The Future of Work

Things are starting to change…

In his talk, “Ideas are Your Only Currency”, Rod Judkins recounted how a surgeon at the Royal Free Hospital, London, had asked him to teach a group of Applied Medical students on how to think more creatively. Rod Judkins is an author and lecturer from the prestigious art school, Central St Martins, College of Art.

The medical school recognised the pressing need to produce more ‘idea students’ rather than ‘students who have skills’. It was clear to them that a lot of the skill-based jobs at the hospitals are going to be redundant as many procedures, such as eye or kidney operations, can now be done by robots. Diagnostics too, are increasingly automated.

Instead, they would like to focus on training future doctors to apply creative thinking with the available medical technology. An example of this applied medical creativity is the ‘spray-on skin’ with stem cells for burn victims. They are also trying to get students to think about how current procedures can be improved. In other words, they wanted to produce more medical innovators rather than the typical doctors.

How much longer do we have until full automation?

Firstly, this depends on the sector. Some areas like agriculture, in particular grain production are already highly automated and have very little human input left. Other areas depend on coordination of a whole value chain, e.g. online grocery retailing, which can take decades to establish. Finally, there are fields where human input is currently essential and full automation is only a distant prospect.

Secondly, the introduction of new technology may be delayed where cost benefit analysis fails to justify its implementation.

Dejian Zeng is an NYU grad student who spent six weeks working undercover at a Pegatron iPhone factory in China. From the experience, he was convinced that with the current operation, the iPhone will likely never be made in the US. He said that with a wage of 2320 Yuan per Chinese worker, (around $400), it is impossible to pay even a base salary to US workers with that same amount. Thus, if the factories are to be relocated to the US the bulk of the work will have to be replaced by machines.

In other words, as long as the cost of labour is lower than the cost of machines the factories will remain in China due to the low wages. In fact, according to Zeng, tasks such as putting the camera and battery into their respective housing are already automated – hence, even the Chinese workers are under no illusion that their work station will be replaced very soon, too.

Thirdly, it depends on whether the new technology is being integrated into an existing system or is used to replace an old system entirely. If it is being slowly phased into an existing system, then coordination and fit would be the main challenges. The difficulty of coordinating the different elements of new and old technology should not be underestimated. The existing workforce needs to be retrained, including giving them an adjustment period for trial and error. In some cases, it would simply be easier and cheaper to scrap everything, re-vet the workforce, and start from scratch.

Lastly, the cause of delay to implementation may actually stem from political and legislative hurdles, and not so much from an economic one.

In a paper by Grace, Salvatier, Dafoe, Zhang and Evans, titled, “When Will AI Exceed Human Performance? Evidence from AI Experts”, a large survey asking machine learning researchers on their beliefs about progress in AI was conducted.

The result is as follows:

The researchers predict that AI will outperform humans in many activities in the next ten years, for example:

  1. translating languages (by 2024),
  2. writing high-school essays (by 2026),
  3. driving a truck (by 2027),
  4. working in retail (by 2031),
  5. a bestselling book (by 2049), and
  6. working as a surgeon (by 2053).

The researchers believe that “there is a 50% chance of AI outperforming humans in all tasks in 45 years and of automating all human jobs in 120 years, with Asian respondents expecting these dates much sooner than North Americans”.

What kind of workforce will we have in the future?

1. Human to machine

Automation gives a picture of a completely hands-free operation. The reality is that grocery crates get stuck in between conveyor belts, sensors need replacing after clocking a certain number of hours, software needs to be debugged and computer security needs to be updated.

Another factor is what’s known in the industry as ‘contingencies’, which are unanticipated complications that cannot be programmed for. For example, self-driving container trucks in their long haul across state lines may experience accidental spillage of dangerous chemicals, bad weather conditions or even just flat tyres. That is why that despite self-driving trucks, truck drivers would still be needed for the trip as a monitor and a precautionary measure.

From those needs, there could be a new job industry arising purely for maintenance, monitoring and organising of the robots, AI, sensors, and various moving parts – in fact, the rise of a whole new breed of automation rangers or mechanics to upkeep the entire auto-ecosystem.

In the meantime, we also need humans to train machines, especially in areas where we don’t have millions of data points for training. This will be a huge industry in itself.

2. Human to human

In a recent article, “Never mind the robots; future jobs demand human skills”, Sarah O’Connor, writes, “By 2030, there will be 34 ‘super-aged’ countries, where one person in five is over 65. Robots can help workers to look after these people but they cannot replace them, nor should we want them to. As the chief executive of Adidas pointed out recently, robots cannot even lace shoes into trainers, let alone help a frail person into the shower. They do not possess any of the qualities that make humans good at caring for each other, like compassion, patience, humour and adaptability.”

The noble idea of how a substantial workforce will take care of the elderly is misleading – not many will have the stamina, perseverance or dedication to nurse an elderly. It is difficult to be convinced that many Mr or Ms Nightingale can be plucked out of this device-fixated generation. To be in the care industry, one must have a calling for it precisely because the job needs a lot of patience and compassion. Those who enter because there are no other alternatives are bound to be frustrated and carry out their job poorly.  As a cautionary note, look at how many abuses there are reported in the old folks homes.

The care industry may be the fastest growing for now, but only people who have never cared for an elderly would romanticise what is in essence a very emotionally and physically demanding, non-glamorous, solitary and repetitive job. To add, the elderly might not even want to be attended to by humans, preferring rather, robotic help as to retain their dignity and independence.

Nor do the old might even need to. Advances in health science will mean that the elderly are more mobile, with advanced medicine preserving most of their cognitive functions, and if they become invalid, there is even an exoskeleton that could be used as a walking aid.

Care is expensive and there are major challenges how to pay for it. Without immigration as a source of cheap labour automation is the only sustainable solution.

3. Human and government

Is it so far-fetched to imagine that due to reduced government budgets, many civil servant posts would be made obsolete or that many types of bureaucracy ranging from building permissions to passport renewals will be processed from end to end by machine learning algorithms?

Perhaps politicians at Westminster too, would be phased out. Imagine if policies were being produced by algorithms – minimising monetary and social costs, maximising benefits – for education, healthcare or immigration. For a discussion, one would tune in to BBC Parliament channel to watch the parliamentary debates on the algorithm-produced policy strengths and biases. One then votes for algorithms instead of politicians. Would this produce a better outcome than today’s method?

Our politics and their consequences have always been a jumbled muddle of hits and misses, luck-of-the-draw exercises where we are never sure whether promises will be kept and if kept, fulfilling them come with huge execution risks and incompetence.

Policy timing would no longer be a finger-in-the-air decision but rather dependent on the assistance of Big Data. For example, an idea to privatise a particular industry may be a good idea but a collection of data might tell the population to wait a couple of more years. Or it might flag that more legal infrastructure would first be needed to support the decision before it is carried out. In the future, AI and Big Data could act as both compeller and caution-device and benefit our political system tremendously in ways unimagined now.

It was Jacque Fresco, the futurist who had recently passed away, who said, “Computers don’t have ambition, they don’t say, ‘I want to control people.’ They don’t have gut instincts.”

4. Entrepreneurs and modular solutions

The beneficiaries of technology are not limited to those who know how to code. Just like how we are able to surf the internet through browsers or prepare spreadsheet through Excel without a lick of coding knowledge, so will there be solutions that bridge the gap for those less technology-literate.

Firstly, any tasks or potential businesses will be built upon modular solutions that can be bought off-the-shelf just as if buying the ingredients for a dinner you are about to prepare. These modular solutions can be sold individually or as packages to be assembled and tailored to your entrepreneurial requirement, neatly fitting with each other as Lego bricks would do. These packages can provide analytics, access to data providers, robotics, machine learning and other AI solutions.

Just as cloud computing lowered the bar of entry to internet start-up companies a similar data, machine learning and robotics start-up scene may develop that is built on common tools and services, without requiring detailed knowledge of all areas but the one the company is exploring.

5. Human and the financial market

The Economist claims that from trading to credit assessment to fraud prevention, machine learning is advancing. From the article, the start of 2019 will see even Chartered Financial Analysts needing AI expertise to pass their exam.

There is certainly a shift for Wall Street from hiring Ivy League jocks to siphoning-off as many quants into the industry, and the benefit of using so many quants have already begun to show. In fact, the Economist writes, “Quant hedge funds, both new and old, are piling in. Castle Ridge Asset Management, a Toronto-based upstart, has achieved annual average returns of 32% since its founding in 2013. It uses a sophisticated machine-learning system, like those used to model evolutionary biology, to make investment decisions.

It is so sensitive, claims the firm’s chief executive, Adrian de Valois-Franklin, that it picked up 24 acquisitions before they were even announced (because of tell-tale signals suggesting a small amount of insider trading). Man AHL, meanwhile, a well-established $18.8bn quant fund provider, has been conducting research into machine-learning for trading purposes since 2009, and using it as one of the techniques to manage client money since 2014.”

The rise of robo-advisors and other Fintech services signal coming changes as well. According to the BlackRock Global Investor Pulse Report, 58% of Millenials respondents would be interested in robo-advice compared to 26% baby-boomers.

6. Human and construction

According to the article “Why the Construction Industry May Be Robot-Proof”, “Well, there is something unique about housing. Typically, home construction activity is custom work – remodelling, renovation, teardowns replaced by a single home, maybe a few homes built on a cul-de-sac. And it is difficult to gain economies of scale – or to automate processes – when every job, or close to every job, is unique.”

Outside some prefab and highly standardised new builds using some 3D printing technology much of the building industry will remain very human centered. Although jobs like architects and interior designer could be machine learned, clients would still want to interact with humans when discussing the design of their house – unless it’s much cheaper to do otherwise. Automating a job like hanging wall papers, with all the non-uniform surfaces and odd corners in a typical house, cannot be done easily in the near future.

Construction is also happening in the virtual world. The virtual reality (VR) and augmented reality (AR) market will be worth almost $37 billion by 2027, according to the latest analysis conducted by IDTechEx. We are underestimating the number of creators, artists, programmers and audio specialists the developers will need for this space.

7. The unemployed and Jugaad

Many become unemployed as human capital becomes neither complementary to machines nor are they cheap enough to make using machines non-viable. This aggravates wealth and income inequality. In the US, the share of wealth owned by the bottom 80% has fallen from 18.7% in 1983 to 11.1% in 2010. Median family income has stagnated while incomes rose significantly for the top 1%.

In the case for technology, inequality may result in little or no access to new technologies for the lower rungs of society. A simple example would be where the poor could only afford bargain-priced ink-based printers while the rich have long upgraded theirs to germanium-based printers.

Jugaad, according to the Wikipedia, refers to “an innovative fix or a simple work-around, a solution that bends the rules, or a resource that can be used in such a way. It is also often used to signify creativity – to make existing things work, or to create new things with meagre resources.”

Just because you are unemployed, doesn’t mean that you don’t have to continue to ‘labour’ for your comfort. It may just be, that as a direct result of many becoming unemployed and lacking resources, they are forced to lengthen the lifetime of their existing technologies by repairing or modifying them. If a little part of their device gets broken for example, rather than throwing away the whole device and buying a new one, they may have to rely on a 3-D printer to print the replacement part. The 3-D printer may be operating commercially at a shop, or locally owned by the council for public use.

Necessity is the mother of invention and we might see the spirit of Jugaad being adopted not just in India, but everywhere else in the world.

Validity of the claim and does it matter?

In “The Zombie Robot Argument Lurches On”, Lawrence Mishel and Josh Bivens write that our claim of ‘robots taking over jobs’ is based on a flawed analysis and there is no basis for claiming “automation has led – or will lead – to increased joblessness, unemployment, or wage stagnation”.

Therefore, any policy recommendations based on this flawed analysis, ranging from redesigning education and retraining the workforce to providing universal basic income, would not make much sense. Furthermore, Mishel and Bivens emphasise that the automation narrative is not validated by the Acemoglu and Restrepo report, writing, “The estimated impact of robots is small, and automation broadly defined does not explain recent labour market trends.”

Here, Mishel and Bivens were referring to the Daron Acemoglu and Pascual Restrepo investigation into the equilibrium impact of industrial robots in local US labour markets. Acemoglu and Restrepo concluded that only a relatively small fraction of employment in the US economy are being affected by robots and therefore, there is no support of the view that new technologies will make most jobs disappear and humans largely redundant.

Mishel and Bivens urge us not to be distracted by this ‘zombie robot narrative’, focusing instead on current issues such as wage stagnation and the rising inequality stemming from failure of macroeconomic policy and globalisation. Which brings us to the question, is this the right way to frame the issue?

Whether you have evidence for this right now or not it is important to remember that many decisions have a very long lead time, such as how to educate our children or how to design government policy.

Personally, between the doubters and the dreamers, I know who I would choose to believe in.

What should we do to prepare?

1. Measure and track for good policy decisions

In the report, “Information Technology and The U.S. Workforce: Where are We and Where do We Go From Here?”, Brynjolfsson et al recommend developing a series of indices such as:

  • Technology progress index
  • AI progress index
  • Organisational change and technology diffusion index

To complement this, I think, would be to appoint a committee of ‘machine economists’ to produce a subjective, annual report of progress on technology and workforce – with good bullet point summaries for TL;DR readers. They can use proxies, such as the most impactful new device to come into the market or numbers of students graduating from technology related courses, and so forth. Whatever event that these ‘machine economist’ deem significant would be included in the annual report, keeping in mind that the intended readers are other economists, policy makers and journalists.

The idea is to focus more on the end result of the technological progress rather than adding up all the inputs that make up technology. Maybe this would be more useful as well as easier to account. One can then surmise the progress by following the evolution of the annually produced bullet points.

2. Innovative education more suitable for the ‘New Machine Age’

I think we have an imperative to redesign an education system better-suited to this technological revolution, not in token resistance to being replaced by machines, but rather to take advantage and multiply these technological dividends as much as we can. Looking at the welfare and social situations of many nations today, the decision to change the current education system may prove necessary rather than merely discretionary.

We need to equip the future workforce with a mind-set to take advantage of all the new possibilities that technology would bring. After all, didn’t Richard Hamming, the American mathematician say, “Teachers should prepare the student for the student’s future, not for the teacher’s past”?

Children need to be exposed to data handling and basic programming at a much earlier age – as early as four or five. In general, these concepts are currently introduced either during the secondary school or at the university.

By introducing data collection, probabilities and other statistics, arrays, IF/THEN, loops, and related ideas in bite-sized and fun format, the children will grow up being familiar with these concepts and learn them naturally. Furthermore, it’s good to teach children logic, a useful way of thinking that would benefit other areas of life too – much more useful than having them memorise the times-tables. I strongly believe that getting an education should be an adventure and not torture.

Creativity will be another important outcome of education, something that machines are still rather poor at, in contrast to rote learning of facts.

The objective is not that they all become programmers, but rather that they become technologically literate – think of how developing nations make the English Language as a subject in schools, not to have a bunch of English teachers, but so that the students can do jobs conducted in the English medium. Similarly, while we don’t know the exact nature of future jobs we can be fairly sure that reliance on machines for repetitive work will increase and humans will be required for more creative and lateral thinking type tasks.

3. Counter the negatives

Professor Ian Golding who runs the Oxford Martin programme on technological and economic change assessed that we are underestimating the shock that technology will unleash on the world. According to his interview with the Business Insider Australia, he believes that we are on the brink of a ‘premature de-industrialisation’ that will “rattle societies in developed and emerging nations, as huge amounts of industrial labour is re-shored to advanced economies with fully automated production systems.”

To quote him, “There will be a re-shoring of production to the advanced economies and of call centres and other machine processes. Of course, this won’t be a re-shoring which will be labour intensive; it will be capital intensive. So, it’s not going to create jobs. I see that one of the real downside risks associated with this is a rapid widening of inequality. Large swathes of people, I think, will find that it’s challenging to get decent jobs. There will be lots of jobs for unskilled and service people, things that don’t require much machinery.”

The implication of this is that for developing countries, the path where wealth can be achieved through stages of industrialisation has just vanished into thin air. The global consequences of this would be economic growth slowing long before catching up to developed levels. At the same time, adopting increasingly cheap technology from around the world should raise living standards even in the poorest places, even if countries fail to raise their productivity much on their own.

What of the developed nations? At the backs of our mind is the realisation that without a share of production, the bottom 80% would remain in relative poverty and little opportunity to improve their lot. This kind of social composition cannot possibly be sustainable, even in a developed country with relatively better social welfare.

Recently, Eric S. Lander, president of the Broad Institute of MIT and Eric E. Schmidt, executive chairman of Alphabet, worried about the lack of funding for research in the US, shared an op-ed in the Washington Post,

“The United States has the most dynamic private sector in the world, with entrepreneurs, investors, big companies and capital markets all eager to license technologies and launch start-ups. But those ventures are often driven by technologies that come from basic research. Few companies undertake such research because its fruits are typically too unpredictable, too far from commercialisation and too early to be patentable.

That’s where government comes in. While investing in basic research typically doesn’t make sense for a business, it has been a winning strategy for our nation. For 60 years, the federal government has invested roughly a penny on each dollar in the federal budget into research at universities and research centers. In turn, these institutions have produced a torrent of discoveries and trained generations of scientific talent, fuelling new companies and spawning new jobs.”

In other words –

4. Competitive landscape

One major concern to be addressed is the rise of superstar firms. In “The Fall of the Labor Share and the Rise of Superstar Firms”, Autor, Dorn, Katz, Patterson and Van Reenen posit that if globalisation or technological changes advantage the most productive firms in each industry, product market concentration will rise as industries become increasingly dominated by superstar firms with high profits and a low share of labour in firm value-added and sales. As the importance of superstar firms increases, the aggregate labour share will tend to fall.

They found that, “firms with superior quality, lower costs, or greater innovation reap disproportionate rewards relative to prior eras. Since these superstar firms have higher profit levels, they also tend to have a lower share of labour in sales and value-added. As superstar firms gain market share, across a wide range of sectors, the aggregate share of labour falls.”

Unlike previous episodes of increasing firm concentration though these superstar firms may be the ones undertaking the kind of ground-breaking research that delivers a better future, without hurting consumers through higher prices which are often close to zero marginal cost anyway. It will be important to rebalance the patent system such that these new giants can’t lock out rivals forever through litigation and to occasionally make these new natural monopolies open up their data to others.


Nothing comes without costs, especially in a technological revolution such as this. We are potentially facing massive unemployment and a tsunami of shifting and re-ordering of the workforce as we have never known before.

What may place us at risk is our inability to reform ourselves, and our way of doing, in time to mitigate the negative impact on the workforce. What concerns me is that in assuming a defensive position against technology, we fail to capture all of the abundant dividends the technology may bring us.

Worse still, if we let the old technology crystallise for lack of enthusiasm and nostalgia for the past. All this, because we fear the future too much and act too little in the present.

We should approach the future of work with optimism instead. Creativity, lateral thinking and ambition are all human strengths that will allow us to achieve great things in conjunction with machines.

Given the rich bounty of automation we’ll also be able to raise the living standards of every human being on earth, while at the same time making the remaining work more meaningful and less soul-destroying, whether through fewer hours spread across more people or through more interesting work.

House Prices One Hundred Years from Now

I would like to commend Professor David Miles for a fascinating talk on the causes of rising house prices, going beyond the usual suspects and looking at technology and incentives. Given the short lecture format not everything could be covered, so I would like to add some of my own thoughts from the point of view of economics and technology.


The decline in interest rates since the early 1980s, both nominal and real, have certainly had a significant effect on house prices. The decline was driven by disinflation and the resulting lower volatility in inflation, which allowed real rates to go much lower. A global savings glut and more recently, monetary stimulus are additional factors. While this is a well-known fact, it is nevertheless important in any discussion about house price growth.

These factors raised affordability at a fixed share of earnings. As much as economists like to look at everything in real terms, nobody in the 1970s could borrow against future inflation if monthly payments would be crushing at double digit interest rates. The longer duration made possible by lower rates would therefore unlock earnings decades in the future to borrow against, rather than being heavily front-loaded while interest rates were high.

Banks went along and raised their limits for maximum lending to earnings, with a significant lag, partly because it takes a long time for stress test interest rates to reduce as well. In other words, when banks ask the question of whether can you afford your repayments if interest rates rise to x%, the x is decreasing very slowly.

However, at the current zero lower bound, there is not much upside to house prices from this factor alone but plenty of potential downside.


What is often missing from the analysis of house price growth (without undertaking a literature review) is a breakdown of how people are actually financing house purchases far above the maximum bank multiples of 4x earnings. Detailing the sources of this further equity or debt would help to determine whether any of these are sustainable.

Increasing equity via repayment of previous homes certainly is sustainable, inheritance and parental gifts probably is too (unless taxed too heavily). On the other hand, rising home equity from appreciating prices may not be counted on as a source of increasing equity as people usually move to more expensive houses than they were coming from. As pointed out in the lecture, older people moving from expensive to cheap accommodation are becoming a rarer feature of the housing market.

Another route to raising affordability is raising the maximum multiples of mortgage to earnings and reducing minimum equity requirements. Having just been through a harrowing financial crisis this is unlikely to occur for at least a decade.

Consumer preferences

The lecture covered the topic of trading more space for other things. It appears that the appetite for more space is unbroken, doubling in the last few decades in the US, which are a truer expression of preferences than the artificially constrained picture in the UK. There is a possibility that ‘peak stuff’ may put an end to this trend. ‘Software eating the world’ has removed the need for many devices, disks and books in the home, the switch to LCD TVs hanging on walls from bulky tubes has reduced removed many TV stands. VR could one day even make these obsolete and with it the distance between screen and seating.

A trend towards eating out more or relying on ready-made foods is diminishing the role of the kitchen, which could shrink in decades to come. Or it could absorb the role of the dining room, which appears to be on its way out. Storage space for groceries could also shrink as people switch to more just-in-time delivery that’s getting cheaper all the time rather than having to store months of supply from buying Costco sized grocery lots. The sharing economy could reduce the need for much stuff further, e.g. power tools, lawnmowers and other rarely used items, where lower transaction costs make it much easier to hire the required tools or skills by the hour. Of course, people have been creative in filling up the space with other things, e.g. home gyms, games rooms and ever larger bathrooms with saunas, Jacuzzis etc., as I have discussed in this previous post.

One piece in the growth of demand is however certain: the sharing of space of unrelated people (or of people in unhappy marriages) or living with parents in their 20s and even 30s due to cost would end if space was cheap enough.

Building technology

The example of very tall and slim skyscrapers in the lecture is only one of many new technologies, maybe not even the most significant. Prefabrication and 3D printing could have a profound impact on the time and cost of construction. In 2015 a 57 story building was put up in 19 days and there are now early prototypes of 3D house printers and automated brick layers. Building and outfitting have not really improved in their productivity for decades. Assembling modules off site or autonomously with robots/3D printers instead could lead to large cost decreases.

By reducing the cost of going up in height it may be possible to increase the incentive paid to landowners with existing structures to tip the balance in favor of the agreeing to higher plot ratios, as discussed in the lecture. Similarly, not all countries have basements by default in most houses, with cheaper digging technology (unlike other building tech this is currently not heavily researched) this most unobtrusive kind of extension of living space would be of great benefit.

Planning rules

Focusing on the UK at first I would like to reference a number of publications by Policy Exchange, starting with this article. It lays out very clearly that the lack of local incentives is one of the main reason behind the lack of suitable space to build on. Fixing this would unlock a great amount of land that could lead to better accommodation for a great many people while remaining affordable.

Giving locals a share in the upside from new residents rather than just the downside of more crowding is something a more federated system of government could deliver, see Switzerland as an example of this. In addition, the oligopolistic hold on the housing market and land banks enjoyed by the large developers could be broken by selling land to individuals who would build on it instantly, rather than holding out for higher margins later. Examples such as Austria where 80% of properties are self-built support this.

I’d like to point out in particular that the so-called green belt around London in fact includes a great deal of farmland within a few miles of fast train connections to the center. This is a colossal waste of resources. Parks and woodlands are greatly valued by local residents and in frequent use and should remain protected. Densification by converting people’s gardens into more houses is usually hated and not a way forward. And while brownfield development is always cited as the way out of this crisis there’s only so much of it and it’s not usually where people want to live.

Surveys consistently show that the most preferred accommodation is a (semi-)detached house with a garden, yet very little of this that’s affordable is being created. Farmland is of low value (in 2010 a reclassification led to a 200x gain), has no use to anyone other than the farmer and in fact is net negative for biodiversity and local health due to spraying of pesticides and fertilizer. Not even the views over the empty land are that attractive. The correct test for keeping land as protected greenbelt should be whether it is accessible and used by the public. Farmland within and just outside the M25 does not meet this test and should be opened for widespread development, especially where it is within short a short distance of fast trains.

Two international comparisons stand out as interesting. In Tokyo it is possible to buy detached houses of decent size within 20 minutes commuting distance of central business districts at $300-400k. This is partly due to excellent transport but also because plot sizes are very small and going up is done in a way that is fairly attractive and preserves privacy. Houses are often torn down after 30-40 years. This may result in slightly higher total cost of ownership but it also enables a much better matching of housing preferences to housing stock.

If cheaper technology enables going from 3 to 4 or 5 floors at similar costs this can be done on existing land as part of the normal replacement cycle, all without requiring additional land and new transport infrastructure. It should also be noted that there are much fewer limits on design of such houses, leading to a much greater variety than can be found in other countries’ monoculture. While it is second best to a house with a garden it maximizes floor space while minimizing commuting time, a trade-off many in the UK would be happy to make.

On the other end of the spectrum is Houston, a city that has not made any attempts to rein in sprawl or impose many zoning rules. The result is affordable housing with plenty of space for a great majority of people. It comes at the cost of longer commutes but as can be seen from the next section technology can be of great help here.

Transport and communications technology

If we are looking one hundred years into the future, it is a near certainty that we will be in an age of autonomous vehicles. This leads to two profound implications:

  1. Space currently devoted to parking where people live will shrink dramatically as car ownership moves to a shared model (see recent Economist cover story), creating more land for living, and
  2. The radius of where people may travel from increases greatly, because of greater speed and comfort.

In terms of parking, space would free up both in the city centers, around transport hubs and on driveways as a far smaller shared fleet is needed for the same level of mobility than in a model of individual ownership. In residential areas, garages and driveways could be rearranged for more living space or units. Parking structures could be replaced with new high rise apartment blocks.

Travel will take two distinct modes, either home to transport hub or home to final destination, based on the density of the city. The first case usually covers cities in Europe and Asia where the dense urban core already has good public transportation: here it still makes sense to rely on trains to bring people to the city center, however the trains bringing them there could be sped up to much higher express levels with far fewer stops if the trip from house to station could be made autonomous. At the transport hub no parking would be required and the time in the vehicle could be spent sleeping or working.

In sprawling cities, transport will be fully door-to-door. Autonomy there would lead to much better traffic coordination, smaller gaps between cars and shorter journey times. Speed limits could be raised significantly. All this will happen without wildcards like Hyperloop or Boring company tunnels, which could improve on this further.

With regard to travel radius, there are four distances to consider when people make choices about a location to live, in no particular order:

  1. commute for employment,
  2. children traveling to schools,
  3. local shopping and entertainment amenities,
  4. distance to community and relatives.

In the context of employment, the rise of remote working is an important factor. While early projections of the death of the office have not played out, a mixed model may be emerging whereby people only commute on some of the days or for shorter workdays, completing a significant amount of work at home. This could reduce aggregate time in transport, so a daily one way 45 minute commute could be replaced with a 3 day a week 75 minute commute, or the commute would be scheduled for off-peak hours to avoid traffic with the rest of the work being done at home.

Much local traffic is about sending children to schools. In many countries parents have a preference for them to be within walking distance. With autonomous vehicles this is a much lesser consideration, children could commute from home to even distant schools in autonomous vehicles without their parents’ involvement, opening up additional employment opportunities to them. This would enable either families or schools to spread out much further than currently possible.

Shopping is being automated at a very fast rate, including groceries. Autonomous delivery is another near certainty over long enough horizons (see my previous post here), cutting down on the number of mandatory trips. While not everyone will adopt such a lifestyle, a significant proportion of the population that’s not interested in shopping as an experience or much entertainment outside the home (e.g. eating out) is enough to reduce demand for living close to such amenities.

This leaves distance to community and relatives as a key consideration. Again, the generation growing up now is far more used to interacting on social media and less reliant on in-person interactions so the importance of location in this respect may decline too. Opposite considerations can come up here as well, whereby it may be as much about avoiding particular communities than it is about finding them.

With communication and transport technology solving most of the distance issues, the main remaining reason for a choice of location is related to status and some unspecified “feel”, whereby city dwellers like the noise, buzz and freedom of a large city whereas more rural residents prefer peace, quiet and fresh air.

Population growth

The model of ever rising house prices rests on the assumption of growing populations, but in many countries there’s not much rural population left to move into cities, birth rates are below replacement level in many countries and immigration isn’t at the scale to offset this and may never be. Life extension technology is at its infancy but over one hundred years could achieve significant breakthroughs, leading to population increases from lower death rates. Absent that scenario, the megacities are the most likely centers of growth, taking population from smaller cities as life will focus more and more around these megacities. The impact on house prices in faraway places then hangs on the question whether truly distant commutes like the one mentioned in the lecture from Somerset to London become viable.


My conclusion regarding the question of 100 year house price growth is as uncertain as the lecture’s. It depends on how many of these threads play out. The finance industry won’t be a positive factor in raising long term prices, at least in the near term, but large scale inheritance could be. The necessity of living near work, school, family etc. will certainly reduce but this could be replaced by a much stronger preference for city living, continuing a very long trend. Centuries-old building technology is due for a much needed shake-up like all other technologies but greater density may clash with preferences. Whether demand for space will keep growing also depend on how space-shrinking technology offsets our natural desire for ever more of everything. Demographic trends 100 years into the future are also uncertain, central predictions are set for declines in most developed countries but immigration and life extension could also change these.

It is only due to human ingenuity that we have achieved incredible living standards, constantly managing to achieve more output with less input. It would be a shame if we couldn’t bend the cost curve for housing as we have for almost everything else in this world. We owe it to future generations.

The Problem With Smart People

The problem with smart people is that they are able to justify their wrong actions with better arguments. This gives them a troublingly unfair advantage over the rest. With that above average ability they attempt to persuade us with explosive fireworks of reasoning that deafen our hearing with their loudness, and daze our sight with their brilliant flashes.

Some amongst us would be easily convinced, while some others, even though we do not whole-heartedly agree, couldn’t find in our minds a path of well laid-out reasons why we shouldn’t just succumb. In this way, those in power have always employed the smarter ones to be marketers of their ideas so that they could increase their already large influence even further.

What then is the defence of ordinary people who have not read Plato nor know Newton’s Laws? Are we defenceless from our lack of scholarship and charming wit?

No, we are not.

In everyone, despite our differences in background and education, I believe there is a sense of what is right and what is wrong, possessing the ability to identify what is unfair, unjust or outright unconscionable. An intuition fully ingrained that does not require a brilliant mind to justify a particular rationality, but rather a compassionate heart to recognise.

Perhaps this is the way that nature balances out those with superior intelligence but no heart, by installing the intuitive wisdom of the ages deep inside those with not as equally brilliant a mind but plenty of heart.

Caveat: I don’t propose a purely irrational, emotional-dependent view either. Instead, a healthy balance of both reason and wisdom-led compassion.

New Possibilities in Autonomous Delivery

A few days ago it emerged that Amazon had put a dozen employees to work to investigate self driving technology. This is a fairly small scale effort that has not gathered much attention but it could turn out to be equally significant as the much more prominent drone effort.

The public is enthralled and at the same time terrified by a future of drones ferrying goods and people around cities. It is hard to imagine the airspace filling up with drones that significantly replace the tens and hundreds of thousands of journeys of people travelling to work and delivery drivers making their drops. While only able to operate in two dimensions the road system remains the best option here as the space around each vehicle can be very small, especially if the majority is self-driving and is communicating with each other to avoid collisions. By contrast even a small fraction of failing aircraft would wreak much greater havoc. The noise coming from even the quietest electric drones would be deafening if there are thousands. And finally the push-back against privacy invasions from drones is not to be underestimated.

This leaves ground transport as the only viable large scale transport option. However, the last yards, as opposed to the last mile, are still difficult to cover for delivery traffic. This is where a combination of autonomous delivery trucks and drones could be very promising.

The basic idea would be that a delivery truck could carry a small fleet of drones that are ready to dispatch packages to the intended recipient. After approaching the destination, a drone would emerge from the roof of the van and fly to the destination.

In the suburbs this could be an area at the back of someone’s house (as in the early Amazon drone videos), or a drop box at the front that only opens for an approaching drone. It could even hover in front to allow someone to take the package. As the back is typically secure it could drop things without the owner being there. The privacy implications would be minimal as the package would only fly a few yards, possibly over your house in order to deliver what you ordered.

In more urban areas you could imagine multi-apartment buildings (without manned receptions) to be upgraded. Similar to individual air conditioning units drop boxes could be installed on every apartment for a few hundred dollars that would open to receive deliveries. If the windows are big enough you could even imagine them to open automatically to allow for drops and the drones depositing the package right inside your home. Balconies are another great potential drop point. Apartments with only backyard facing windows are no obstacle as the drone would just go over the building to reach the other side.

Large apartment blocks without opening windows or balconies and businesses would probably continue with manned desks for accepting deliveries for a while but automating these, including drone flight indoors are possible in a more distant future.

This leaves only very rural areas where we’d see long distance drone flight as there would not be enough packages to require a van to send there. It also opens up otherwise inaccessible places, very important in the developing world.

It could even eliminate the need to park. Instead a delivery van could circle a block, release one of its dozen drones whenever it is closest to the destination building to make drops. It would then return a few minutes later to collect them again, potentially without ever stopping as drones fly out and land while the vehicle is moving at normal speeds. In each case the flying distance would be only a few tens of yards horizontally and a few tens of yards vertically, if they have to go over a building to reach the other side.

There are added advantages. The battery technology to cover a few hundred yards is very unchallenging, unlike the multi-mile journeys from depot to house. The drones could recharge inside the van until the next drop. Given the lower range they could also carry larger weights, making autonomous grocery deliveries including drinks practical. There are fewer safety issues: they’d be close to the ground while making the horizontal journey, avoiding pedestrians and other obstacles carefully. They’d then find a safe square meter or so without people beneath them to make the vertical climb to reach the destination and make their drop, before returning again.

By contrast, a much hyped competing technology of small autonomous ground crawling delivery vehicles seems less promising. There is no mechanism to drop the contents if the owner isn’t there and even small curbs seem like a major obstacle. Drones could hover or even set down temporarily in order to avoid all pedestrians much more easily, while always being able to fly over or across obstacles. For added safety drones could be prevented from flying where pedestrian density is above a certain level. It’s also to be determined whether it would be safest to fly them at eye level (with mesh around the rotors to protect pedestrians) or at 3m height just above people, while still avoiding flying directly above them at all times. Also, the maximum weight of any single drone package could be limited to no more than a few kg. All these measures would result in very safe operation where falling drones should never cause much injury.

Eventually you could imagine all kinds of delivery being handled this way, not just packages but also daily mail, groceries and take-out food. The drone-releasing vehicles could come in all sizes, from scooter sized single drone ones serving time critical take-out deliveries that can swerve through traffic to very large vans that serve large areas.

Another benefit could be to switch away from cardboard packaging, which requires recycling and more garbage truck trips. Instead, you could imagine reusable plastic crates being used. They don’t need to be locked as the grip of the drone would act as a lock until delivery is complete. After announcing its impending arrival a few minutes earlier it may be that a drone landing in someone’s backyard, window or front room would then give 1-2 minutes to the user to empty the crate to take it away immediately again. If that is not an option it could be left in the same spot for pick-up during the next delivery and a deposit system could be used to incentivise their re-use. Closed plastic crates are also better in any weather than cardboard that can get wet.

Completely autonomous deliveries could also be shifted to off-peak hours, including night-times when traffic is very light so this could also help reduce rather than increase traffic.

Unfreedom of Speech

Those who are the masters of platforms have to be extremely cautious in upholding freedom of speech. In an environment where fake news spread with ease but where the education system has failed to produce enough critical thinkers, we need to guard against abhorrent views that leave stains like curry on a cotton shirt. Allowing free speech is not the same as permitting carelessness that normalises hatred, leaving it permanent in the fabric of our society.

How can we tell whether a view is abhorrent or not? One giveaway is that it fosters the feeling of superiority in one group of people above another group. Opinions that are conveyed within a mere hour can justify resentments in those that had already held them. This can undo decades of work that aims to raise the status of minorities, on the basis of justice and equality, overcoming many roadblocks to achieve the same opportunities and recognition.

The counter argument is usually, why not fight falsehoods with truth and facts, or are we scared of a little debate? To that I say, where did that thinking get us with Trump? Can we really assume that everyone will know the truth when presented with it? And let’s not forget those who know the truth but willingly turn their backs on it.

After the Brexit referendum result was announced, 289 cases of hate crime were reported the day after. Again, that’s a record of 289 cases in only one day. This tells us that for some, all they needed was (what they perceived) as tacit agreement from society that their hatred is justified and therefore, can be expressed openly.

Often, the consequences of hateful speeches do not end in the hall where they’re held. The effects ripple out onto the streets and manifest in aggression that may harm others. Some people who come to these events may not only come to listen to the talk, but also to tally those attending, how many there are in agreement with such views. A large enough crowd will make them feel more assured to voice or act out the hostility that has been kept hidden for so long.

My friend in Westminster who works in higher education said that there has been a drastic increase in violence towards minorities in universities. Last year, shortly after Brexit, the police reported that there had been a 42% spike in hate crime and numerous reports of ethnic minorities and immigrants being targeted for racial abuse.

In Croydon two Fridays ago, a 17 year old Kurdish boy was severely beaten by a mob of up to 30 people when he admitted to them that he is an asylum seeker, witnessed by onlookers from a nearby bus stop. He was left with a fractured spine, shattered eye and bleeding in the brain. He is now fighting for his life.

I too, have been mistreated (though not beaten, but verbally abused) at an art gallery by those brazened by Brexit, who thought that I did not belong there and that now it’s socially acceptable for them to say so. And that wasn’t the only time. Now I am fearful of going to places where people might think that I don’t belong. And when I do, always keeping in mind to be out of the way and become a wallflower. This has made me think that freedom of speech resulting in the loss of freedom for others is not really standing up for freedom at all.

Masters of platforms need to exercise some wisdom and common sense. Don’t close your eyes to the fact that by permitting or encouraging, you are complicit in fostering hatred and division. Everything has its good and bad. Freedom of speech too has its evil, perhaps not to the listeners of the speech, but rather to the group that can get hurt by the actions resulting from the speech’s message. Holding up pure ideals without taking into account human behaviour and eccentricities, their capacity to overreact and be riled up, is being negligent in the protection of the fragile groups of society.

When they are young, by all means, teach them the sacred value of freedom of speech. But when they are a little bit older, do teach them about moderation and practicality of holding onto ideals, including their unintended consequences.

I believe in free speech. I believe, I truly believe. But falsehoods and hatred can win if we are not careful.

That’s what I’m afraid of.


On technology and labour

In this week’s Economist Free exchange column entitled “Remember the Mane”, Ryan Avent asks why productivity lagged while technology adoption is on the rise. Reading the article, I can’t help but wonder whether we are focusing on the right things.

Firstly, many commentators tend to lump all types of technological progress under one header, but this leads to rather blunt analysis. There are many types of automation for instance; sensors, machine learning and robotics, just to name a few. These affect the rate of replacement of labour and productivity differently within each industry.

With each passing year, the price of sensors as well as their sizes get smaller and smaller. At the same time, coupled with better computer processing power, the fields of machine learning and robotics are advancing in leaps and bounds. Sensors may replace factory workers in charge of checking for defective products or fruit sorters in the farms. On the other hand, better machine learning may one day replace accountants, lawyers and journalists. (Economists, of course, are irreplaceable and safe from automation.) Like so much in economics, we need more micro and less macro!

Secondly, what if we don’t view this issue from a Luddite vantage point and concentrate instead on the possibility that we don’t make the breakthroughs required for society to thrive. What if the government and politics, or a whole hosts of other factors get in the way and cause a slowdown in technology? What if self-driving for instance, gets such a bad reputation through a series of unfortunate events that it becomes socially unacceptable to implement? What if genetic engineering degenerates into a war of patent lawsuits and stalls?

Living with “less work” plus “more technology” is a clear trend. Although we should worry about both parts of that equation, we should perhaps put greater emphasis on how to ensure the “more technology” part remains sustainable instead of attempting to mitigate the consequences of “less work”.

Thirdly, we are still at the point where the economy is able to afford automation, which unfortunately, replaces those under employment or keeps the remaining unemployed. What if one day, the economy cannot sustain the renewal of technology despite the availability and innovation of new technology. Much has been written about potential solutions for the unemployed, e.g. UBI, taxing robots, reducing working weeks etc. However, something that has not come up before could be the crystallisation of old technology.

What would such a world look like? Well, picture Cuba that was once rich. In the 1960s they were driving the latest American cars, but after a sharp drop in purchasing power they’re still driving those cars well past their normal asset life. In other words, automotive technology has not advanced for fifty years on the island, it has crystallised. One could argue that if technology deflation happens at a faster rate than the rate of fall in earnings we can keep holding off this effect, but then again, who knows?


A poem by Jane Hirshfield

A librarian in Calcutta and an entomologist in Prague
sign their moon-faced illicit emails,
“ton entanglée.”

No one can explain it.
The strange charm between border collie and sheep,
leaf and wind, the two distant electrons.

There is, too, the matter of a horse race.
Each person shouts for his own horse louder,
confident in the rising din
past whip, past mud,
the horse will hear his own name in his own quickened ear.

Desire is different:
desire is the moment before the race is run.

Has an electron never refused
the invitation to change direction,
sent in no knowable envelope, with no knowable ring?

A story told often: after the lecture, the widow
insisting the universe rests on the back of a turtle.
And what, the physicist
asks, does the turtle rest on?

Very clever, young man, she replies, very clever,
but it’s turtles all the way down.

And so a woman in Beijing buys for her love,
who practices turtle geometry in Boston, a metal trinket
from a night-market street stall.

On the back of a turtle, at rest on its shell,
a turtle.
Inside that green-painted shell, another, still smaller.

This continues for many turtles,
until finally, too small to see
or to lift up by its curious, preacherly head
a single un-green electron
waits the width of a world for some weightless message
sent into the din of existence for it alone.

Murmur of all that is claspable, clabberable, clamberable,
against all that is not:

You are there. I am here. I remember.

Jane Hirshfield, a current chancellor of the Academy of American Poets, is the author of The Beauty, a book of poems, and Ten Windows, a book of essays.