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The start of a decade is traditionally ushered in with a flurry of predictions. Those usually turn out to be wrong, but are illustrative of the expectations of the current age. Errors are informative, and show our limitations, our fads and misunderstandings. Looking back at predictions can be fun. Hindsight allows us to feel superior. We imagine that, if we could travel back in time, we could be of great use to our ancestors. Probably not. We would be chattering to them about scientific advances we did not fully understand, based on supportive technologies which would not be available, and without an accurate appreciation of what they already knew. They might find us arrogant, ignorant and pretty useless. For example, without looking it up, help your ancestors build a two way radio.

Prediction is not impossible: some bright and very diligent people can people can achieve accuracy by doing their homework on specific topics, as Philip Tetlock has shown. The trick seems to be to understand the background statistics in some depth, (say the number of times a government in power gets re-elected) and then make small adjustments in line with new circumstances, but rarely any dramatic ones. Business as usual seems to be a wise bet.

https://www.unz.com/jthompson/the-tetlock-forecast/

I have neither the wit nor the application to be a super-forecaster, but to reveal my current expectations, here are some wild surmises about the world in 2030.

1 Very few people will be using flying taxis, other than those already using conventional flying taxis.
2 Very few people will be being driven by autonomous vehicles.
3 Most cars will be powered by internal combustion engines.
4 Batteries will be only a little better than they are at the moment.
5 People all over the world will be richer and healthier.
6 Population growth will stabilize, except in Africa.

As you have seen, I can generate many testable predictions about very general subjects. Will I be any more capable if I make predictions about intelligence research?

I think the field will continue to flourish. “Ordinary” intelligence research, about what it is related to what in ordinary life, and how intelligence contributes to people’s achievements will continue to account for most published work. People will try to boost it by training techniques, and mostly fail. New ways will be found to test it, and turn out to contribute little. Some people will continue to doubt it can be tested, and is of any significance.

Brain scanning will improve, and with any luck will be carried out on larges samples of representative people, doing intellectual tasks which can be measured reliably, thus leading to better understanding about the links between brain activity and problem solving.

Artificial intelligence will be used as a tool to replace some routine pattern identifying tasks such as in medical screening, and in generating game playing strategies in simulations so as to design new materials and medicines. It will be the adjunct of choice when solving new problems. It will probably be used in almost every setting, and then become better understood and refined to deal with those tasks humans find too dull to dwell on for long.

Particularly, the study of genetics of intelligence will flourish. It is the best game in town. There is a risk of repetition, but further analyses will sharpen findings, and this will teach us more about our origins than has been known ever before. That is to say, by 2030 we will have learned more about our origins than previously known.

If debates about racial differences in intelligence are to be taken down to a genomic level, it will be necessary to assemble million person samples of non-Europeans, particularly Africans. It would be good if this were to happen in the next decade, but I assume such data will be collected in China, not Africa. Central governments have to be well-organised, positive about science and capable of delivering education and other basic public services for good statistics to be collected. Epidemiology tends to be a Scandinavian disorder.

I think there will be an increased acceptance of the screening of IVF embryos for health reasons, including for severe retardation from any cause. Journalists worry about “designer babies”. I think it far more likely we will move slowly towards “disease resistant humans”. As part of this process, if those few parents undergoing IVF choose the healthiest of their several possible embryos, there could be a boost of about 4 IQ points for those few children, which will be useful but hardly noticeable.

Currently, the moral issue revolves round embryo selection: given that a choice has to be made, what is the moral choice? “Do no harm” is the Hippocratic injunction. Is it moral to choose an embryo which will grow up to suffer a preventable disease? Most parents will probably feel that it is not, particularly if there is a family history of such a disease. Eventually, such families may feel that it is not moral to pass on the disease genes. Some children at maturity might start asking health related questions about the extent to which they were genetically screened, and be resentful if left carrying preventable genetic risks. This won’t happen this decade, but might become an issue for those born in the next one.

A justified concern about unintended effects, plus laws which prohibit such experiments, will prevent or at least delay attempts at genetic engineering. China has put He Jiankui and two colleagues into prison and banned them from receiving further research funding. It is unlikely that there will be any further CRISPR-cas9 type tinkering with human genomes for quite some while, and not by 2030. Work in other species will provide comparative data on the rate, extent and consequences of unintended effects. The rate estimates from mice is that they will be lower than 1% and usually minor in terms of consequences, but that is still high if contemplated for humans.

Looking further ahead beyond 2030, some people have made startling predictions about what genetic engineering might achieve in boosting human intelligence. I haven’t paid these much attention, arguing to myself that such speculations were premature and exaggerated. Using 4 IQ gains from embryo selection as the base rate, I saw little reason to get excited. Ever cautious, I thought I would check whether my caution was justified. I asked people in the business what might one day be possible, if it was both legal and possible to remove the currently known intelligence-reducing genes and ensure that everyone had all the currently known intelligence-boosting genes. To be clear, this estimate does not require further discovery of the links between the genetic code and human intelligence. It takes the current state of knowledge and assumes that gene editing techniques are good enough to go through the list of “intelligence genes” and make sure everyone has a full house.

Asking around, the answer seemed to be that CRISPR will probably not be an effective technique for making multiple changes in a single genome. So, the first point is that current technologies won’t work. CRISPR can handle short sequences (inserting and replacing) but not the longer ones required for the intelligence-boosting task.

Second, if one makes the leap of assuming that eventually there will be a new technique which can handle longer sequences, there is still a significant problem. Most of the hits mentioned in current research papers are not the causal sites, but merely correlated with the true causal sites. Much further work would need to be done to identify the causal sites. Only then can the manipulation of those sites be attempted.

 
• Category: Science • Tags: AI, IQ 
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This has been my best ever year, with 448,525 pageviews, an average of almost 9000 pageviews per post. These posts provoked 1.25 million words of comments, another all-time record, not bad for a mere 50 posts. The range of comment was very broad, the positions adopted often diametrically opposed, and quality of the best commentators outstanding. I wanted to reward those who stuck to the argument and provided references in support of their views, and Ron Unz had already noted those commentators, and arranged a way of doing so. Thanks to them, and to all of you for reading, and writing enthusiastically in response.

The top ten posts are shown below:

The world’s IQ of 82 drew the most attention any of my posts has ever received. Readership at 78,663 was almost 8 times higher than my most popular post last year. A viral post, it would seem. Global politics ought to take account of human capital. The next iteration of the world IQ database will probably show that IQ 86 is the best estimate, particularly if very low scores in some studies are excluded. In strict terms there is no justification for such an exclusion, since all results must be accepted on an equal basis, but tests of study quality are appropriate in my view, and I think a quality-weighted estimate will be around IQ 86. This very detailed and extensively documented and explained collection of papers on national intelligence is now a great resource for researchers. Contributions and referees are welcomed, as further relevant results are tracked down and included.

Although he has blocked me and so will not be able to read this, I am most grateful to Nassim Nicholas Taleb. He wrote an attack on intelligence testing which was so silly I decided to ignore it. Some of you asked me for my opinion, so somewhat against my will I went through it, correcting what I saw as the most glaring errors. That drew in a large number of readers, and overnight gained me 350 new Twitter followers. The moral is: rebut promptly, and never avoid an open goal.

I have always been fascinated by human errors, including my own. An aeroplane cockpit should be finely tailored to the human mind. When it is not, passenger die. The saga of the Boeing 737 Max 8 and its internal contradictions was a real-life Hal 9000, as in Stanley Kubrick’s “2001: A space odyssey”, a rogue computer that attacked the crew. Boeing produced software which had a mind of its own. When I called foul on it, I worried I was jumping the gun. I was a Boeing fan, and had previously lambasted the Airbus side-stick as being opaque, but the MAX software fix was terribly flawed, and would have been picked up by old-style Boeing engineers. Operators must have an accurate conception of how controls work. The comments on these posts were an education: there was much to learn from knowledgeable readers with technical information to impart.

Other posts gained readership by taking on various critics of the study of group differences and of intelligence testing. This is debate as it should be: an exchange of views about supportive evidence. I argue that genetics is a source of individual and group differences, not the sole cause, but an important one. On intelligence testing, the surprising finding is that intelligence is ridiculously easy to measure, and adequate tests take only a few minutes. Although these posts of mine were popular here, I am under no illusions: the criticisms which I rated as mistaken will have been read and believed by far more people than I reached in these refutations.

In the list above, look at the last column. Readers are having a proper read: they dwell a fair time on each post. The Boeing posts were a particularly good long read.

Finally, for aficionados, look at what is not in the Top Ten: for the first time “The 7 Tribes of Intellect” got pushed into 11th place, albeit missing inclusion by a mere 39 pageviews.

Some readers just dip in: I suppose they came to visit the “viral” posts and then, edified, went elsewhere. At the other end of the spectrum, there were very welcome repeat visits from loyal readers.

Bluntly, some people read me by mistake: I should have called the blog “Supplementary Statistics Appendix 3” to give them fair warning of what to expect. I hope they found many other more congenial places to satisfy their interest in psychology.

Here is a clue: although readers span the age range, with a big peak among those who beginning their careers (and liberating themselves from politically correct educators?) 83% of them are men, probably with a technical approach to life. They would like to know how things work, and expect to handle some numbers along the way.

Here is a new finding. Turks came to visit, but did not stay long. Why? Perhaps they wanted to know what evolution was about, and then got cut off. Any ideas?

The US predominates, as in real life. On a broader perspective, out of a total of 199 thousand readers, 119 thousand came from the British Empire (as was). Good to see cultural continuity. Readers in Sweden and Germany feel it worth having a look. France…. well, I am pleased to welcome inquisitive Franks.

I know there are many other far more popular psychology blogs, but given the necessarily technical nature of intelligence research, I think this is a good showing.

Twitter followers have risen from 4,500 last year to 5,825 now. I have not totally lost interest in Twitter, but have tweeted less, restricting myself to doing so when putting up new posts on the blog. I have given up looking at Twitter impact statistics, while still being interested in my blog statistics. Also, I have let many tweets pass me by, without responding. Each to their own opinion.

As always, I favour blog commentators who are evidence-based, responsive to counter-arguments, tough on all claims but kind to other commentators. To those who went out of their way to explain as well as argue, I appreciate your work enormously. Some of the exchanges should be written up and posted in their own right.

If you can please ensure that your anonymous handle is distinctive, that will help put your line of reasoning into context. If your name is Legion you are still as safe as when you call yourself Anon.

Back to the blog. 1,132,000 pageviews is more than I ever hoped to achieve. Thanks for reading, and Happy New Year.

 
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To the Church of the Knights Hospitaller of Jerusalem, as is my wont, to celebrate the habits of my tribe, as parishioners have done since 1211. They must have done so before that, but not in this building. The service of Nine Carols was just after dark, with the rain lashing down in the bleak and sodden mid-winter, mud upon mud, wet as a wet, wet stone.

Arriving wet, and late, I got my best ever pew, up at the front facing the lectern for the readings. In deference, parishioners on this holy night had filled the church from the back. The first shall be last, and the last shall be first.

The nave was full to overflowing, the transept also full, the chancel empty of choir, the congregation in good voice, the carols familiar, dependable. In particular: Once in Royal David’s City (not verses 4 and 6), Oh little town of Bethlehem, The Holly and the Ivy, God rest you Merry Gentlemen, Hark! The herald angels sing. Just the organist, our voices, a few candles, and no fuss. We swelled with praise. For variety, the vicar allocated verses to male and female voices, though he did not specify if that held true of the choruses, which made us falter somewhat, and noting the hesitant volume, he later clarified that both sexes should sing those. In the spirit of priestly festive fun, he invited us to sing the descant on the last verse of every carol, if we knew it. Few did. The coral tradition is lapsing, and the effective canon shrinks.

Carols are not upon oath when it comes to theology. It is a question whether they get the hang of things better than the ancient writings, or whether they are excursions in search of a rhyme, making personal points dear to authors. Those carols that catch on engrave their own truths, so perhaps the point is moot. Some songs get sung, some tales get read. The readings were done by adults, who spoke well, with meaning. Each reader was known to us, and so were their texts. The readers had aged slightly, the texts not so much. Readers stood for our inspection at the lectern, like plaintiffs at a photo booth which opens once a year. The process ages them, and we, eternal and unchanged in our pews, merely watch. Isaiah and Luke predominated, then Micah and finally the mysterious John. The message was passed on, though without the thunder of other times.

There is a moment in all ritual when repetition makes participants pivot between confirmation and criticism. There is no news but the old news, so why repeat it? This is ancient stuff about tax collection, the lines are well worn: so are you. Here is a familiar story, and you know where it leads, and a year has gone by, and the crops are gathered, and stored, and your year has gone by, and cannot be stored, but perhaps remembered. William James referred to the flywheel of habit, and sometimes beliefs spin from former fervour, not from present faith, though there was that too.

All this talk of birth: there was at least one baby, mildly talkative, giving a babbling commentary; and perhaps another asleep. Despite the injunction to do so, I did not dwell on those on the further shore, but thought of those on this one. For someone to be missed they must be noted beforehand: pay attention to the living, the imperative of the present.

Perhaps impelled by the promise of mulled wine, there was a certain briskness to the celebration. There were no imported sopranos to marvel at, nor even a small orchestra to swell the scene. We were making our own entertainment tonight. Perhaps it was 45 minutes, possibly 50. We did not tarry over our observances.

After the blessing a pause and then the organ finale, and it was all over. In a glaring change, the lights were switched on, and the ancient peace was lost. Mulled wine, mince pies, conversation. An elderly lady graciously excused herself from attending a Christmas party, on account of her elderly husband being unsteady on dark and wintry nights. A much younger woman spoke of Italy, and of a friend who had just left the village. He was holidaying in Thailand, bored, and hoped Singapore would be more interesting. A farmer complained of the persistent rain, a month’s worth in the last few days. Slugs were eating the winter seeds he had planted, particularly those close to the woods. He had put down as many poison pellets as the law allowed, and was hoping the crows would devour the remaining slugs.

Leaving, I commended the vicar on assuming his parishioners were either male or female, and nothing else. He replied that he chose the words deliberately, so that sons could sing with their fathers even though their voice might not have changed. In a former life he was a biologist. Outside the wind was blowing, and I remembered there were cars parked on the road, and things to do. A parishioner already standing outside staring at the dark rain-speckled carp pond wished me Merry Christmas. Perhaps he was thinking of 808 years of services.

Walking back through the rain, illuminated by a headlamp on the glistening tarmac, I swear I heard an owl hoot.

And to you too, may he hoot Merry Christmas.

 
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Usually, British politicians take inspiration from US election campaigns. Very occasionally, the traffic goes the other way. Poorer cousins can sometimes make a contribution. Perhaps this election repays attention, since it is about a party winning an absolute majority against apparent odds. The 2019 UK election has brought about the biggest political opportunity for a decade. Today, at the State Opening of Parliament, we had a very optimistic wish list read out by the Queen. On her behalf I should remind you that she reads it, but doesn’t write it.

The pattern of winners and losers in the last four decades of UK electoral history is interesting.

Margaret Thatcher won majorities for the Conservatives in 1979 (43), 1983 (144) and 1987 (104). Nothing daunted, the Conservatives decided to replace her with John Major, who won in 1992 (21) but did not prosper thereafter.

In 1997 John Major lost to Tony Blair, who won a landslide for Labour of 179, a post-war record which still stands. Tony Blair won again in 2001 (167) and 2005 (66). Nothing daunted, the Labour Party decided to replace him in 2007 with Gordon Brown, who prospered even less, never winning an election.

David Cameron beat Gordon Brown in 2010 to win 306 seats for the Conservatives, but that was 20 seats short of a majority, so had to go into a coalition with the Liberal Democrats (57) which led to compromises for both parties.

In 2015 David Cameron won the Conservatives a majority of 12 seats, and the Liberals collapsed to 8 seats. Before he could do much with his majority, Cameron had to win a referendum to stay in the European Union. To his surprise, he lost, and resigned. It was assumed that the winner for Leave, Boris Johnson, would then become Prime Minister, but after being dumped by his No 2 Michael Gove, he withdrew, and Teresa May became Prime Minister instead.

Because Labour had chosen far-left Jeremy Corbyn as Leader, Teresa May called an election 2017 to get the large Conservative majority predicted by the polls. She campaigned badly, on an unpopular Manifesto; Corbyn campaigned well, so May lost her absolute majority, and was bailed out at great cost by the Ulster Unionists. She did not prosper, limped on, and after two years the Conservatives replaced her with Boris Johnson, who has just delivered them an absolute majority of 80.

I hope that account was not too confusing. The moral of the story, in my view, is that political parties do well when they have leaders the public votes for. Thatcher did well for the Conservatives, Blair did well for Labour. They are the post-war front runners in the politics business. The Conservatives dumped Thatcher because they thought she was too confrontational and radical; Labour dumped Blair because he was too conservative and insufficiently left wing. Unwise. Some politicians prefer the prospect of being the leader themselves to the threat of their party losing power.

Boris Johnson has started well, with the biggest majority since Thatcher, though not at her levels. He is young enough to do another two elections, or three if he wants to be the absolute winner in modern times. We shall see.

The simplest version of UK electoral history is that since 2010 the Conservatives were in government, but only partly in power, often because of internal divisions over Europe. Now we have a Government again, able to make laws as it chooses, the battle over Europe won by the Leavers, so we have five years with more certainty about the political direction the country is taking. The result may be a relief even to those who lost the election. At a national level, there is much to be done. I doubt that many will mourn the Brexit stalemate of the past three and a half years. “Getting Brexit Done” reminds me of Robert Graves’s farewell to the First World War: “Goodbye to all that”. Enough.

Perhaps we will all traipse merrily to the sunlit uplands and live happily ever after, but at least there will probably be five years before another election. That is worth something. Time to get back to more pressing tasks.

How was the campaign won? The outlines are already known: the Conservatives stuck to one basic slogan, kept their manifesto short, and campaigned most vigorously in Leave seats outside London. They gained first time Conservative voters, but lost in London and university towns. A fuller analysis will come out over the next few weeks. Labour is now having a pause for reflection. Commentators noted that Corbyn would not smile and chat with Johnson as they led their parties to hear the Queen’s Speech, as custom and habit has it. Perhaps that was his final act of rebellion.

What is the moral of the UK election for the US election? I leave the answer to those who know something about the subject, and will read your comments with interest.

 
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A few days ago, I was worried we would have a Hung Parliament, as a resurgent youth-led voting public scooped up the free offers showered on it by the Labour Party Manifesto. Discussing this some days ago with people in a position to know better, the younger of the two contacts feared that the Conservatives were losing the youth vote (which they did) among other things by being tempted by targeted offers of free transport for the under 25s. He feared the whole of London was lost (most of it was) and that the Conservative leadership did not understand how people thought outside city centres (definitely not so). When we were on our own again my older contact said the younger one was too pessimistic, but the best we could both come up with as a prediction was a small working majority, and even then, it was best not to depend on it. Part of the reason was that in 2017 Labour under Corbyn did very well, which was a shock as their vote firmed up at the last minute, and was not predicted by the polls. Teresa May was a wooden performer, and her Manifesto contained unpopular things, for example a proposal which increased the chance that family homes would have to be sold to pay for social care.

This time the result was far better than expected. His majority is a “stonking” 80 seats, the best result since Thatcher in 1987. England voted Conservative, affronted by a Labour leader who was seen as unpatriotic, disloyal and untrustworthy. Boris was seen as a bit of a rogue, but charming and with a sense of humour. He passed the pub test: many voters thought it be fun to have a drink with him.

The Conservative election machine regained its reputation of being a machine, not a knitting circle. The guiding principle was that, if something was done in 2017, it should not be done again. The Manifesto was kept short, and short on promises, with no hostages to fortune. When Cabinet Members were even slightly off-target, and made comments that could be misinterpreted, for example, that it “was common-sense to leave a burning building” when discussing the Grenfell Tower fire, they were immediately side-lined and never seen again. “Get Brexit done” was repeated ad nauseum until even Labour repeated it. The repetitions became a joke, but it was deadly effective. Focus groups struggled to list what the other parties wanted but everyone, Leaver and Remainer alike, knew what the Tories would do. Lines of command in the election HQ were clear, and the focus on limited objectives relentless. It will be studied carefully in the US. Fear is a good motivator, and even those who were normally confident of victory remained terrified it would all go wrong, like 2017.

Scotland voted for the Scottish National Party, but curiously that does not guarantee they would all vote for separation. Currently they do well out of the Union. Being rebellious need not go the whole way. However, this is a problem.

Northern Ireland has moved closer to Ireland, with one seat moving to Nationalist (Irish) parties from the Unionist Northern Island (Conservative) cause. Wales moved closer to English Conservatism, dumping traditional Labour in several seats.

Northern Ireland has never been particularly popular with mainland voters. The English don’t like people who take politics too seriously, still less those who murder their countrymen because of politics. The English would be happy to be shot of Northern Ireland, and only defend them because they want to remain part of the United Kingdom. Nonetheless, they are seen as shouty and too fond of history and waving the Union Jack. Dumping them would be popular, but won’t happen.

Dumping the Scots would also be popular. Their Parliamentary leader shouts, sides with Labour, and was part of the obstructive faction that blocked Brexit. If Scotland doesn’t want to be part of the Union there is no enthusiasm for wooing them with more money. Who knows, in another decade or two Engerland might just be Engerland.

What are the pointers for the future? Never judge the electorate solely by the people they elect. Being elected goes to the elected’s heads. Some Conservatives believed they were capable of judging what the public really needed, and that what they needed was not what they voted for. They joined Labour’s “destroy Brexit by a thousand delays” plan. (Boris purged them, and they all lost their seats at the election, or did not contest it). Labour believed their own estimates of their personal importance. They promised to respect Brexit and then openly sabotaged it. The Liberal Democrats chose the policy of revoking Brexit. Unwise, undemocratic, unelectable.

The public were having none of it. Whatever they had voted in the 2016 referendum, in 2019 they voted to Leave, either out of conviction about Brexit or conviction that if Parliament asks the people for their opinion, in a once in a lifetime referendum, they should respect the results.

Boris made the difference. The character of the candidate matters. Boris is a Cavalier, not a Roundhead, close to Merry England, the alehouse, and buxom wenches. People understand that. They voted for the normal bloke who likes a bit of a laugh, not the perpetual protester and his pamphlets. Now the Boris team will have a chance to show the electorate that they are worthy of being supported five years from now. One person will be particularly keen to do that. A Share in two revolutions is living to some purpose. Dominic Cummings helped win Brexit 2016 and a Conservative landslide in 2019. The entire team will enjoy the new dawn.

 
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Sceptics say the best way of predicting tomorrow’s weather is to say it will be the same as today. Predictive models struggle to beat that pedestrian approach, which one could label a rolling null hypothesis.

Today, Wednesday, pollsters are predicting how voters will behave tomorrow, Thursday 12th December, election day. That ought to be fairly easy. Polling has been carried out every month, and more intensively over the last 6 weeks of the campaign. Among those people willing to divulge their opinions, and likely to vote, the pattern is pretty clear: probably some sort of Conservative majority over all the other parties combined.

This is the stage at which pollsters are looking carefully at their predictive models, aware that an accurate result will gain them commercial advantage in the years to come. Are you part of a business anxious whether consumers will buy your new product? Why not test it by giving the contract to the pollster who got the General Election right?

Naturally, pollsters would like some wiggle room. Yes, they will be tested on their final prediction, but if necessary, they can look back a week or two at their previous predictions, and tell some sort of post hoc story: “we got it right the week beforehand, but gave a little too much emphasis to factor Y. We have learned our lesson, and will include Factor Y in our survey work on your product”.

More wiggle room comes from the dual nature of their predictions: calculating the popular vote (reasonably easy) and calculating how that will translate into seats won in 650 constituencies under the harsh first-past-the-post system (much harder). If something is good enough for horse-racing, it should be good enough for judging politicians, but one vote can make a difference, and some margins in the 2017 were no more than 20 votes.

The YouGov MRP model is based on the largest poll, involving 105,612 interviews. This is a good number, given that most polls are in the 1,500-2,000 range. They say of their model:

It works by modelling the relationship between respondent demographics (age, gender, class or past vote) and their vote, and how this changes in different types of seat (region, marginality or incumbency). This model is then applied to the demographics and political circumstances in each seat, projecting results in each of the 632 constituencies in Great Britain.

In fact, this is the familiar Multilevel Regression and Post-stratification approach to produce estimates for states and congressional districts in US elections, and parliamentary constituencies for UK elections.

The idea behind MRP is that we use the poll data from the preceding seven days to estimate a model that relates interview date, constituency, voter demographics, past voting behaviour, and other respondent profile variables to their current voting intentions. This model is then used to estimate the probability that a voter with specified characteristics will vote Conservative, Labour, or some other party. Using data from the UK Office of National Statistics, the British Election Study, and past election results, YouGov has estimated the number of each type of voter in each constituency. Combining the model probabilities and estimated census counts allows YouGov to produce estimates of the number of voters in each constituency intending to vote for a party. In 2017, when we applied this strategy to the UK general election, we correctly predicted 93% of individual seats as well as the overall hung parliament result.

Without labeling them as 95% confidence limits, they admit that their predictions about the number of seats won by the major parties covers a wide range, and there could be no majority (Hung Parliament) or a larger majority Conservative majority. Could be. To get an outright majority, the winning party must get 326 seats, since none of the other parties are willing to help the Conservatives, the front-runners.

YouGov’s latest and final general election MRP model shows the Conservative Party headed for an overall majority. Predicted vote shares in our final poll:

Conservatives 43%, 339 seats
Labour 34%, 231 seats
Scottish National Party (Scotland only) 41 seats
Liberal Democrats 12%, 15 seats
Brexit Party 3%, 0 seats.
Conservative overall majority of 28.

If this turns out to be true, the Conservatives would win 339 seats (22 more than they took in 2017) and a vote share of 43%, their best performance since 1987. The actual number could range from 311 to 367 seats. However, drilling down into the detail, applying general results to individual constituencies is an error-prone procedure, even before tactical voting is factored in. The Labour vote is strengthening later than it did last time, but is still on an apparent upward trend. The lower estimate of the projected Conservative majority may turn out to be closer to the actual result.

Please note that a failure to predict a specific constituency does not invalidate the overall prediction. An intelligence test can predict who will do well on average, but there will be individual exceptions.

So, that is the overall picture about what will happen tomorrow. Other predictive sites (Electoral Calculus) have come to slightly different conclusions, suggesting a Conservative majority of 46.

For those of you who think that we are being manipulated by outside forces, this election is a test case. You have a chance to tell us, with your inside knowledge, what the actual outcome will be. Let me hear your predictions before 22 hours, on Thursday 12th December.

For the record, I have no such insight. The few people I know who could claim some inside knowledge believe that the Conservatives will not obtain a working majority, and that we will be in the limbo of a hung Parliament again.

 
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Tomorrow, Wednesday, is the last campaigning day of the UK 2019 election. The vote takes place on Thursday, and the result should be known by the end of Friday. If the result is very close and re-counts are required, it could take longer, and not be settled until next week.

As already discussed, political polls are reasonable indicators of general intentions, but are subject to sampling errors and to late changes of mind, and useless for determining late emergences of mind. For many citizens it is the sight of the actual ballot paper which triggers a decision. An independent candidate with a jokey title may get their vote, but most will plump for apparent safety, or may be swayed by the last message received.

Uniquely, this election reflects the new power of social media. Facebook and to a lesser extent Twitter communications have got more attention than some of the TV debates. For better or worse, these media are more difficult to regulate. A lie/searing expose of truth can go around the world before truth/refutation or counter-lie can get its boots on. Pictures still have their power, and a photo of one child in a casualty department can have more impact than any reasoned discussion of health policy and funding options.

Uniquely, this election reflects a treble polarization.

1 Traditional political party loyalties have been unsettled by the Brexit referendum of 2016, so that “Remain” and “Leave” are new phantom parties, posing new opportunities and threats to ancient loyalties. Traditionally, the Conservatives were seen as the upper-class party, Labour as the working-class party. Now, because so many of the working class voted to Leave the European Union the Conservatives are said to have a following among lower socio-economic status, lower education voters, while Labour is getting the votes of professional class, Remain in the European Union, high socio-economic status, high educational level voters. It is all very confusing. Class is no longer political destiny.

2 The other polarization is age: the young disproportionately back Labour, the old vote Conservative. This makes the sudden burst of registered younger voters a wild card in predicting the outcome. It also means that any campaigning about historical events has little impact on younger voters: they simply did not come of age under previous Labour governments, so cannot see the relevance of the warnings they are given. Equally, older Conservatives may have little grasp of current problems faced by younger voters, particularly the costs of renting property, the difficulty of ever buying property, and the costs of commuting to work.

3 The final polarization may be the most profound: this has become a contest between the Conservatives and all other parties. That is to say, the Conservatives (318 seats in 2017 election) do not have to just win a majority over the main opposition party, Labour (262 seats). They have to win a majority over all the parties put together. This is a high bar to clear. Although the other parties are labelled as: Labour (262), Scottish Nationalist (35), Liberal Democrat (12), Democratic Unionist Party (10) Brexit Party, Plaid Cymru (4) Green Party (1), Brexit Party (0), they have the option of joining together to form a minority coalition. Note that the Scottish Nationalists do not want to be in the United Kingdom, and want another referendum in order to leave; Plaid Cuymru want Welsh independence; the Democratic Unionist Party very much want Northern Island to remain in the United Kingdom (though on their own terms, and not in any coalition with the Conservatives). They are none of them natural bedfellows, but the prospect of power, if available, is likely to lead to a coalition of convenience.

For once, commentators may be right to say that this is one of those famous elections which dominate the political landscape for decades. It may be the end of Britain as a market-led economy, and the beginning of a Government-led one. A lot is at stake. The election has been waged as a culture war, with the public either repelled or merely bored to death with it. Politics is not a popular sport here. Politicians are not held in high regard, and many voters are grimly searching for the least awful option. A pity. The political aims of Conservatives and Labour are worlds apart. Electors used to sneer that there was nothing to choose between them, and now that there is everything to choose, some are still complaining. There has never been a Manifesto like that put forward by the Labour Party, with widespread nationalisation, tax increases and heavy expenditures. The Conservative Manifesto is more cautious, but still promises much in the way of expenditure while saying that taxes will not rise. The Conservatives are matching some of the Labour offers, but Labour is proud of offering a dramatic changes toward a powerful State. This will end in ruin, Conservatives say, with historical examples aplenty.

Sadly, there is a lot of ruin in a nation, and Britain has a tradition of just plugging on regardless, but both the economy and the commanding heights of society itself may be changed more profoundly than in 1945, and how that will end no one can say at the moment

 
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I have no idea what you will be thinking or doing on 12th December, but efforts are being made to determine how UK citizens will vote on that day. Why the fuss? A rational approach to elections is to read the party manifestos, judge the personal and societal impact of the proposals, calculate the probability of the promises being kept, and then vote in advance by postal ballot. That done, the good citizen has no need of reading the news, watching debates, or even waiting in a queue on election day. Certainly, the rational citizen has no need of opinion polls: they are not relevant to informed decision-making.

In a further show of rationality, the wise elector will not stay up on election night, since the event cannot be influenced by watching it. Wiser still, the elector should not check the results for a few days, to avoid wasting time with dangling chads, recounts and other frivolities.

Sadly, the current culture of instant gratification requires a daily feed of speculation about how the election is going, that is, how other people are thinking about which way they might vote on election day, and whether they are likely to vote at all. That provides hours of comment. Then, in a meta-analytic frenzy, commentators discuss how much the opinion polls themselves are causing citizens to change their intended behaviours, as they realize that they are in a minority or, conversely, in such a majority that they might be giving too much power to the most popular party. Others, feeling exposed at being revealed to be in a minority, switch to the most popular party, just as others are abandoning it.

Opinion polls took off in the US in the 1920s. Gradually pollsters learned about the effects of selection bias. If you only poll the readers of your newspaper, you leave out the majority who don’t read it, and certainly those that don’t read any newspapers. Sampling is crucial. However good your sample, you can never include those who don’t want to be sampled. Different avenues of approach lead to different types of voter. Telephones (remember those?) only catch older people at home, and that may be only 20% of home numbers dialed.

To keep calm and avoid election fever, I have been reading a book on statistics. The best statistics books are those one does not admit reading. They explain complex matters in simple terms, and one is forever grateful, without admitting it.

David Spiegelhalter. The Art of Statistics: Learning from data. Random House, 2019.

This is a good book, with helpful explanations which concentrate on key concepts, not specific formulae. Brian Everitt, one of the developers of cluster analysis, always said to me that it was a deficiency of statistics that when you asked a statistical question you got a number instead of an answer. “Yes” or “no” are generally the answers one is searching for.

Far from bringing solace, the book discussed the problem of using opinion polls to predict election results, using the UK election of 2017 as a prime example of the shortcomings of conventional techniques, which failed to spot a late surge for the Labour party, leading to a hung Parliament, and a precarious working majority derived from a cobbled together Conservative coalition.

Can statisticians do better in 2019?

Spiegelhalter’s book is worth reading because he poses interesting questions, and answers them without numbers (or at least, without too many complicated numbers in the first instance). His aim is to get you to think straight about problems, and to solve them in a systematic way, leaving the number and calculation issues till later. Think hard, plan carefully, and then you can let the (properly selected and presented) numbers do the talking. OK, numbers don’t talk, but if you have thought things through, then you can explain the findings in ordinary language.

For example, has a nice family doctor been murdering his patients? How does one estimate normal death rates in medical practices? What counts as an excess? Anything else worth measuring? Is time of the day the death occurs something worth counting?

Spiegelhalter shows in a simple figure (page 5) that Dr Harold Shipman’s victims disproportionately died in the afternoons, when he did his home visits, and administered a lethal opiate overdose to at least 215 elderly patients. As Spiegelhalter dryly observes: “The pattern does not require sophisticated statistical analysis.”

Spiegelhalter’s approach is immensely sensible. He shows that statistics require careful thinking, and only then some number crunching, followed by an honest depiction of the findings. He is a good guide to statistics, particularly for those who panic at the sight of mathematical notation. He is good at explaining (yet again) the difference between relative and absolute risk; the distorting effects of question framing (in the UK 57% supported “giving 16 and 17 year olds the right to vote” but only 37% agreed with the logically identical proposal to “reduce the voting age from 18 to 16”; the distorting effects of telephone polls which do not declare what proportion of telephone numbers dialled never answered; he explains that a causal link does not mean that every single person shows an effect (many people smoke and don’t get cancer, but smoking causes more people who smoke to get cancer than those who don’t smoke, and some non-smokers get cancer); don’t rely on a single study, instead review all studies systematically; some potential causes can be called “lurking factors” but actual causes follow the Bradford Hill criteria (page 115): effect size so large it cannot be explained by plausible confounding; appropriate temporal or spatial proximity in that cause precedes effect and effect occurs after a plausible interval, or at the same site; effect increases as exposure increases, and reduces upon reduction of the dose; there is a plausible mechanism of action; the effect fits in with what is known already; the effect replicates; and the effect is found in similar but not identical studies.

He is excellent at explaining regression to the mean (two thirds of the apparently beneficial effect of speed cameras are due to regression to the mean); at discussing the bias/variance trade-off (over-fitting predictors to correct “bias” and reflect local circumstances at the cost of lower reliability); and in accusing algorithms of prejudice when predicting whether criminals will re-offend, notions of justice are being favoured over predictive accuracy.

There is much to recommend in this book. He covers a wide range of statistical issue with clarity, particularly on probability, so Chapters 8 and 9 are worth buying the book for. I will probably refer further to this book in subsequent posts.

What does this mean for the UK election on 12 December? I will try to explain. The current YouGov snapshot shows the following voting intentions, and what they are likely to mean in terms of parliamentary seats.

UK elections are carried out in 650 constituencies, and use the “first past the post” system, in which the winner is the one with most votes, and becomes the Member of Parliament, and all the other votes contribute nothing to the election. Harsh but effective, like the race between spermatozoa.

 
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For some years now I have made occasional mention of a survey conducted in May 2013 to March 2014 to find out what intelligence researchers thought about racial differences in intelligence. Now the paper has been published, so in academic terms the work actually exists, and can be quoted and commented upon. I can remember looking at the draft of this survey, suggesting it be made shorter, which is what I always say. Long surveys lead to low return rates. When it finally came out, I’m not sure exactly how I answered it, but will give my best recollections in this post. Academia makes a tradition out of slowness: the last survey on this matter was in 1988. By this reckoning the next survey will be in 2052. No need to rush things.

Survey of expert opinion on intelligence: Intelligence research, experts’ background, controversial issues, and the media. Heiner Rindermann, David Becker, Thomas R. Coyle. Intelligence 78 (2020) 101406
https://doi.org/10.1016/j.intell.2019.101406

Abstract
Experts (N max = 102 answering) on intelligence completed a survey about IQ research, controversies, and the media. The survey was conducted in 2013 and 2014 using the Internet-based Expert Questionnaire on Cognitive Ability (EQCA). In the current study, we examined the background of the experts (e.g., nationality, gender, religion, and political orientation) and their positions on intelligence research, controversial issues, and the media. Most experts were male (83%) and from Western countries (90%). Political affiliations ranged from the left (liberal, 54%) to the right (conservative, 24%), with more extreme responses within the left-liberal spectrum. Experts rated the media and public debates as far below adequate. Experts with a left (liberal, progressive) political orientation were more likely to have positive views of the media (around r= |.30|). In contrast, compared to female and left (liberal) experts, male and right (conservative) experts were more likely to endorse the validity of IQ testing (correlations with gender, politics: r= .55, .41), the g factor theory of intelligence (r= .18, .34), and the impact of genes on US Black-White differences (r= .50, .48). The paper compares the results to those of prior expert surveys and discusses the role of experts’ backgrounds, with a focus on political orientation and gender. An underrepresentation of viewpoints associated with experts’ background characteristics (i.e., political views, gender) may distort research findings and should be addressed in higher education policy.

As you can see, the paper confronts the politics/attitudes nexus head on. The popular view is that political orientations determine attitudes to scientific findings: find the author’s politics and you can predict and also discount their opinions. On the contrary, author’s observations of life may determine their politics, and in fairness you can equally argue that once you find the author’s observations and experiences you should discount their politics.

Who were the experts?

The survey was sent to authors who published at least one article after 2010 in journals covering cognitive ability. The journals included Intelligence, Cognitive Psychology, Contemporary Educational Psychology, New Ideas in Psychology, and Learning and Individual Differences. In addition, members of the International Society for Intelligence Research (ISIR) were invited (from December 2013 toJanuary 2014) to complete the EQCA, and an announcement was published on the website of the International Society for the Study of Individual Differences (ISSID).

A total of 265 responses were received, which produced a response rate of 19.71% from those approached for an opinion. This is not very good. The survey was long, which may have put people off, and since it asked about contentious matters, experts may have felt it was best avoided. As you may note later below, less than half of those who replied answered the item on racial differences in intelligence. They may have worried that the personal responses would leak out in some way.

The respondents have a claim to expertise. Their academic work was better than the scholarly average, so they probably know their subject. They were somewhat Left inclined, and this had an impact on questions like the contribution genetics makes to black-white differences. 16% of experts reported a 100% environmental explanation, whereas 6% reported a 100% genetic explanation. This group leans left in general, and is more extremely left on this particular issue. (For the record, I find it hard to argue for either of these extreme positions. My recollection is that I was in the 50:50 camp). Psychologists are generally very Left inclined, and intelligence researchers somewhat Left inclined.

According to Duarte et al. (2015, their Fig. 1), the leftward tilt in psychology emerged over the last three decades, leading to a 14:1 ratio of left (progressive, democratic) to right (conservative, republican) psychology faculty. More recent data show an even larger disparity (16.8:1, Langbert, 2018). The leftward drift is reinforced by a liberal bias among journalists (e.g., Groseclose & Milyo, 2005; Kuypers, 2002; Lichter, Rothman, & Lichter, 1986) and in Wikipedia (e.g., Greenstein & Zhu, 2012, 2018). In addition, there have been increasing disruptions and attacks against scientists with a perceived right orientation at university talks (e.g., Duarte et al., 2015; HXA Executive Team et al., 2018; Inbar & Lammers, 2012; Jussim, 2018). Student groups have interrupted lectures, courses, and invited talks, and in some cases violently attacked scientists and scholars with a perceived right orientation (e.g., Charles Murray; Arm, 2016; Beinart, 2017). Finally, these events parallel a growing political divide between progressive and conservative factions in the US and other countries (Pew Research Center, 2017, p. 7f.). In the Pew survey, the gap between Democrats and Republicans in the US grew (in 10 political domains) from an average of 14.9% in 1994 to 35.8% in 2017, an increase of 20.9%. 20.8% of this increase (or 99.5% of the growth) was due to a shift to the left by Democrats, whereas 0.1% was due to a shift to the right by Republicans.

Of course, if our science is worth anything, none of this should matter. Leftists should follow the facts, and where the weight of evidence supports a conclusion, they should back that conclusion. Rightists should likewise follow the evidence. As James Flynn says, science should be allowed to do its work.

Respondents are not very religious, but are socially liberal, and lean Left.


Rinderman et al. worry that

 
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The concept of general intelligence does not always gain general acceptance. It seems too general, and thus unable to explain the myriad sparkles of individual minds. Multiple intelligence, some people aver, is a better thing to have: a disparate tool set, not merely a single tool which has to be deployed whatever the circumstances.

Not so. The great utility of general intelligence is its generality. It can solve, or at least partially solve, the very large range of existential problems which beset our ancestors. It can help solve the current problems which beset us now, none of which were pressing on us in that particular form over the many generations in which our brains developed.

Indeed, having specialized skills would be a risky strategy for any life form, because whatever triumph that specialist mind conferred in a very specific niche, it would be hopeless if the niche disappeared, and it had to survive in an unfamiliar environment. For many specialized brains that would be a death sentence. Seen from an evolutionary perspective, a case can be made for prioritizing general problem-solving ability above all else. Specialized skills are limiting: they are too refined for the rough and tumble of ordinary existence. Better a Jeep (General Purpose vehicle) than a low-slung racing car if you want to travel across the rough roads of the world. The latest developments in artificial intelligence are based on making that intelligence general, not specific.

I have talked about artificial intelligence before, in the distant old age of 2016. That was when the best game we had in town was Alpha Go. How ancient that seems now. It was programmed to do things, using the game-winning strategies developed by the programmers.

https://www.unz.com/jthompson/artificial-general-intelligence-von/

Now we have Alpha Zero. It has been given an improved but still very simple brain, a few dozen layers deep, rather than the mere 3 layers of former years. Of course, there are not actual neurones or axons. These are concepts which serve to organize the way the programs run, and this is done on whole sets of servers, the way that most complex big-data problems are handled. It is this form of quasi-neural organisation which allows deep learning networks to operate. I see them as correlation accumulators, being conditioned by the reward of winning into deriving the strategies which promote winning, and learning their craft by perpetual competition. Call it speeded intellectual evolution: thousands and thousands of games being won or lost (generations flourishing or perishing) which lead to a well-conditioned, super-smart survivor, ready to take on the world.

These changes in the depth of learning make a big difference. Just give Alpha Zero the rules of a game, and it dominates that game, even though (or perhaps because) it has zero domain knowledge about that game. It has been stripped of human wisdom. It is an ignorant but fast-learning student. And it dominates all games, once it has been given the rules. Zero knowledge, but an ability to learn. Finally, a blank slate.

What will all this mean for us? Some citizens are waiting for the Singularity, also known as the Second Coming. Forget it, says Hassabis. Artificial intelligence will be a tool we use: fine in some settings, not so good in others. For example, artificial intelligence is very good at looking at retinal scans and detecting anomalies which require further investigation. The artificial intelligence programs of old would have flagged up the particular scan for further investigation, and left it at that. Now the program flags up the scan, and also identifies the features which led to it being selected for investigation. The best human expert can look at the suggestion, and decide whether the artificial intelligence program has got it right. The expert now has an even better tool than before.

Can artificial intelligence be mis-used? Yes. So can a filing cabinet. Do you remember those? Code breakers with filing cabinets helped win the Second World War for the Allies. That code-breaking required very crude artificial intelligence tasked with doing just one job: calculating whether an encoded message could have been created by a particular rotor setting of an enemy Enigma machine. By rejecting, say, 240 impossible settings a few possible ones could be studied in more detail. After breaking the code then real intelligence took over, and the knowledge stored in filing cabinets made sense of the messages.

Demis was interviewed by Jim Al-Khalili on The Life Scientific, a BBC radio program.
I hope this link works for you, though it may be UK only.

https://www.bbc.co.uk/programmes/m0009zbj

 
• Category: Science • Tags: Artificial Intelligence 
James Thompson
About James Thompson

James Thompson has lectured in Psychology at the University of London all his working life. His first publication and conference presentation was a critique of Jensen’s 1969 paper, with Arthur Jensen in the audience. He also taught Arthur how to use an English public telephone. Many topics have taken up his attention since then, but mostly he comments on intelligence research.