Sustainable Energy Authority of Ireland have released their National Energy Projections 2024. In this they predict Ireland will have *2.6 more solar electricity generation capacity in 2030. And their optimistic estimate is 3 times more. Ireland has promised to install nearly 4 times more.
It is these peoples jobs to make these projections. and they know far more than I do about electricity generation. But I think they are wrong because of straight line continuing reasons
Below is Ireland's increase in Solar generation since 2017, the first year I can find data for. It increases by more than the 40% annual growth Solar has had world wide for decades
But say we slowed down to this 40% increase rate where would that leave us in 2030? We would have 10 times more solar than now. Not the 3 times SEAI predicts on the optimistic path.
Lots of things could interrupt Ireland's trend but 1. there are lots of planning applications for new solar farms. ' If all were developed, it would add a further 9.5 GW in solar energy to the grid,
surpassing our 2030 target of 8 GW'
2. We have promised to install 8GW of capacity so planning hold ups seem less likely
3. Prices keep dropping, and production keeps increasing. Solar installs in general keep surpassing expectations.
I think the SEAI solar predictions are too low and we are going to have over 10GW of solar installed by 2030. Instead of 2030 to have 5.7GW I think that will be 2 years time, by the end of 2026.
Prizes are a really good way of funding science but are not used enough. All sorts of prizes from longitude to private space have speed up technological development in their area.
Kaggle is an interesting example of current innovation incentivised using prizes. Kaggle defines a metric over a dataset and people try an build models that predict that well. This is then tested over another dataset to prove your predictions are the best. For not very much money a large number of very skilled people work on a defined problem for fun, kudos and the possibility of profit.
Typical Kaggle competition lasts 3 months, offers $25,000-100,000 in prize fund and attracts around 1000 specialists
At least top 10% of those specialists, ~100 persons are of prime quality, many others 'just' good.
Could a similar thing be done for discovering materials with properties we want? There are all sorts of problems that could be solved with materials with new properties. There are commercial incentives to develop many useful materials already. A more efficient solar panel or energy dense battery could have such commercial value lots of people are working on making them already. But some properties of materials are known to be useful but not commercialised yet to have huge competition or budgets trying to create them.
If we agree prizes are a useful incentive. And that we need new materials with useful properties how might a kaggle for such prizes work?
Kaggle has test datasets unknown to competitors held out to prove later which prediction model is best. For a materials version proving specific qualities in the lab would, initially, be too expensive. Relying on the scientific peer review process, of quality journals, would probably be enough initially. Occasionally issues in published materials research comes to light. But that happens in kaggle competitions too. And with prizes fairly low the incentives for shenanigans are not huge. Use a paper being published by a high quality journal as proof that a material has the defined property.
How long would the competitions be open for? The millenium prize for solving known big hard maths problems are open ended. Kaggle competitions are shorter a few month time periods. The time needed for journal papers to be approved and the difficulty of making materials means a year is probably more practical. Having a year competition timeline makes it more open to tinkerers than big grand ambitious challenges. I think 'A prize to someone who makes a wire room temperature superconductor at atmospheric pressure' is too ambitious. 'A prize to someone who publishes the warmest superconductor in a substance that can be turned into a wire by December 2022' is more practical. Competitions for improvements of a defined characteristic over a period of a year or two seem to be the best prize incentives to me.
How much would the prizes be for? Using journals keeps the cost of running the competitions low. But also means huge amounts of money cannot be involved. Also unlike kaggle a company putting up a dataset is not paying the prizes. The prizes would just be donated by people who can see that creating a product with these properties would be useful for improving our lives. As such a Patreon like model where donations are collected would probably be best. Stripe lets foundations setup as non profits set up these sorts of donations. Prizes would probably be in the 100K to -> 1 million range but initially to prove the concept would be much lower.
What would be a good initial material quality to test this Patreoned Kaggle for materials idea on?
You rent a Uhaul truck in New York to move to a new job in Texas. UHaul will be left with a truck in Texas. If people really want to go New York -> Texas but less so Texas-> New York they will reduce the price of the Texas -> New York. If you get all the prices to move one way between all the cities in the US you end up with a good idea of where people are moving. And as people usually move for jobs where the jobs are.
The idea I saw first in Marginal Revolution. This blogpost seems to be where the whole UHaul weighted graph idea came from. Dan Armstrong and Páll Hilmarsson
I took a list of the 34 most populous US cities (all over 500,000) from wikipedia. This is 1122 links in total. The 294 cities is 86142 total links. You only seem to be able to get containers not trucks from Honolulu, Hawaii.
This is a Complete graph where each edge has a length and a weight/capacity (price). some cities are really cheap to leave because enough people are moving (sinking) there that UHaul want to get the trucks back to the cities people are leaving (source)
The extreme costing trips are
The trips with the biggest difference between one way and another are
by price
Source
Destination
Round dif
Round ratio
San Jose, CA
Washington, DC
2404
2.3
San Francisco, CA
Washington, DC
2345
2.3
Philadelphia, PA
Portland, OR
2213
3
and by ratio
Source
Destination
Round dif
Round ratio
San Jose, CA
Las Vegas, NV
580
4.1
San Francisco, CA Las Vegas, NV 608 4.1
San Francisco, CA
Las Vegas, NV
608
4.1
Philadelphia, PA
Jacksonville, FL
1301
3.9
The spreadsheet with these calculation is here. the code to work all this out is pretty raw but it is here.
I will come back to this later and work out Eigenvalue Centrality and maybe how distance relates to prices. Also it would be interesting to see if some places are summer sinks and some winter sinks in a few months time.
What if you could emulate the brain the way we emulate computer worms?
C elegans is a 1mm long worm with 302 neurons, 3 Nobel prizes and has survived a space shuttle crash. It is one of the simplest animals and has been studied in massive detail. Like the fruitfly or ecoli anything these lab animals do that you cant explain you wont be able to explain in people either.
Whole brain emulation is a prediction that we will be able to simulate the brain in enough detail to create artificial intelligence very like us.
Robin Hanson on econtalk talked about the possible results of whole brain emulation. "This scenario, which we've called whole brain emulation--taking a whole brain and emulating it on a computer--requires three technologies. One is scanning--you have to be able to scan something in sufficient detail; have to see exactly which parts are where and what they are made of. Two, you have to have models of these cells, a model of the cell input signature and then what comes out of it as a mapping--doesn't have to be exactly right, just has to be close enough. Three, you need a really big computer. A lot of cells, a lot of interactions." Hanson blogs about brain emulation here. There are interesting fights about whether whole brain emulation is a reasonable prediction or just "the rapture for nerds".
Many biologists seem to think computer people are completely misunderstanding how complicated biological systems are and computer sciencey whole brain Emulation types say that biologists do not understand abstractions because they deal with this complexity all the time. '[Robin] Hanson’s fundamental mistake is to treat the brain like a human-designed system we could conceivably reverse-engineer rather than a natural system we can only simulate. We may have relatively good models for the operation of nerves, but these models are simplifications, and therefore they will differ in subtle ways from the operation of actual nerves. And these subtle micro-level inaccuracies will snowball into large-scale errors when we try to simulate an entire brain, in precisely the same way that small micro-level imperfections in weather models accumulate to make accurate long-range forecasting inaccurate.' is an example of the biologists argument against brain emulation.
'We should expect brain emulation to be feasible because brains function to process signals, and the decoupling of signal dimensions from other system dimensions is central to achieving the function of a signal processor.
"We can do trend extrapolation and say: Where are we now; if trends continue how long would it take? The computing technology has a nice solid trend; we can project that pretty confidently into the future. The problem is we don't really know how detailed we're going to need to go into these cells. The scanning technology, we have decent trends. This is a vastly smaller industry; small demand. That technology actually looks likely to be ready first. We've actually done a scanning of a whole mouse brain at a decent resolution. A thousandth smaller than a human brain. What does that mean--scanning of a brain? They slice a layer, do a two-dimensional scan of that layer at a fine resolution, go across each cell, and then they slice another layer and do the same thing again. Let me ask again, sort of naive question: If you could take a person's brain out of their head while they were still alive, are you going to be able to get access to my memories in this process? my creativity? All these things we think of as more than a physical process, but of course as you say, it's just chemicals interacting. Is it imaginable that we would be able to reconstruct my memories? To the extent we are confident that your memories and personality are encoded in these cells and where they are and how they talk to each other, so we get that right, we get it all right. That's all you are. Let me say it differently. Looking at it isn't enough. Scanning means noticing the chemical densities. There's thousands of kinds of cells in your brain, and each cell sort of behaves a bit differently. What we need is to know when a cell gets a signal from the outside, electrical or chemical signal, how does that change a cell and what kind of signal does it send out. So, we need to have a model of each of those cell types. We have, actually, models of a wide range of cell types. Doesn't seem that hard to model these cells. We just have a lot of cells to go through and not that much motivation to do it all in a rush. We have actually pretty good models of some particular cells. We have a cell on a dish, we send a signal in, model on the computer, do the same things."
Both sides here. The brain is really complicated squishy stuff and the simcity looks like a real city if you squint sides here could be right. I want a comparison of the predictions of these two theories now and not in 2040 though.
If we had Hanson's 1,2,3 met for an organism and we were not emulating it that would seem to be a problem for the theory.
One is scanning--you have to be able to scan something in sufficient detail;
The c elegans connectome was mapped in 1986 Two, you have to have models of these cells, a model of the cell input signature and then what comes out of it as a mapping--doesn't have to be exactly right, just has to be close enough. There are not many types of neurons in c elegans so we should have a fairly good model of when they will fire.
Three, you need a really big computer. A lot of cells, a lot of interactions." How big a computer would you need to model all these cells and interactions?
In When will computer hardware match the human brain? Hans Moravec (1997) gives some nice graphs of how much processing you get for $1000
This puts the amount of processing available to a C. elegans at about 1990 levels for $1000. So in 1986 that processing power would have easily been available to university researchers. Maybe that graph is optimistic but if it is out by 25 years for something as simple as c elegans that means predictions of whole brain emulation by 2050 also on the graph will be out as well.
For the last 25 years we have had the power to emulate the whole brain of C. Elegans. Why haven't we?
1. We have not actually because our neuron firing models has not been accurate enough 2. No one cares about emulation fo a worm. A lot of people care about this worm the numbers of neuroscience papers on it confirm this. 3. They are just a bit delayed. There is a thread here on less wrong about this an open source project openworm* 4. It is hard to get output from a worm 'Our first goal is to combine the neuronal model with this physical model in order to go beyond the biophysical realism that has already been done in previous studies. The physical model will then serve as the "read out" to make sure that the neurons are doing appropriate things.' Pixar, special effects companies and computer game programmers must have fairly good worm emulation programs. If there is a big problem making an animal bodies simulation surely one of them could easily enough make a good model of a tiny bag of gunk?
'Whole Brain Emulation A Roadmap' acknowledges the gap that exists in our emulation of the animal and suggests alternatives ' While the C. elegans nervous system has been completely mapped (White, Southgate et al., 1986), we still lack detailed electrophysiology, likely because of the difficulty of investigating the small neurons. Animals with larger neurons may prove less restrictive for functional and scanning investigation but may lack sizable research communities'
Why 25 years after having a good map and enough computation to run the calculation have we not emulated C Elegans? If it is the modelling of the cells 'I have talked several times to one of the chief scientists who collected the original connectome data and has been continuing to collect more electron micrographs (David Hall, in charge of www.wormatlas.org). He has said that the physiological data on neuron and synapse function in C. elegans is really limited and suggests that no one spend time simulating the worm using the existing datasets because of this. I.e. we may know the connectivity but we don't know even the sign of many synapses.'
The openworm project is really cool. and it might be a good way to get some evidence into the whole brain emulation debate now.
'The problem is we don't really know how detailed we're going to need to go into these cells. '
If Ken Hayworth is right and it is just that 'He has said that the physiological data on neuron and synapse function in C. elegans is really limited' is this because the biologists are right and step 2 the cell models will not be as easy to build as supporters of whole brain emulation claim?
These is a project here to emulate C Elegans. And a good paper here on the problem involved Dynamics of the model of the C Elegans neural network. Just in time to make me look more stupid is A Worm's Mind In A Lego Body. It is not full emulation yet but it is at lest on the path there.
* An article from Popular Science on Whole Brain Emulation here that made me resurrect this post I drafted two years ago. Since then the openworm project has moved on massively.
Drones have become wildly popular recently. They seem to be on the path of military, geeks, specific industries ->everything that successful tech seems to go through. It seems likely that large numbers of small deliveries will take place by drone in ten years time.
One thing that damaged bird sized tech in the past was hawks. Jon Bentley described in 'More Programming Pearls'
The computers at the two facilities were linked by microwave, but printing the drawings at the test base would have required a printer that was very expensive at the time. The team therefore drew the pictures at the main plant, photographed them, and sent 35mm film to the test station by carrier pigeon, where it was enlarged and printed
photographically. The pigeon's 45-minute flight took half the time of the car, and cost only a few dollars per day.
During the 16 months of the project the pigeons transmitted several hundred rolls of film, and only two were lost
(hawks inhabit the area; no classified data was carried). Because of the low price of modern printers, a current
solution to the problem would probably use the microwave link.
Hawks and other birds of prey taking issue with these noisy (for now) airborne intruders into their territory. Everyone was worried about people below shooting them down, but it turns out there may be another threat that can’t be so easily policed; outlaw avians....A delivery drone that takes its shape and forms that outline in the sky will not be attacked by a lesser predator, even if it’s not already wired into their genetic memory
The article suggests creating drones that look like very big hawks to discourage natural hawks from attacking them.
This effect doe not just apply to birds of prey though. Prey species hide when they see the outline of a bird of prey. And doing this increases their anxiety enough to reduce feeding and decrease numbers drastically over time. The drones that look like birds of prey will not have to prey. Just being in the sky with the right silhouette will drastically reduce the number of vermin.
Changes to ecology have unpredictable effect on the environment. Less pigeons would seem an improvement to the urban environment but they do eat bread and other foodstuffs. If numbers are reduced enough to prevent this bad things could happen.
tldr: 1. there will be lots of drones 2. They will look like birds of prey 3. They will have a big effect on rats, pigeons and other prey species.
In what year will the most farmers ever be working? We reached peak baby in 1990 and peak manufacturing employee slightly later.
Mass employment in manufacturing just isn't coming back 'I estimate global manufacturing employment to have been between 150 million and 200 million workers in 2002, with those numbers reflecting a global decline of 20-30 million manufacturing employees in 2002 compared to 1995.'
You can never tell exactly what the future will hold but with the increasing use of robots points to reduced manufacturing jobs for example "Foxconn to rely more on robots; could use 1 million in 3 years". Agricultural employment as a percentage of total employment has been declining since the industrial revolution. The percentage of Americans employed in agriculture has dropped from over 90% at the time of the American revolution to around 2% now for example.
The UN says peak rural population will be sometime between 2020-2025. "However between 2020 and 2025, the total rural population will peak and then start to decline," and "Global rural populations will peak in the 2020s, leading to mass abandonment of rural lands.(Data Source: UN Dept. of Economic and Social Affairs, Population Division)". Not all rural people are farmers and I think the proportion of farmers amongst rural dwellers is decreasing. If the figures of peak rural population being sometime 2020-2025 then that means the most farmers that will ever be living will occur sometime before 2020.
The first time in human history since the agricultural revolution that most people were not employed as farmers would have been some time before urban population passed rural population. The World Population Becomes More Urban Than Rural in around 2007 so we are not long past the majority of people being farmers. 'Agriculture still accounts for about 45 per cent of the world’s labour force, or about 1.3 billion people' according to this 2007 report. Until recently most people were farmers.
The world continues to urbainse, farms continue to mechanise and population continues to rise slower than it used to. All this means that sometime before 2020 farming will become globally a declining employer. If total farming and manufacturing jobs are declining and transport jobs could do the same soon that means we will have to find new things for people to do.
This prediction of declining numbers of farmers globally sometime around 2020 is one that someone with better google foo could disprove quickly, if you can please correct me in the comments.
This is a post where I do a back of the envelope estimate of when we'll see driverless cars, what will they do to taxi costs and what will that do to unemployment.
There are several estimates to when driverless cars will arrive. The New York time estimates 2020.
Self-Driving Cars By 2030, Sebastian Thrun predicts, more people will use self-driving cars in their daily commute than manually driven cars. Submitted by Sebastian Thrun, developer of Google’s self-driving car. Our readers predict this will occur around 2020, having moved this date 1381 times.
Many similar bets of Driverless cars being regular enough in 2020 and ubiquitous in 2030 exist for example here,
By 2020 - Driverless cars are commercially-available and street-legal somewhere in the United States. By 2027 - New driverless cars outnumber new cars requiring at least some human control, in the US market.
In my post last week, my commentors took me to task on my prediction that cars will drive us in ten years. Some thought Americans would wise up and learn to love mass transit. They don't know Americans.
Others thought the hardware cost would even in ten years remain out of reach. Google did not build an autonomous car by creating the hardware but by harnessing and training good machine learning algorithms. No amount of hardware would have given you a car able to navigate the streets of San Francisco five years ago.
What effect will these cars have? There are all sorts of ideas about how they will alter parking and car ownership. I'm going to try do a back of the envelope here on how much Taxi fares will cost if you don't have to pay the driver.
For each additional 1/6th of a kilometre or time 28 seconds)
(a) Day time 8am to 10pm €0.15 (b) Night time 10pm to 8am €0.20 (c) Sundays, Public Holidays, Christmas Eve and New Year’s Eve €0.20
Ignoring the pick up costs of about 3.40.
The AA says it costs around 25 cent per kilometer to drive a car in Ireland. About 25 pence per mile in the UK. Taxis charge 1.20 so the majority of the cost looks like the driver. You would have extra costs on top of a normal car with a commercial vehicle. But given the pick up costs a driverless taxi could be about a quarter the cost of a taxi with a driver. The price elasticity of demand should allow an estimate of how this will alter taxi usage. This paper "Estimation of Price Elasticity for Taxi Services in Hassel" gives a PED of -2.644. Though others such as Schaller at -.22 and here of -.6 shorter term. Taxis that cost a quarter the current price with a PED of -2.6 would mean about ten times the number of taxi journeys. The long term viability of public transport should take this possibility into account. If by 2030 people will be taking ten times the number of taxi journeys would enough people be using Metro North to make it cost effective?
Transport employs nearly one hundred thousand people in Ireland. Which is about 1 in 20 people who have a job here. Or about a third of the number of unemployed. I doubt everyone who works in transport will lose their jobs overnight. But taxis provide an example of how economic effects could provide a huge incentive to move to driverless cars. So far technological progress has always eventually resulted in new jobs to replace old lost ones. The money people save getting into town for a night now could end up being spent in town and require more employment in restaurants and bars for example.
But I think it is worth considering the possibility that fairly soon we could have nearly a hundred thousand people who earn a decent wage at the moment becoming unemployed in a short period of time. Construction lost 160 thousand people in three years. Transport jobs do not pay as well as construction did. But if the construction change caused most of our current economic issues it would be unwise to ignore a large sudden future change in transport employment.
To put some skin in the game, I am predicting that in 2025 in a period of three years we will see structural unemployment of about 5% of the workforce, half of those that work in transport.
I mentioned in this post on 2030 that I expect Polio and Guinea worm to be eradicated by then. It becomes a tricky issue when a disease gets really uncommon how you find and treat the last few cases? So far only smallpox and rinderpest have been eradicated. Eradication is great because once its done its done. You would not have to immunise every child for polio any more. Every polio vaccine has a small cost and risk and once thats gone you can go spend the money on something better
Alert the government on the occurrence of new cases of certain ailments and you may get a cash award! The government has targeted vaccine preventable diseases such as diphtheria, pertussis, measles, tetanus, and leprosy for elimination by 2016. India is also on the verge of being declared polio-free. District medical and health officer Dr G. Srinivasulu explains that even after being declared polio-free, there should not be a single new case for 14 consecutive months in the country. This is where the reward comes in. “If anybody succeeds in detecting a new polio case meanwhile, the government will give a cash award. Even in case of detection of new leprosy cases, ASHA health workers are given Rs 150-Rs 200,” he said.
A team from the Massachusetts Institute of Technology won $40,000 in a high-tech scavenger hunt on Saturday by discovering the location of 10 red weather balloons.
"We're giving $2,000 per balloon to the first person to send us the correct coordinates, but that's not all -- we're also giving $1,000 to the person who invited them. Then we're giving $500 whoever invited the inviter, and $250 to whoever invited them, and so on..." it said.
Some similar system that set up a chain of reward could be really useful in disease eradication. Many security protocols rely on a sort of iterative proof of trustworthiness. Something similar could be used to allow steps toward eradication without fear some other country is going to stop efforts.
Assurance contracts are another approach. It is possible that some regions are scared that once a disease is eradicated to their area they will lose funds. Some way to guarantee that funding will not reduce or to reward successful eradication might help here. Something like Dominant assurance contracts might help to change incentives to encourage eradication.
How about a guarantee fund for each of the remaining countries with polio and guinea worm that when who declares them free they get some cash bonus. You could imagine a kickstarter project that gave the minister of health in Nigeria money when polio was declared eradicated from the country.
The juice of the carrot, the smile of the parrot A little drop of claret - anything that rocks Elvis and Scotty, days when I ain't spotty, Sitting on the potty - curing smallpox
We want to discourage deliberately being lax about a disease so you have to be clever about incentives. Anyone have any good idea for how you could bribe people and governments to further incentivise disease eradication?
I have no idea what will happen to the euro in the next month. And whatever happens will have big consequences. Yet I was willing to make predictions for 2030 about lbr, driverless cars, solar power and education in my last post.
The thing is I think I am cheating with technology predictions. Theres a wildly unpopular branch of Marxism that argues for technological determinism. Marx can be interpreted as saying that our technology is inevitable and will change us in unavoidable ways. "The windmill gives you society with the feudal lord: the steam-mill, society with the industrial capitalist"
After reading "What technology wants" by Kevin Kelly I am a convinced technological determinist. There is a podcast from Kelly on technology at econtalk
The book makes a compelling case that
1. You cannot shut yourself off form technological change. The Japanese tried it and failed. The Amish dont try it, they stay about 50 years behind on average but they do not avoid new technology forever.
2. No technology ever dies out.
3. Each new technology is an inevitable consequence of the last. No one person of country can cause or prevent a new technology, though they can shape its exact form.
Almost all patents of significant technologies have multiple very similar independant patents lodged at nearly the same time. Airplanes, radio, transisters, computers, television whatever you can think of about three guys thought of it and implemented it independantly within a few months of each other. This suggests that once the right prior technologies exist the next one is inevitable.
Keynes wrote about 2030 in 1930 in the article “The Economic Possibilities for Our Grandchildren.” which has been surprisingly on accurate for the last eight decades. So I am betting it will continue to be for the next two. He made brought claims about future growth rates that have been accurate. I will make similar claims now. Given that I dont think non technological predictions can be made I am going to try anyway 1. Grinding poverty will be gone. This is a low bar of 365 dollars a year in 1990 dollars. Thats really bad. Much worse than medieval England but it is one I think we can reach.
3. World population will be slightly lower than the medium UN estimate of 8321380. The high is 8776486 and the low is 7867332. So I will guess 8250000.
This is just a few predictions based on the world continuing to go the way it has for the last two hundred years. But like I said I cannot predict what will happen to the cash in my pocket over the next two months so two decades away is being ambitious. If you have any predictions for 2030 please put them in the comments. It might be fun for the floating brains in a jar to laugh at them at the time.
Loads of brilliant technologies went mainstream this year. Some new technologies were created but I don't know enough about any of them to make claims for their future. I'm going to describe what I think these old but newly well known technologies mean in reference to the world when my new daughter is 18 in 2030.
Learning by reading Watson came along from IBM and answered quiz questions really well. Siri did something similar with peoples requests.
This might not seem like a big deal. Not many of us make a living answering quiz questions. But how many of us have jobs that involve finding the right page based on some search and parsing out the right bit of text? A surprising amount of medicine, lawyering, general office power point monkeying involves this. What happens when a cockroach knows everything? Watson is the answer to that as that is about the actual intelligence level it has. What happens when in 2030 the cockroach is a thousand times smarter? I have no idea.
Depressingly most of these systems seem to be owned by big companies like apple, Google and IBM. Most of the data used and the tools that analyseit are open source. It will be a really cool project when someone makes an opensource wikipedia based answering bot.
"if, in like manner, the shuttle would weave and the plectrum touch the lyre without a hand to guide them, chief workmen would not want servants, nor masters slaves." Aristotle wrote in Politics which says that smarter machines will free us from servitude. So far this has been the case but will that continue?.
Driverless cars
Will my daughter ever drive for non fun reasons? People will always drive the same way people still ride horses. Just now they do it for fun rather than transport. Two trends are making it less likely that my daughter will ever have a drivers licence. The increasing sophistication of driverless cars and our decreasing acceptance of the idiocy of youth.
If Ferris Bueller had a day off now, would he spend it on Facebook? Because cars are relatively more expensive and relatively less exciting teenagers are less inclined to drive now. Facebook and youtube provide entertainment for free so you are less inclined to work thousands of hours so you can afford a mildly entertaining car. Cars are now only mildly entertaining as safety nazis have turned them all into a homogenous look that cannot even be modded easily. If you cannot put a spoiler and underlights on your Clio your just not going to look cool as a 17 year old.
Combined with cars being less attractive to teenagers there is increasing control placed over them. New drink drive limits for learners have been imposed here. I have heard talk of curfews for young drivers. We are less inclined to accept the god given right to load a car with 7 of their mates and wrap it around a tree at 4 in the morning. In 2030 well have so many constraints on teenagers to prevent them killing themselves as to remove much of the attraction from driving.
The technology element of this is the driverless car
Hanson wrote
So a huge upcoming policy question is: when will what big cities manage to coordinate to change road law to achieve these huge auto-auto economic gains? Thirty years from now we may look back and lament that big city politics was so broken that no big cities could manage it. Or perhaps history will celebrate how the first big city to do it dramatically increased its importance on the world scene
Cowen said
The typical American spends an average of roughly 100 hours a year in traffic; imagine using that time in better ways — by working or just having fun. The irksome burden of commuting might be lessened considerably. Furthermore, computer-driven cars could allow for tighter packing of vehicles on the road, which would speed traffic times and allow a given road or city to handle more cars
These technologies will come in gradually drive train technology, lane assist, parking assist, crash avoidance are all present in next years s-class Mercedes. Probably legal hangups will delay driverless cars. If I was to guess it will be the old that get them pushed through. The old are increasing in numbers and will continue to vote. The baby boomers won't accept the loss of independence that goes with not being able to drive currently. Legal changes to allow driverless cars could be a vote winner. I'm willing to bet that by 2030 a combination of our scardy-cat nature about risk, the grey vote and improved technology will mean that my daughter may never have to drive.
Solar Power
The exponential improvement in solar power became news this year.
Averaged over 30 years, the trend is for an annual 7 percent reduction in the dollars per watt of solar photovoltaic cells...10 years later, in 2030, solar electricity is likely to cost half what coal electricity does today
Education Education has not changed much in a long time. This is partly due to Baumol's cost disease where a teacher now can only teach the same number of kids as one in 1900. Since that time manufacturing jobs can produce vastly more than they used to. But education is one of those human centric industries that has not changed much.
Since videos came out it has been possible to watch lectures at home. Just giving kids computers does not improve education. If you look at the list here of the best educational strategies Tutorial instruction, Reinforcement, Corrective feedback, Cues and explanation are now part of online educational programs.
Stanford this year ran three computer courses where anyone can sign up for free, get homework graded by computer and do exams at the end. This is a graduate level course in one of the worlds best universities for free. The Khan academy has been around for a while but this year it moved from just a list of videos to include problems. The site is now using machine learning and gamification techniques to improve these problems and thus student learning. They are also using statistical tests to improve the website layout and which version of a explanation gets used. These computer assisted techniques are even being used by humans to get better at Jeopardy as the video below describes.
Interestingly the same guys who got learning by reading and driverless cars to their current state are also important in these changes to education Sebastian Thrun, Andrew Ng and Peter Norvig. This year technologies became mainstream that finally turn computers into the amazing educational tools they have always promised to be.
Comparison How did these areas change from when I was born till I was 18?
Cars became safer and drink driving became mildly uncool. The main change here was removing lead from petrol though. The recent drop in crime and increase in IQ may be largely due to removal of leaded petrol. I think driverless cars are important but not as important as this.
Power generation changed a bit, Chernobyl made nuclear uncool but it was probably never economical anyway.
Education did not change much. I did example questions from the year I was born to practice for the leaving cert. Corporal punishment still existed in my time but mainly for nostalgia rather than because they got true joy battering children. I was born after the education system demilitarized. I predict education will change more in my daughters childhood than mine.
Computers did not really visibly exist for people when I was born. By the time I was 18 it was obvious they were going to change the world even if they had not fully done that yet. I think the change from no computers to some was bigger than useful computers to really useful ones that I predict will happen.
Here is the prediction in 2030 for the technologies that became public this year. Many of the cars will be driverless. The world will get a most of its new generational electrical capacity from solar. Education has already changed massively this year just people have not realised it yet. We will each have an assistant that knows everything. I don't know how that will effect employment, my guess is she will end up working in a job that does not exist at the moment.
I've wondered for a while about how far away we could see the earth if we were using our current technology and we had our current light output. At what distance could we see the artificial light the earth produced?
Existing optical telescopes and surveys can detect artificially illuminated objects comparable in total brightness to a major terrestrial city at the outskirts of the Solar System ... For this signature to be detectable, the night side needs to have an artificial brightness comparable to the natural illumination of the day side. Clearly, the corresponding extraterrestrial civilization would need to employ much brighter and more extensive artificial lighting than we do currently since the global contrast between the day and night sides is a factor ∼ 6 × 10^5 for the present-day Earth
Lets ignore that our telescopes will get better (about 2.5% a year?) so how quickly at current rates will the earth take to be this bright?
“over the last three centuries, and even now, the world spends about 0.72% of its GDP on light. This was the case in the UK in 1700 (UK 1700), is the case in the undeveloped world not on grid electricity in modern times, and is the case for the developed world in modern times using the most advanced lighting technologies.”
But what is that in terms of extra light produced? "In 1700 a typical Briton consumed 580 lumen-hours in the course of a year, from candles, wood and oil. Today, burning electric lights, he uses about 46 megalumen-hours—almost 100,000 times as much."
So that means if we grew at the same rate we have for the last 300 in about 300 years we will be producing enough light that if it was all shone out into space the earth would be as bright at night to an outside observer as it is in the day. I dont think you can make projections this far and it still leaves the question of how long after that ambient external light would be that bright. Still I think its interesting that even with current detection technology as civilisation the 300 years advanced from us would be nearly visible to us. I would guess this prediction will reduce but 300 years is my first estimate to when we could see ourselves.
Population surge difficult to halt and almost impossible to reverse was published yesterday in the Irish times. It is also availible in blog form here. The article makes some interesting and arguable claims about human environmental damage to the planet. These are based however on claims about human population that do not match the evidence or the UN's demographic predictions.
Today, just like every day for the last 50 years, around half a million babies will be born.
This is not true the figures from the UN are here. In detailed indicators look in births and in select country look in world. Between 1960-1965 302136 babies were born each day. Between 1985 and 1990 375909 babies and between 2005 and 2001 367320 babies. The 500000 figure is not just wrong but drastically wrong.
The geometric nature of population growth makes it extraordinarily difficult to arrest, and almost impossible to reverse. The last population doubling took only 40 years. Even if global population growth rate drops to just one per cent, today’s seven billion would swell to an unimaginable 14 billion in 70 years.
The growth rate is being arrested. As I have said before in "We have reached Peak Baby" the number of children each woman has has been falling for decades.
Though surprisingly accurate population estimates get better over time. For example the 2050 estimate has been recently honed in
U.N. Raises “Low” Population Projection for 2050 The "low-variant" scenario of population growth now foresees 117 million more people on the planet in 2050 than it did two years ago. While the "median-variant" scenario, often seen as "most likely," remains almost the same as before - predicting a world with 9.2 billion people by mid-century ... The high projection, however, foresees some 10.5 billion people - a 295 million person decrease from the previous high projection. The medium projection is 9.2 billion people,
It says something that an decline in the high estimate an over 2.5 times bigger than the increase in the low estimate is not the headline.
There are still countries that have very high birth rates per woman. Senegal for example had 7.5 babies per woman in 1968 4.8 babies and in 2010. But these countries are developing at a speed that is likely to see these birthrates drop rapidly. "Senegal has lower borrowing costs than Ireland." and a GDP growth rate of 4.2%. As these countries that still have a high birthrate develop their birthrate will drop rapidly the way ours and other developed countries did.
The article is in the Irish Times gives the wrong figure for the number of births per day and "unimaginable 14 billion" scare figure. The demographic evidence and historical trends indicate the population will not go to this level. Current UN estimates are for the high population prediction do not match this figure for 2081. There were never that many babies born per day and the birthrate has been falling so fast that we will not reach the 14 billion in 2081 figure.
How quickly are humans getting better? We tend to think technology is getting better or that humans augmented by technology are improving. New swimming records happen regularly as swim suit technology improves. This post just throws up some evidence about human progress.
The Effect of Testing for Performance Enhancing Drugs on the Progress of World Records in Weightlifting “From 1964 to 1988 the relative strength of the world record holders in those weight classes increased by 21% …The same analysis in other types of sports, where there had been some changes in training methods over the same period of time, revealed that the maximum improvement was only 9%“ So most improvement in weightlifting seems to have been from pharmacological rather than having a wider range of people to select from or improved training mechanism reasons. However what about areas of human endeavour that drug taking seems unlikely to help?
In chess taking steroids seems unlikely to help. Though future nootropics might. "We conclude that there has been little or no ‘inflation’ in ratings over time—if anything there has been deflation. This runs counter to conventional wisdom, but is predicted by population models on which rating systems have been based…The results also support a no answer to question 2. In the 1970’s there were only two players with ratings over 2700, namely Bobby Fischer and Anatoly Karpov, and there were years as late as 1981 when no one had a rating over 2700 (see [Wee00]). In the past decade there have usually been thirty or more players with such ratings."
Even musicians are getting better Virtuosos Becoming a Dime a Dozen "The overall level of technical proficiency in instrumental playing, especially on the piano, has increased steadily over time." One good explanation for this and the chess improvement is just that more people are getting to try these, people who are not as limited by nutrition and disease as they would have been int he past.
"But the pipeline that selects and trains runners behaves, in some ways, like the model. If a person with record-breaking potential is born in Kenya, where running is the national sport, the chances are good that he will be found, he will have opportunities to train, and he will become a world-class runner. It is not a certainty, but the chances are good.
If the same person is born in rural India, he may not have the opportunity to train; if he is in the United States, he might have options that are more appealing.
So in some sense the relevant population is not the world, but the people who are likely to become professional runners, given the talent. As long as this population is growing exponentially, world records will increase linearly.
That said, the slope of the line depends on the parameter of exponential growth. If economic development increases the fraction of people in the world who have the opportunity to become professional runners, these curves could accelerate."
Progress of things like number of children suffering malnutrition and having clean water can really result in increasing the number of great chess or piano players as well as the world running record. We are getting better at loads of things because more people are getting to try them without the poverty induced hinderances they used to have. According to this model it is not that population is increasing exponentially but at the moment population of people who have a chance at being great at something is.
If you have other explanations for why and in what human achievment is progressing I would love to hear them.
I saw this paper 'Austerity and Anarchy: Budget Cuts and Social Unrest in Europe, 1919-2009'
with the intro
'In the wake of this week's London riots, some commentators have linked the youth unrest to budget cuts. The authors of CEPR DP8513 explore the historical basis for this view and finds that austerity and violence have tended to go hand in hand.'
I am reading through the paper now. But I wonder if there was an image that could quickly show a connection between the two.
1958 Notting Hill race riots
1970 Garden House riot
1971 Priestlley riots
1975 Chapeltown race riot
1977 Battle of Lewisham
1980 St. Pauls riot
1981 England riots · Brixton riot · Chapeltown race riot · Toxteth riots · Moss Side riot · Handsworth race riots
1985 Brixton riot · Broadwater Farm riot
1987 Chapeltown race riot
1989 Dewsbury race riot
1990 Strangeways Prison riot · Poll Tax riots
1991 Meadow Well riots
1995 Manningham riot · Brixton riot
2001 Bradford riots · England riots · Oldham race riots · Harehills riot
2005 Birmingham race riots
2010 UK student protests
2011 London riots
Now if you look at the government spending as a percentage of GDP here. On top of this graph I put a bar for every riot each year one occurred.
Counting all riots as the same is not fair. Their graph goes from 34->48 whereas the riots go from 0->6. Laying the first on the second is not considered good practice in data visualisation. Also and this is a big one. If GDP drops as in a recession and the percentage of government spending to GDP stays the same total government spending will drop. a fairer graph would look at gdp or government spending adjusted compared to riots not the two combined.
The proper paper says rioting and austerity go hand in hand. I will read it carefully to see how close the link is. But a quick look at the data and no obvious major link jumps out at me.
When will we reach peak babies? In what year will the most children be born? I bet last night a shiny pint that we will reach peak babies in the next three years. That the most babies ever born will be in a year before 2015.
Now I accept that we could never actually know how many children will be born in the future. The bet will end when I present enough evidence to convince those I am betting with rather than with a proof. Demographics is regarded as one of the most predictable of social sciences but some possible future invention could drastically increase the number of babies. We could have brave new world style artificial wombs of some such that vastly increases the birth rate for example.
Hans Rosling the statitician tweeted recently. I looked up the UN data on this here. In detailed indicators look in births and in select country look in world. The highest birth number in the world was 1985-1990 Period Births per year 1950-1955 97 769 1955-1960 102 894 1960-1965 110 280 1965-1970 118 200 1970-1975 121 715 1975-1980 120 676 1980-1985 129 088 1985-1990 137 207 1990-1995 134 960 1995-2000 132 473 2000-2005 131 644 2005-2010 134 072 2010-2015 135 775 2015-2020 135 396 2020-2025 133 800 2025-2030 132 452 2030-2035 131 991 2035-2040 132 099 2040-2045 131 926 2045-2050 131 127 2050-2055 129 904 2055-2060 128 785 2060-2065 127 998 2065-2070 127 402 2070-2075 126 725 2075-2080 125 823 2080-2085 124 775 2085-2090 123 753 2090-2095 122 837 2095-2100 121 992 Now it could all of a sudden rise up and any prediction for the future is unlikely to be as accurate as historical estimates. Still I think I win the bet.
This does not mean that population will drop. As we are living longer world population is still expected to grow. But it does mean we can say that Malthus was wrong. Human numbers will not grow exponentially barring some disaster.
This week I was lucky enough to visit the Analog Computer Museum near Frankfurt. Bernd who owns and protects the collection I have known for years via email so I was happy out to finally get to meet him and his wife. These Analog computers carry out calculations using electronic components.
Bernd works as a software archeologist. That is he updates the systems of banks and such that are written in OS' and languages that almost no one knows anymore. If the software running your bank was written int he 60's and you want to get it running on Linux Bernd is the man to call. These languages are so obscure they make the COBOL look like the Beatles. The job seems to pay well enough as he can afford warehouses to keep his computer collection in and a collection of vintage sports cars he drives at terrifying speeds on the local autobahns.
Yes I take my wife to Computer Museums but in fairness shes a physicist and I suspect she thought this rocked as much as I did
These machines are ideal for real time simulation. This Telefunken currently simulating a car was used to train nuclear powerstation operators with simulations of various 'problems'
Next time you call rand() think of this board that was used to generate random numbers through electronics
Old school fractal printed out and taped to the side of a Vax. It is like chalking up a kill on the side of a WW2 fighter plane. Computing from the time where men were men and debuggers were nervous.
I cannot rationalise why these analog computers are so cool (pics here). I think its to do with getting to the bare metal of a computation. Also something of the history of these machines is amazing. Looking at the circuit boards you can imagine national characteristics they describe. The German machines based on mathematical abstractions are beautifully clean (and easy to fix apparently). The Japanese machines were a mess like their remote controls. The British machines had a distinct boffin feel to them. The machines from communist countries really seems like a scramble of clever but under resourced hacks. The American machines were big brash and heavy.
What happens is that most technologies become obsolete, diminish their role, but they don't disappear--more idea-based and can be resurrected more easily. Seems like a silly claim: the hand-axe, the arrowhead--they don't exist any more. And that's what I thought too... Looking on the Internet was able to find an example of whatever the challenger had given to me: brand new steam-powered valve for a steam-powered car; they're making flint axes exactly the same way, using exactly the same tools to the point they are almost indistinguishable from the original; archeological artifacts, making in huge numbers today.
But I really worry that the knowledge of many of the engineers who created these machines will be lost. One thing is that the analog museum really wants donations of machines that may be thrown out. If you see a box of the brand Dornier, TeleFunken, Gould, Aritma, BBC, Electronic Associates Inc, Solartron or even just something you think might be of interest send him an email. Even parts of these machines could be really useful to help repair the computers he has.
I do not think these machines are purely of historic interest. It is possible that in the future analog computers will be used in the real time simulations they excel in. One area I think they could be useful for is search engines. Linear algebra calculations are at the heart of modern search engines. this is described in The $25,000,000,000∗ Eigenvector the linear algebra behind google and How Google Finds Your Needle in the Web's Haystack
These calculations do not need to be precise (the google algorithm uses random walks) which removes one of the big objections to analog computers.
George Dyson in the this years edge question 'What Scientific concept would improve everybody's cognitive toolkit?' describes a search engine based on analog computers here
Analog computing, once believed to be as extinct as the differential analyzer, has returned. Not for performing arithmetic — a task at which even a pocket calculator outperforms an analog computer — but for problems at which analog computing can do a better job not only of computing the answer, but of asking the questions and communicating the results. Who is friends with whom? For a small high school, you could construct a database to keep track of this, and update it every night to keep track of changes to the lists. If you want to answer this question, updated in real time, for 500 million people, your only hope is to build an analog computer. Sure, you may use digital components, but at a certain point the analog computing being performed by the system far exceeds the complexity of the digital code with which it is built. That's the genius that powers Facebook and its ilk. Your model of the social graph becomes the social graph, and updates itself.
Analog computer methods of calculating eigenvectors have been described decades ago (pdf here).
It is possible that the techniques of analog computers could be the future of search engines. We should make some effort to save these machines, any manuals written on them and if possible some of the knowledge of those who made and used them.
Watson is a computer currently playing the quiz Jeopardy. You can see a video of this here
One useful question is how long this sort of supercomputer like power will take to be seen in everyday life? It has 3000 cores running and answers in less than three seconds. On one machine would take 2 hours to answer a question according to here So how long to get a desktop computer to be able to answer at this speed? I propose that half the speed improvement in Watson like programs will be from Moore's law and half from algorithm improvements. To go from 7200 seconds to say 2 seconds will require about 13 halvings in speed. I predict this will occur in the time it take processors to improve 7 doublings in computation. You can buy your own supercomputer now on the cloud and depending on how long you are willing to wait you could get an answer to a Watson like answer for costs of around a dollar (if you had the data and software Watson uses).
One comparison here is with chess. "It has been estimated that doubling the computer speed gains approximately fifty to seventy Elo points in playing strength (Levy & Newborn 1991:192)."
If doubling in processing power happens ever two years that would imply about a 30 point increase a year. The actual improvement (in computer v computer games) is described as 'With a 40-point annual improvement due to hardware upgrades, and a 30-point annual improvement due to software upgrades'. Implying improved algorithms are responsible for half the improvement.
This argument is summed up in this explanation as to why a fairly normal computer Deep Fritz in 2002 was an improvement over the supercomputer Deep Blue in 1997 'Deep Fritz has improved considerably over Deep Blue. Despite Deep Fritz having available only about 1.3% as much brute force computation, it plays chess at about the same level because of its superior pattern-recognition-based pruning algorithm'
I claim there is an analogy to Moore's law that says something like.
Once computers get good enough at a task to have a flashy TV challenge from then on algorithms will cause half the improvement in that task
So if I am right I think Watson like computation instead of talking over 25 years to move from twelve refrigerators to something we can use everyday should take less than 10 years. I would take an even money bet that in five years there will be a service you can use from your phone that is a lot closer to Watson than to a search engine we see today.
*update A friend just made this bet with me "20 euro bet that January 2015 there is a search engine that with a set of quiz questions from one gameshow program (the weakest link, who want to be a millionaire, university challenge) and it has to get 7/10 right". The effects of learning by reading (and autonomous cars) are examined in this rather long but brilliant blogpost
