (right or wrong), can never be contradicted by evidence, no matter how strong or otherwise convincing. This is an especially dangerous flavor of confirmation bias (see #3 above).

5. Trust the Experts: Because we can't personally experience everything, we must trust the opinions of others that have experienced things that we have not. Assuming that white elephants don't exist because you haven't seen one is foolish if others have. Thus, a large percentage of our understanding of the world around us must be based upon the witness and opinions of others. Our task is often to determine which witnesses to believe, and which opinions to trust.  When deciding which experts to believe, always assign more weight to the opinions of people who know more about the subject, than you do to people who know less about the subject. This means that we should trust and respect the experts in their fields. Look for issues and ideas where there is a strong consensus among the experts in a given field. And be careful of internet sources. Some 60 year old guy blogging in his underwear from his parent's basement does not a reliable expert make.

I understand that most human progress was made when people like Galileo challenged expert views on things like whether the earth was at the center of the solar system. But Galileo also understood that challenging this consensus required careful study and very strong evidence. He then went out and did the difficult legwork to gather, summarize, present, publish, and then defend that evidence. And when he did, the consensus gradually changed. It is possible (and necessary) to occasionally challenge a consensus view, but it should require strong evidence first. To think that we know better than the vast majority of those around us without that very strong threshold of both effort and evidence is one important definition of pride.

6. Look for General but not Unanimous Consensus: Understand that there will always be a few dissenting voices on every issue. Don't assume that because you found a PhD physicist that thinks that the earth is flat that there is "controversy" among the scientific community on the issue, and that there is no scientific consensus on the matter, or think that the idea that the earth is a sphere is "only a theory", or that you should "teach the controversy" on this matter. Instead, look for general agreement among some large majority of the experts. 

7. Avoid Anecdotes and Emotional Stories: Anecdotes are almost entirely useless, since there will always be an anecdote or two that seems to support any possible position that one could conceivably hold. Unfortunately, these anecdotal stories often have vast emotional impact, but that doesn't mean that they are right. Instead, look for broad statistically significant studies to find truth. They are less emotionally convincing, but they are far more likely to be right!

If you follow these 7 rules, you will undoubtedly be wrong on occasion. But you will be wrong less often than if you don't, and you will be willing to change your mind rapidly when more information showing that you were wrong becomes available. If you do this, you will be unlikely to be lead astray, and you will be far more likely to discover things as they really are, really were, and really will be. 

So, how does that play out?

In the vaccination debate, it means that we should pay more attention to reputable doctors than we do to Jenny McCarthy when talking about whether we should vaccinate. It means that while the emotional story of the child that died after being vaccinated may be more emotionally moving, it should not be as intellectually convincing as a broad based statistical study. And it means that we shouldn't be surprised to find a few MD's in both camps. But we should look at the broad consensus, and realize that the vast majority of reputable doctors favor vaccination. Therefore we should favor vaccination. There is no vast conspiracy to make vaccination look successful when it is not. Sure the pharmaceutical companies have the motivation to do this, but the vast array of doctors who care about their patients don't. At least not in a way that could cause this level of near universal support.

How would these principles play out in the global warming debate? I am sure you can immediately see the answer. How about evolution? Again, is the answer obvious? How about economics? For some economic issues, things are a bit more muddled, but that itself is a conclusion, namely that there is consensus on some important points, but disagreement on some others.We should likely be uncertain ourselves when it comes to the areas of expert disagreement. It is remarkably prideful to assume that we know for certain answers to controversial questions that so many other very intelligent people don't.

What about the truthers? The birthers? Opposition to GMOs? And the list goes on and on and on.

(For more thoughts on the 'wisdom of the crowd,' the 'marketplace of ideas' and the problems the internet has produced in these things, see my paper: "Amplifying the Wisdom of the Crowd, Building and Measuring for Expert and Moral Consensus" by myself and Brent Allsop.)

The Singularity May not be Near, but You Have Yet to Convince Me

I would like to take a moment to respond briefly to Michael Shermer's fascinating article: "In the Year 9595, why the Singularity is not Near, but Hope Springs Eternal" in Scientific American, January 2012.

Michael Shermer's rebuff of singularitarianism is witty and Interesting, but ultimately un-convincing. He makes fun of those who make predictions as "soothsayer's", but he seems to be ignoring the power of trends to often accurately predict future technological performance. His "baloney-detection alarm" may go off, but he provides no counter data. I prefer a data driven approach myself, and this article, witty as it was, was certainly not data driven. If the data says that this generation is most likely special, then it most likely is, Copenhagen principle or no.

Of course, trends don't always continue. But if they don't, in this case, I will be extremely interested in knowing why not, and it was this question that was never really addressed by Michael Shermer. For example, many people have argued that computational performance trends will not continue because we will hit the quantum limits of Moore's Law by 2015-2025. At least that would be a reasonable, although ultimately flawed, argument to make. But Shermer doesn't even do that. If he had, then he might have given me more to refute. For example, then I might have been able to discuss the fact that the human brain is a proof by example that it is possible to perform about 10^19 CPS for about 20 Watts, in a few cubic feet of space IF one is willing to change the architecture of the computer system from today's Von Neumann architecture to something more massively parallel. Which means that Moore's Law may stumble to a halt, but that there is plenty of room for computational improvement after the death of Moore's Law. Of course, progress down this new route may well follow a different trend, improving at a different speed. Progress may even slow for a time after the death of Moore's Law while we face up to the fact that we must switch directions before improvement can continue. But even if this is the case, since we are set to pass the upper bound for performing a full neural simulation of the human brain by 2025, Moore's Law will ultimately fail too late to stop the creation of the hardware needed for true AI.

Shermer did provide one data point, namely that knowing the wiring diagram of the nervous system of Caenorhabditis elegans, and having sufficiently powerful hardware to perform a full neural simulation has so far not lead to a working brain simulation of Caenorhabditis elegans. This is indeed an interesting data point. However, we appear to be making exponential progress at understanding the behavior of individual neurons, AND exponential progress at understanding the wiring diagrams of the brains of ever more complex organisms. Both. I argue that ONCE we thoroughly understand the behavior of individual neurons (and their many types/kinds, connections, and plasticity) THEN knowing the wiring diagram of ANY complexity is enough for full brain simulation. This is important to point out, because some singularitarians seem to think that once we have the wiring diagrams for human brains, and once we have the computational raw power, fully human level AI is inevitable. This is not true by any means. If computer trends continue, we will have the computational power to run a full neural level brain simulation by about 2025 in our super computers. But that doesn't mean that we will have the human connection diagram by that time, nor does it mean that we will have cracked the neuron by that time. However, we ARE making exponential progress on both fronts, so if we don't have these things by 2025, I would guess that we will have them by 2045... give or take 25 years or so either way. There is a lot of uncertainty there, mostly because we don't yet know exactly how complex the problem will be (the neural level modeling I mean, we have a descent idea about the other). Furthermore, the power to do the simulations will feed back on our neural understanding. We can plug one neural model into the simulation, and see how it runs, then compare to a real brain scan, and then tweak the simulation... rinse... repeat.... etc.

Essentially, I think that this man's skepticism is unfounded, or, at least, if it is founded, he failed miserably to explain why it is founded, or to be convincing in any meaningful way.

James Carroll's Review of The Greatest Show on Earth: The Evidence for Evolution

The Greatest Show on Earth: The Evidence for Evolution by Richard Dawkins

My rating: 3 of 5 stars

This book was only so so, and there were two main reasons.

First, his evidence:

It simply wasn't that good. And it's not because there isn't good evidence for evolution. But the whole way through this book I kept thinking things like: "I could produce better evidence than that!" "Why didn't he mention this or that?" and, "Why is he talking about this, it's a huge digression?" etc. The evidence he provided is actually overwhelmingly convincing, the problem is that there is actually even better evidence out there that he didn't talk about (or that he only mentions in passing). I did learn about a few lines of evidence that I didn't know about before, so in that sense it was worth the time I spent. I just wish that he had done a better job, since I completely agree with him that we badly need this sort of a text today.

Second, his atheism:

Dawkins is a staunch atheist. Now, Dawkins claims that his primary purpose is to provide the evidence for evolution in order to save those who have been deluded by those he calls the "history deniers." That is his term for those creationists who deny the fact that evolution happened in order to cling to Biblical inerrancy. But if that was his goal, then he should have left his atheism on its shelf, at least for the duration of this text. In fact, in the introduction, he claims that this is what he is going to do. However, it appears that Dawkins is so enamored of his atheistic position that he is incapable of doing so, and I fear that it chased away the very people he was trying so hard to reach.

I vastly preferred "Why Evolution is True" by Jerry Coyne. That book is what this book should have been. http://www.amazon.com/Why-Evolution-True-Jerry-Coyne/dp/0670020532 If you are looking for a good book on the evidence for evolution, Coyne's book is the one I would suggest instead.

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Book Review, Stephen Hawking, The Grand Design

The Grand Design by Stephen Hawking

My rating: 4 of 5 stars

"Traditionally these are questions for philosophy, but philosophy is dead. Philosophy has not kept up with modern developments in science, particularly physics. Scientists have become the bearers of the torch of discovery in our quest for knowledge." Stephen Hawking

I couldn't agree with that statement more. Some of his other conclusions in the book from which the quote was taken "The Grand Design"... not so much.

But in what way is philosophy dead? Clearly the love of wisdom is not dead, but it may well be that the field of liberal arts philosophy may indeed be dead (or at least loosing relevance and productivity).

To attempt to discover the real truth requires more than sitting and thinking, it requires observation, and then modeling, which requires math. This means that today the mathematicians and physicists are doing the real leg work of philosophy, while the liberal arts philosophers are, for the most part, spinning their wheels.

There is a feeling that theology and philosophy should be the ones asking the questions about morality, theology, meaning, and God, while science should keep its distance. But I believe that you can't ask these questions correctly without a firm grounding in the observations of science and physics, which MUST inform any inquiry into philosophy, or even theology. As Einstein said, science without theology is lame (in the sense of not having the power to move things forward), while theology without science is blind (in the sense of moving forward, but not seeing where it is really going).

Therefore, I find that I simply can not agree with those that say that science should leave such theological matters to religion. In my view, Stephen Hawking has every right to venture into the field of theology, and to bravely see what implications his understanding of the laws of physics has on his understanding of God. This is a useful and potentially very productive undertaking.

Let us take some of Hawking's conclusions in this book as an example, and see how science can inform theology:

1. In the beginning, the universe was very small, thus the rules of Quantum Mechanics hold, and things like the universe can (and indeed will) appear out of nothing without violating the rules of quantum mechanics, so long as it eventually cancels itself out, just as virtual particles usually do.

2. The universe has an equal amount of positive and negative energy, and so is a cosmic free lunch, and can (and will) appear out of nothing (essentially, the universe cancels itself out, much like virtual particles do).

3. But the universe was also hugely massive, so it followed not only the rules of quantum mechanics, but also the rules of relativity, which says that mass bends space and time, and at the point where you have enough mass to make a black hole (as we clearly had in the early universe), time itself stops, so there IS no time before the big bang, time curves back upon itself, and comes to a single closed point, creating a beginning not only of the universe, but of time itself, and thus it creates a beginning to the chain of causation. The chain of causation (where the causes come before the results) comes to an end at the Big bang, which necessarily had no cause, because there was no time before the big bang for that cause to act in.

His conclusion? There is no God in the platonic sense of the "prime mover" or "first cause" because 1. we don't need him to explain how and why the universe could come into being, (quantum mechanics does that) and 2. there could be no creator of the universe, because there was no time before the universe was created for Him to act in. Essentially, God could not "cause" the universe, because relativity guarantees that there was no time in which he could act to initiate such a cause, and after the big bang bangs, we don't need Him to explain the progression of the universe from that point on (the laws of nature do that).

Whether or not you agree with these conclusions (which I do not), it is clear that a firm understanding of the issues surrounding quantum mechanics should indeed necessarily inform our theology. Even if his reasoning here is flawed, that is the way science works. It is necessary for someone to make these sorts of inferences, so that science can move forward and either prove or disprove this theory.

So, why don't I come to the same conclusions as Hawking? His reasoning appears rather solid at first glance. However, relativity and quantum mechanics are notorious for their inability to play nicely together, and there are a myriad of potential theories that have been proposed in an attempt to produce a good theory of quantum gravity. He is here espousing one of these theories, granted, it is the one that is (so far) the most mathematically robust, but it is by no means the only solution to this problem. For example, some theories of quantized time predict a big bounce instead of a big bang, in which case there was indeed time before the big bang. Another competing theory predicts that two of the membranes predicted by M-theory collided, producing the big bang, again, this is a theory that predicts time before the big bang. Still other theories predict that there are other dimensions of time, outside of our own. It is also unclear to some whether quantum fluctuations can create virtual particles without space or time in which to create them, which could cast doubt on whether a quantum fluctuation alone could create the universe from no-where and no-when. For example, Sean Carroll proposes that each universe is born from parent universes (see From Eternity to Here: The Quest for the Ultimate Theory of Time), in which case, time would indeed exist before the big bang. The possibilities are nearly endless. And, most importantly, we have yet to find observations that can clearly differentiate between many of these competing theories. Essentially, we have no observationally verified theory of quantum gravity, which is necessary before we can make any real predictions of how the universe behaved in these early moments that are so essential to Hawking's arguments.

So, if we take this into consideration, we can rephrase Stephen Hawking's brilliant deduction differently. IF we accept THIS theory of quantum gravity, together with its predictions about quantum fluctuations and the beginning of time, THEN the universe necessarily had no cause within our dimension of time, and thus, there is no God that exists solely within our universe's dimension of time. I believe that this is a valid deduction, and, to some extent, it should inform our understanding of God. It is only unfortunate that he didn't state his conclusions with this level of cautiousness. Instead, he is far more confident in his conclusions than is warranted by the data, and he leaves out the many "if"s that should have preceded his conclusion. This was perhaps my only serious disagreement with the Book.

And what of my own conclusions about God? That is not really what this review is about, but to be short:

Theleologians in my chosen branch of Christianity have often said that God does not just predict the future, he quite literally sees it. For this to be the case, God must, of necessity, exist outside of our dimension of time, and likely outside of our dimensions of space as well. I find the fact that science is now predicting a universe of multiple dimensions and multiple universes (some with different laws of physics), and is finding that God cannot exist only within our dimension of time and still create the universe, to be quite faith promoting since that is in line with what I believed all along.

Stephen Hawking would likely take issue with my interpretation of his work, but hey, that is what Science is all about, and we should be grateful to Stephen Hawking for so clearly expressing this brilliant deduction.

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Is the Singularity Near or Far?

In this article, titled "The Singularity is Far", http://www.kurzweilai.net/the-singularity-is-far-a-neuroscientists-view?utm_source=KurzweilAI+Daily+Newsletter&utm_campaign=a40a06de5c-UA-946742-1&utm_medium=email David J. Linden challenges many of Kurzweil's timetables for the reverse engineering of the Human Brain. His primary argument is that although data is growing exponentially, our understanding of that data appears to be growing only linearly.

Lincoln Cannon challenged this article's premises here:http://lincoln.metacannon.net/2011/07/singularity-merits-understanding-but.html

Lincoln's response was well thought out, and he had some excellent points.

Lincoln's primary argument seems to be that we don't need understanding, just simulation and scanning resolution. "In a sense, it would be like riding a bike versus understanding the physics of riding bike; we can do the former without the latter." I essentially agree with him there. It is indeed possible to develop a singularity like event using simulation without understanding.

However, when Kurzweil made his predictions, he assumed that functional simulation would require much less computational power than would a full simulation. Essentially, Kurzweil assumed that we would use the power of "understanding" to create algorithms that are more efficient than the brain, and his entire time table was based upon this assumption. If we are instead going to assume that we will use simulation without understanding to do the trick of creating the singularity, then we must recognize that the computing power needed will be far greater, and this will move the time table for the Singularity far back from Kurzweil's predictions.

There are several reasons why I reject Kurzweil's time tables for the Singularity:

When I look at most of the technology trend data, I tend to see exponentials where Kurzweil sees double exponentials. Furthermore, although I do see exponentials trends in our data gathering abilities, like David J. Linden, I see linear progress in our understanding of that flood of data. I actually believe that understanding is most likely on an exponential trend too, but it is just in the early, nearly linear, beginning of an exponential that will take time to "ramp up" to the knee of the curve. But it's hard to map numbers to brain "understanding" and so it is hard to predict when this shift will take place.

Kurzweil's time table is based on 10^14-10^16th cps to simulate the functionality of the brain, something that would require re-writing the brain's algorithms in a more efficient manner, and that requires understanding. To go the "simulation without understanding" rout you need more like 10^19th cps. That would push many of the dates for Kurzweil's predictions back several years at least.

10^19 cps should arrive in super computers by 2022-2025 according to my last projections. https://picasaweb.google.com/jlcarroll/Economy#5620432299391054642. This really isn't in time to meet Kurzweil's deadlines, because he predicts strong AI at about the time when the computation necessary to simulate the brain hits $1000, not when it can be done only on the world's most expensive supercomputers. In other words, he predicts that we will have good strong AI simulations AFTER we have had clumsy ones in a super computer for a while, after we have some time to study and perfect the clumsy ones, and then only after they get cheap enough to work really well and become ubiquitous.

Down the "simulation without understanding" road, you need 10^19th cps to hit $1000 instead of only needing 10^16th cps to hit $1000, and that shouldn't happen until significantly after 2022 when our fastest super computers should be able to do it. My last prediction put this landmark at about 2058! And that assumes that the doubling rate of cps/$ doesn't slow after Moore's Law hits the quantum barrier somewhere between 2020-2025. If it slows, which it might, then this could take even longer. I will admit that if I am wrong, things don't slow down but speed up, and if there is a double exponential at work here that I can't find, then this might happen significantly sooner. Nevertheless, even then, it would still happen some time after Kurzweil's deadline if you use a simulation without understanding paradigm.

In other words, I may buy into many of Kurzweil's predictions, but I find that I must also question some of his timetables.

GDP, Going Further Back, Optimism Again

I earlier blogged about Why I am an Optimist. In that post I presented the following graph of GDP between 1930-2011:

My Per Capita, inflation adjusted GDP graph for 1930-2011.

I was fascinated by the exponential growth in GDP, even in inflation adjusted per-capita GDP, and craved more data. Since getting data from the future by Hepatoscopy failed (mostly because I couldn't find a good lamb to sacrifice and read its liver), I decided to take the more practical rout, and look further into the past instead. Granted, looking further into the past is usually not as exciting as looking further into the future, but we will take what we can get until we invent that pesky time machine.

In any event, I looked around the internet for some more data, and found this data, which I summarize in the following graph:

My Per Capita, inflation adjusted GDP graph for 1 AD - 2001 AD.

What interested me most about this data was that it indicates that for the last 2000 years, inflation adjusted, per-capita GDP has been growing at a super exponential rate. This means that not only is the GDP growing exponentially, but the rate at which it is growing exponentially is itself growing exponentially.

But what exactly does it mean for GDP to be growing at a super exponential rate?

What it means is that trade, specialization, technology, and automation have been making us all more productive and more wealthy. And it means that the rate at which have been making us more productive and wealthy has been increasing. And that the rate at which this rate is increasing has itself been increasing. All the wars, dark ages, inquisitions, famines, natural disasters, genocides, recessions, and depressions of the past 2000 years have only been minor bumps along the road to increased prosperity when viewed from the perspective of this 2000 year sweep of history.

What would it mean if this trend were to continue? We can only guess, but something like the end of scarcity, and the beginning of overwhelming world wide prosperity would be one such guess, and would be a reasonable one at that! Insuring that this outcome is actually produced will naturally require a certain amount of effort on our part, but I believe that that will be effort well spent.

Some housekeeping

Because I want a place to ramble about economics and politics, and because my photography viewers aren't usually interested in that, and because my politics people aren't usually interested in my photography, I decided to split the blog.

Politics, economics, computers stuff, transhumanism, all that will stay here. If you are looking for my photography stuff, go here:

http://jlcphotography.blogspot.com/