singularitarian

In a talk titled “Beyond Today”, Google’s CEO Larry Page infused Zeitgeist 2012 attendees with a healthy dose of optimism and a call to make ambitious bets, be better organized and work harder to accelerate technology and improve people’s lives. Donning a Google Glass prototype, he began his talk casually demoing the tech by saying, ”If you guys are going to take my picture, I’ll take your picture too.” Then with a voice command and the tap on the side of the frame, he shared it with everyone at Google. That simple action captured the flavor of his two-part talk, which highlighted Google’s current efforts and cast a vision for where Google is headed next, guided by a slogan he borrowed from a University of Michigan summer leadership course: “Have a healthy disregard for the impossible.” We’ve been painting a picture of a bright technological future here at Singularity Hub, and now Larry Page is here to bolster our argument. (via Larry Page: With A Healthy Disregard For The Impossible, People Can Do Almost Anything | Singularity Hub)

Ray Kurzweil’s book The Singularity Is Near dragged me back into a subject that I am familiar with. In fact, ten years ago I thought I was the first to have discovered it only to find out later that a whole cult with increasing number of followers was growing around it. I took my distance from them because at the time they sounded nonscientific. I published on my own adhering to a strictly scientific approach. But to my surprise the respected BBC television show HORIZON that became interested in making a program around this subject found even my publications “too speculative”. In any case, for the BBC scientists the word singularity is reserved for mathematical functions and phenomena such as the big bang.

Kurzweil’s book constitutes a most exhaustive compilation of “singularitarian” arguments and one of the most serious publications on the subject. And yet to me it still sounds nonscientific. Granted, the names of many renowned scientists appear prominently throughout the book, but they are generally quoted on some fundamental truth other than the direct endorsement of the so-called singularity. For example, Douglas Hofstadter is quoted to have mused that “it could be simply an accident of fate that our brains are too weak to understand themselves.” Not exactly what Kurzweil says. Even what seems to give direct support to Kurzweil’s thesis, the following quote by the celebrated information theorist John von Neumann “the ever accelerating process of technology…gives the appearance of approaching some essential singularity” is significantly different from saying “the singularity is near”. Neumann’s comment strongly hints at an illusion whereas Kurzweil’s presents a far-fetched forecast as a fact.

What I want to say is that Kurzweil and the singularitarians are indulging in some sort of para-science, which differs from real science in matters of methodology and rigor. They tend to overlook rigorous scientific practices such as focusing on natural laws, giving precise definitions, verifying the data meticulously, and estimating the uncertainties. Below I list a number of scientific wrongdoings in Kurzeil’s book. I try to rectify some of them in order to properly present my critique of the Singularity concept.

On Scientific Rigor

1. The Goodness of the Exponential Fits

At the risk of sounding pedantic I want to point out that the correlation coefficient R2—which Kurzweil displays as a stamp of quality control on all his exponential fits—does not provide unequivocal evidence that a certain theoretical curve best fits a given set of data. This is demonstrated in Figure 1 where the correlation coefficient between the data points and the gray line is maximal, i.e., R2 = 1.000, but it is obvious that the line constitutes a very poor fit for the data trend.

A much better figure of merit for the quality of fits is a simple sum of differences squared or the more sophisticated chi-square per degree of freedom.

Kurzweil’s fits are no more convincing for the R2 values he displays on them.

Figure 1. For two significantly different trends (a steeply rising one and a practically horizontal one) the correlation coefficient can be 100%.

2. The Reliability of the Data 

All the data for the graphs of Chapter One, which play a crucial role in Kurzweil’s introduction of the subject, come from two articles of mine.[1,2] The data consist of fourteen sets of milestones in the evolution of the universe, which I researched. But while I strived for the data to come from independent sources I did not succeed very well. Two sets were not independent and I made that clear in my articles. One set had been given to me without dates and I introduce them myself; the other set consisted of my own guesses. Both sets were heavily biased by the other twelve sets in my disposal. Moreover, some data were simply weak by their origin (e.g., an assignment post on the Internet by a biology professor for his class, which is no longer accessible today.)

As a matter of fact only one data set (Sagan’s Cosmic calendar) covers the entire range (big bang to Internet) with dates. A second complete set (by Nobel Laureate Boyer) was provided to me without dates. All the other data sets coming from various disciplines covered only restricted time windows of the overall timeframe, which results in uneven weights for the importance of the milestones as each specialist focused on his or her discipline.

Any hard-core scientist would try to double-check the quality of the data that support his or her central thesis and/or estimate the uncertainties involved. Kurzweil does neither. Instead he augments the number of data sets by one adding the set from my second publication—which is the average of 13 of the previous data sets—and thus boasts evidence from 15 independent sources!

3. Adherence to Natural Laws

    Kurzweil is possessed by the exponential function. He criticizes people who make forecasts by simply extrapolating straight lines on linear trends. But he does the very same thing on logarithmic paper.

    Naiveté is not associated with the graph paper being linear or logarithmic. Kurzweil’s wrongdoing is relying on mathematical functions rather than on natural laws. The exponential function represents only part of a natural law. Nothing in nature follows a pure exponential. All natural growth follows the logistic function, which indeed can be approximated by an exponential in its early stages. Explosions may seem exponential but even they, at a closer look, display well-defined phases of beginning, maturity, and end, the integral of which yields a logistic. Explosions can be described from beginning to end far more accurately by a logistic—albeit a sharply rising one—than by a pure exponential.

    As for his double exponential, it corresponds to reality even less than a simple exponential. Kurzweil observes double exponentials only when he divides by the price, for example “calculations per second per $1,000”. He obtains a double exponential because he is dividing two logistics. One is the increase in processor performance (Page 64) and the other is the decrease in processor cost (Page 62). However, mathematically the ratio of two logistics is not necessarily a double exponential. It can easily yield a pattern growing less aggressively than a simple exponential depending on the parameters of the two logistics.

    Why then Kurzweil feels confident that the double exponential will continue for a long time to come? It is an assumption as naïve as that of extrapolating a straight line. A pattern can be used to make forecasts only as long as it represents a natural law that guarantees invariability. The law here is logistic growth and the ratio should be taken only after the two logistics have been estimated.

    Another manifestation of sloppiness is Kurzweil’s discussion of the “knee” of an exponential curve, the stage at which an exponential begins to become explosive, see Pages 9 in the book.

    It is impossible to define such a knee in a rigorous way because of the subjective aspect of the word “explosive”. Figure 2 displays four sections of the same exponential function. On graph (a) at the top the knee could well be at time = 70 but as we look closer it progressively moves down to time = 7 in Graph (d) at the bottom. It is still the same exponential function with the vertical scale expanded.

    There is no way to single out a particular region on an exponential curve because the pattern has no intricate structure. It is basically a one-parameter mathematical function that varies continually and identically from -¥ to +¥. It always grows at the same percentage rate. In contrast, the S-curve has a ceiling and a center point, which can be used as reference points.

Kurzweil’s knee depends on the judgment of the observer, namely that the curve attained a relatively high value. The knee can be defined as a threshold, an absolute level characterized as high by the majority of observers. This is clearly a source of bias.

Figure 2. The same exponential is displayed with different vertical scales. Kurzweil’s knee can be positioned anywhere depending on the perception of the observer at the time.

Where Are We on the Curve?

Toward the end of his book Kurzweil addresses the question of logistic growth. In fact he admits that there are always limits and that even his exponential growth curves will eventually turn into S-curves, but this will happen very long time from now. So he stops there, closes the S-curve topic, and goes back to his discussion of the exponentials.

It seems to me that the obvious question for any scientifically inclined mind would be “if we know there is an S-curve, can we defined more rigorously our position on the curve given that S-curves have reference points.” In other words, instead of saying that we are at a point “very high” with respect to where we have been, but “very low” with respect to where we are going—exponential knee—we can now estimate how far is the ceiling of the corresponding logistic?

One way to do this (besides fitting the data to a logistic) would be to establish a relationship between the level of the exponential knee and the level of the logistic ceiling from well-documented and universally accepted cases. For example, how long did it take to populate the earth from the time a population explosion was first noticed?

Three such cases are presented below.

1. World Population

World population has grown significantly during the 20th century during which it traced an archetypical logistic growth pattern, see Figure 3. Its evolution during the early decades depicts an exponential pattern, which later becomes an S-curve as expected. The deviation from the exponential begins in the 1970s.

The crucial question is where is Kurzweil’s knee. We can translate the question as “when did the population explosion begin?” I believe it was right after WWII around 1950 when world population reached 2.5 billion, as indicated by the big circle on Figure 3.

Figure 3. An exponential (dark gray line) and a logistic (light gray line) fit on world-population data. The graph focuses on the 20th century during which we have accurate and detailed data (yearly numbers from 1950 onward). The logistic fit is exemplary. The circle indicates what in my opinion could be taken as the exponential curve’s knee.

The data are of good quality and come from a reliable source.[3] The logistic fit is excellent, as can be appreciated by simple inspection. The final ceiling is forecasted at 9 billion and this number is generally accepted by most experts including Kurzweil.

It then becomes evident that the exponential knee occurred when world population reached 28% of its final ceiling.

However, by some historians the population explosion began in the West, around the middle of the 17th century. The number of people in the world had grown from about 150 million at the time of Christ to somewhere around 700 million in the middle of the 17th century. But then the rate of growth increased dramatically to reach 1.2 billion by 1850.

In this case the exponential knee would have occurred when world population reached 8% of its final ceiling.

2. Oil Production     

A completely different growth process, oil production in the US, can also help us establish a relationship between the knee threshold and the ceiling. Oil began being produced commercially in 1859, but production picked up significantly only in the early twentieth century. Cumulative oil production in the US turned out to be a smooth process that followed the logistic growth pattern extremely closely. The logistic fit is excellent, see Figure 4.

The knee as shown represents 10% of the ceiling.

Figure 4. Yearly data points (small dots) are fitted with exponential (dark gray line) and logistic (light gray line) functions. The data and the logistic fit are taken from my book Predictions – 10 Years Later.[4] The circle indicates a reasonable position for Kurzweil’s knee. 

3. Moore’s Law

The celebrated Moore’s Law is a growth process that has been evolving along an exponential growth pattern for four decades. The number of transistors in Intel microprocessors has doubled every two years since the early 1970s. But it is now unanimously expected that the growth pattern will eventually turn into an S-curve and reach a ceiling. On page 63 of his book Kurzweil claims that Moore’s law is one of the many technological exponential trends whose knee we are approaching. But he also agrees that Moore’s law will reach the end of its S‑curve before 2020.

Moore himself says that “sometime in the next several years we get to some finite limits, but not before we get through five generations.” According to one study, the physical limitations could be reached by 2017.

Given that we are dealing with an S-curve, the slowing down in speed improvement must be gradual so that five generations may bring an overall increase with respect to today’s numbers by a factor smaller than 25 =32. But even if the factor is around 30, the position of the exponential knee translates to around 3% of the S-curve’s ceiling.

Based on the above three examples we can say that the knee of the exponential curve tends to occur at a threshold situated between 3% and 28% of the ceiling of the corresponding S-curve. This translates to a factor smaller than 30 between the level of the knee and the final ceiling. This factor is less than two orders of magnitude and has been estimated rather generously.

Let us then apply this knowledge to Kurzweil’s exponentials. 

On The Singularity

Armed with the knowledge that all exponentials will eventually turn into logistics and that the exponential knee generally occurs at the level of a few percent of the ceiling let us confront some of Kurzweil’s predictions.

1. Supercomputer Power

From the graph on Page 71 of Kurzweil’s book and assuming that the exponential trend will continue until 2045 (which I personally doubt) we find that computer power will reach 6x1023 Flops (floating-point operations per second) at “singularity time”. But from 2045 onward and until computer power reaches a final ceiling, there must be further growth of less than two orders of magnitude. This translates to an ultimate computer power of less than 1025 Flops, which is in flagrant contradiction with Kurzweil’s forecast of 1050 and beyond!

2. The Time to the Next Evolutionary Milestone

In my article “Forecasting the Growth of Complexity and Change” I related complexity to the inverse of the time intervals between evolutionary milestones. Kurzweil points out that this is not always true because while the time to the next milestone has been steadily decreasing complexity did not always increase. There have been occasional decreases in complexity between milestones, e.g., the mass extinctions.

I agree that immediately after a mass extinction the world’s complexity may seem reduced, but it is also true that the fundamental change produced by a mass extinction gives rise to all kinds of new mutations and species. By the next evolutionary milestone the complexity of the world is higher than it was before the catastrophic event.

In any case, whether one talks about complexity increase or its inverse, i.e., the decreasing time interval between evolutionary milestones, one deals with a growth process that seems exponential (as a function of milestone number) from the very beginning, i.e., the big bang. But like all natural-growth processes it will certainly turn into an S-curve sometime in the future.

And here again we are facing the same question. Will the process continue along its exponential path sufficiently long to “explode” (tantamount to a singularity) or will it turn into an S-curve sooner rather than later?  In my articles I argued in favor of the latter and not only because the quality of the S-curve fit was a little better than the exponential one (there are too many uncertainties involved to take these fits seriously).

But let us approach the same question via Kurzweil’s knee. He says that we happen to be around the knee of the exponential curve at present. The ceiling then of the corresponding S-curve should be less than two orders of magnitude higher (or two orders of magnitude lower if we are dealing with an upside-down S-curve—time to next event is getting smaller).

This places the midpoint of the S-curve at the 4th future milestone (canonical number #32). Future milestones will keep appearing at shorter and shorter time intervals but not indefinitely. The 1st future milestone should be in 13.4 years from Internet’s time (taken as 1995). By the 4th future milestone (25 years from Internet’s time) there will be a new milestone every half a year. But from then onward the frequency of milestone appearance will begin to slow down.

My logistic fit had positioned the midpoint of the S-curve at canonical milestone #27 implying an immediate beginning of the slowdown, and the 1st future milestone in 38 years from 1995.

The two estimates are in good agreement considering the crudeness of the methods. But they are both in violent disagreement with a singularity condition such as Kurzweil describes. 

3. Acceleration in General

Kurzweil positions the singularity in the year 2045. This is strongly dependent on the evolution of the performance of computational power, see earlier discussion. But independently of the earlier discussion, and if we make it to year 2045 at all, given that this date corresponds to the ultimate “knee” of the overall runaway exponential trend, one should expect a further increase in acceleration of no more than an additional factor of less than 100.

This factor of 100 is the upper limit of what should be expected for all trends that display an exponential “knee”.

In Summary

  • All exponential curves that represent a real growth process constitute part of some logistic curve.
  • The “knee” of an exponential curve defined as “the stage at which the pattern begins to appear explosive” represents a threshold of the order of at least few percent of the corresponding S-curve ceiling. Consequently, between the level of the exponential knee and the level of the ceiling of the S-curve there is a factor of less than 100.
  • Evolutionary milestones, as we perceive them today, will at some point begin to appear less and less frequently. This point in time is most likely between now and year 2045.
  • Despite an impressive amount of technological progress still remaining to be achieved, there is no convincing argument that a singularity of the Kurzweil type will ever take place.

My comments

Scientific sloppiness is a contradiction in terms. Kurzweil and the singularitarians are more believers than they are scientists. Kurzweil recounts how he agreed with a Nobel Laureate during a meeting, but I suspect that there is no Nobel Laureate who would agree with Kurzweil’s thesis. The #1 endorsement on the back cover of his book comes from Bill Gates whose scientific credentials stop at college dropout in junior year.

One Nobel Laureate, Paul D. Boyer—whose data Kurzweil uses when he makes his central point—has anticipated two future milestones very different from Kurzweil’s. Boyer’s 1stfuture milestone is “Human activities devastate species and the environment”, and the 2nd is “Humans disappear; geological forces and evolution continue.” I estimated above that the next milestone should be between 13.4 and 38 years from 1995. I suspect that there are many hard-core scientists who would agree with Boyer’s first milestone and my time estimates.

One could argue that Boyer is acting himself as a believer rather than a scientist in this case, and could be right. But Boyer does not go on to write a 650-page book on the subject. Maybe because it simply wouldn’t sell!

I must admit that I did not read Kurzweil’s book to the end. Around Page 150 I got fed up and stopped. There is a large collection of facts and references in this book and from this point of view the book merits a place in one’s library. But as science fiction goes, even realistic one like Kurzweil’s, I prefer more literary prose with plot, romance, and less of this science.

References

[1] T. Modis, Forecasting the Growth of Complexity and ChangeTechnological Forecasting and Social Change, 69.4 (2002) 377-404

[2] T. Modis, The Limits of Complexity and ChangeThe Futurist, (May-June 2003) 26-32.

[3] U.S. Census Bureau, http://www.census.gov/ipc/www/worldhis.html

[4] T. Modis, Predictions - 10 Years Later, Growth Dynamics, Geneva, 2000.

I wonder what 2014 will be like? I thought 2013 was going to finish in as boring and apathetic a manner as it began, yet suddenly everything seems much more exciting. People are finally waking up to the broken economic system, we’re on the verge of ending the drug war and Jesus H. Christ fucking anti-senescence, mind uploading and the whole god-damn singularity seems to be pushing it’s way into the public mindset. I didn’t think I’d be alive to see this day :3

An anti-conjunction fallacy, and why I'm a Singularitarian

An anti-conjunction fallacy, and why I’m a Singularitarian

When anyone talks about the possibility or probability of the creation/existence of an UFAI, there are many failure modes into which lots of people fall. One of them is the logical fallacy of generalisation from fictional evidence, where people think up instances of AI in fiction and use that as an argument. Another is how the harder a problem is, the faster someone solves it, without spending even…

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PESSIMISM AMONG THE SINGULARITARIANS: IS IT A BAD THING?

Have you heard? Robots are coming and they are going to steal our jobs!

I expect you have heard rumors to that effect, because the tech news seems positively awash with reports of automation replacing shop assistants, cooks, and much more besides. Is this necessarily a bad thing? Of course not. I, for one, think it could potentially be the best thing ever. It could finally deliver the future that John Maynard Keynes promised automation would bring about: A huge reduction in the number of hours people would be required to devote to a job, and a massive increase in the amount of hours per day that can be devoted to a life of leisure. And, no, a life of leisure need not mean everybody is transformed into a couch potato, spending their days ‘doing nothing’. People may well do very little except vegetate in front of the TV when ‘leisure time’ is just a couple of week’s vacation from the usual necessity of having to devote 40 hours of almost every day to some mind¬numbing activity, but once people are properly liberated from both jobs and the monetary and cultural pressures imposed on the unemployed to persuade them to rejoin the ranks of the wage slaves, and properly adjusted to the novel idea of boundless leisure, I predict a vast increase in the adoption of meaningful activity.

It occurred to me that not many ‘robots are coming for your job’ articles paint this event in optimistic terms. Instead, they tend to use phrases like ‘robots will steal your job’ and ‘employment is increasingly threatened by automation’. I devised a challenge that I posted on the Singularity Network Facebook page:

“I challenge you all to find ONE example of a news report about robots which does NOT feature a comment along the lines of ‘but there are concerns that these robots threaten jobs’ but DOES feature a comment along the lines of ‘there are hopes that the rising productivity enabled by these robots will free up more leisure time for people”.

I do not think this challenge would require too much work. It would not take much effort beyond googling ‘robots will free us’, ‘robots liberate us from jobs’ or some such phrase to see if somewhere out there on the Web there is indeed an essay that views the robot revolution in a positive light. But, so far, nobody has bothered taking up the challenge, instead using my post as an opportunity to make gloomy replies such as:

“The powerful would rather kill the masses than allow them to have leisure time”
and
“We have not benefited with “increased leisure time” or even “increased pay” from automation since the late 1970’s. Productivity has increased but salaries have remained flat. Most workers are being scammed, in a sense stolen from, but have no forum of redress”.

One comment even accused my challenge of “whitewashing the ugly truth; that technology is already taking more jobs than it creates, that it is creating more inequality, not less, and that our politics are unprepared to handle the inevitable increase of poverty resulting from it”.

I can remember a time when Singularitarians were a whole lot optimistic. The future was something to look forward to. It was not considered to be a dystopia with rising inequality transforming capitalist democracies into something resembling a neo¬feudalist rentier society like 18th¬century France, it was to be a glorious paradise on Earth with death conquered and SAI¬powered nanosystems and full¬immersion VR satisfying our every material desire.

So, what happened? Why do we not champion the idea that the future is going to be great anymore, instead preferring to issue stark warnings about how bad things are and how much worse they are going to get?
I would like to propose that ‘pre¬millennial Singularitarians’ have given way to ‘Post¬millennial Singularitarians’. Back when we were all super¬optimistic about the future, people like Max More were concerned that belief in inevitable better days ahead would lead to complacency:

“In the Western world, especially in millennarian Christianity, millions are attracted to the notion of sudden salvation and of a “rapture” in which the saved are taken away to a better place….I am concerned that the Singularity concept is especially prone to being hijacked by this memeset. This danger especially arises if the Singularity is thought of as occurring at a specific point in time, and even more if it is seen as an inevitable result of the work of others. I fear that many otherwise rational people will be tempted to see the Singularity as a form of salvation, making personal responsibility for the future unnecessary”.

As people like James Hughes have argued, this kind of passive sit back and wait for the inevitable techno¬rapture is comparable to pre¬millennial Christianity which held that Christians needed only to prepare themselves for salvation and paradise would be established for them. On the other hand, post-millennialists reckoned that Christians had to first turn back the tribulations and establish a kingdom of heaven on Earth. Only then would there be the Second Coming.

What no doubt greatly helped the post¬millennialists’ case is that the year 1001 came and Christ did not return. In fact, we are now well into the year 2015 and there is still no show from the big C.

Enough about that, though, what about the ‘rapture of the nerds?’. Obviously, my use of the word ‘millennial’ in ‘pre¬millennial Singularitarianism’ and ‘post¬millennial Singularitarianism’ has nothing to do with time spans of a thousand years and is instead a reference to passively waiting for paradise on Earth to be established, versus considering it necessary to actively prepare the way for such a transformation. However, I would like to propose that there is a date which perhaps has convinced many that the bright future we looked forward to was not quite as inevitable as we once thought. That year, is 2009.

What is so significant about that year? Well, it is the first year for which Ray Kurzweil offered predictions concerning technological change in his book ‘The Age Of Spiritual Machines’. The book was published in 1999 and, ten years later, we finally had the opportunity to test Kurzweil’s predictions against that ultimate judge, the reality of the year 2009. Some who did just that judged Kurzweil’s success rate to be pretty poor. For example, Alex Knap of Forbes wrote:

“Out of 12 key predictions that Kurzweil highlighted for the year 2009, only one has come completely true. Four were partially true (score them a half¬point each) and eight failed to come true by the end of 2011. That’s a score of 3 / 12 – or 25% accurate”.

Over on his ‘Accelerating Future’ blog, Michael Anisimov seemed just as critical, saying “So far, I haven’t seen Kurzweil straight¬up admit that he was wrong”.

I should point out that Anisimov certainly was not saying that Kurzweil got it all wrong, only that he had some misses as well as hits. Ascertaining exactly how many ‘hits’ versus ‘misses’ he got is actually kind of difficult because, as Ieet Spectrum put it, “Most of his predictions come with so many loopholes that they border on the unfalsifiable”.

Ray Kurzweil also pointed out that his predictions for 2009 were not actually for the year 2009 but rather the decade between 2009 and 2019, so we still have a few years left before we can really say how accurate a prophet of technological development Kurzweil really is (if, indeed, we can ever really say how accurate he is. That IEET Spectrum article argues that doing so will prove difficult).
But can people really be blamed for mistaking predictions for a decade for predictions of a specific year when the opening sentence of that chapter was “It is now 2009″? I could not find any caveat in that chapter along the lines of ‘do bare in mind that these predictions are for the decade of 2009¬2019 not just 2009′.

Whatever. The point I am trying to make is that, prior to 2009 Kurzweil was the infallible prophet who had shown us how the future was going to be and had the charts to back up his prophecies. Those exponential curves showed the pathway to technorapture was a smooth one with no obstacles in the way. After 2009 we began to wonder if whether the future Kurzweil promised was quite as inevitable as we had believed. Perhaps there were obstacles in the way of progress, after all?

Take ethical concerns over such things as genetic engineering. Kurzweil assured us that ethical opposition to such things was completely incapable of getting in the way of progress:

“These ethical debates are like stones in a stream. The water runs around them. You haven’t seen any of these biological technologies held up for one week by any of these debates”.

But in his book ‘Rational Optimist’, Mark Ridley painted a rather different picture:

“African governments, after intense lobbying by Western campaigners, have been persuaded to tie genetically modified food in red tape, which prevents them from being grown commercially in all but three countries”.

It would seem, then, that opponents to GM are not so powerless after all. If our opponents and others with a vested interest in preventing the establishment of the future we desire have the ability to delay or even prevent it, we cannot just passively sit back and wait for its inevitable emergence. We must instead keep our eyes peeled for possible impediments to progress and actively work to promote the establishment of the future we desire for ourselves and future generations. In that case, the pessimism which greeted my challenge is no bad thing. It shows that people are thinking about what could go wrong, not just taking the laid back attitude that a utopia is inevitable and all we have to do is wait for it to be established for us.

But, equally, too much pessimism could lead to a ‘we’re doomed so why bother?’ attitude. It is important to remember that, while the future may not be wonderful, it certainly could be. Oh, and as for my challenge, there are indeed some articles that look positively on the robot revolution. For example, a Wired article said:

“Assuming a post¬scarcity system of distribution evolves to peacefully and fairly share the fruits of robot-driven post¬scarcity production, jobs as we know them might not just become unnecessary—they might stop making sense altogether…By eliminating the need for people to work, robots would free us up to focus on what really makes us human”.

Perhaps Max More would be pleased to note that passive pre¬millennial Singularitarians are being replaced with a more skeptical breed of transhumanists who accept that there is much to be done before we can rest assured that such a future is inevitable?

* hero image used from irobot

PESSIMISM AMONG THE SINGULARITARIANS: IS IT A BAD THING? was originally published on transhumanity.net

Will science and technology save us?

Transhumanist initiatives and Singularitarians often refer to the latest results of research to prove that the world is increasingly getting better or even “the Singularity is near. Understanding research here is essential to avoid being biased and fooled by optimistic interpretations or alleged feasibility.

Singularity or Bust

Raj Dye:

In 2009, film-maker and former AI programmer Raj Dye spent his summer following futurist AI researchers Ben Goertzel and Hugo DeGaris around Hong Kong and Xiamen, documenting their doings and gathering their perspectives. The result, after some work by crack film editor Alex MacKenzie, was the 45 minute documentary Singularity or Bust — a uniquely edgy, experimental Singularitarian road movie, featuring perhaps the most philosophical three-foot-tall humanoid robot ever, a glance at the fast-growing Chinese research scene in the late aughts, and even a bit of a real-life love story.

For 45 entertaining minutes which invite to use the search engine of your choice, because it’s even more entertaining to find out what actually has happened in the last four years.

Delicious article on foggy and wishful thinking in Singularitarianism:

“But, my friend, if you are making a novel claim, the burden of proof is on you to argue that there are positive reasons to think that what you are suggesting may be true, not on the rest of us to prove that it is not. Shifting the burden of proof is the oldest trick in the rhetorical toolbox […]”

About CU

Continuity University offers a more sceptic view, not primarily towards technology itself, but to a specific attitude we adopt on technology these days [1]: Tech-optimism.

Especially in positions like Transhumanism and Singularitarianism an outspoken tech-optimism and confidence with exponential technological progress is a common convention. Their feed provides us with great inventions and attractive prospects that should improve our future lives – often in a way far beyond therapeutic purposes.

Continuity University calls thinkers, philosophers, artists, scientists, students and anyone who entertains reasonable doubt towards alleged feasibility and solely positive impacts of technological practice on humanity and environment.

Why CU?
It is a proof fact that with every invention the invention of it’s malfunction and accident comes along too (Paul Virilio, 2005). Therefore, the question is not only what we should do, but with no less urgency: How should we think and talk about tech in consideration of that?

Beyond this, Continuity University aims to focus and foster an often unattended force of self-transformation and cultural (ex)change: Art.

Hence, we distinguish between two basic types of Transhumanism:
“Tech-Transhumanism” and “Art-Transhumanism”


1 http://www.pewinternet.org/2014/04/17/us-views-of-technology-and-the-future/

Virilio, Paul (2005). The Original Accident (L'accident originel), Cambridge: Polity, 2007, p. 10.