Fully Automated Luxury Communism A Manifesto

In most developed countries, particularly in Europe, lower growth is already rubbing up against higher spending. In the UK the costs of health and long-term social care, the state pension and other benefits are forecast to increase annual spending by 2.5 per cent of GDP every year in the decade after 2020. Between 2016 and 2030 Britain’s population over sixty-five will grow by a third while its ‘oldest old’ – those over eighty-five – will almost double. While politicians perennially talk of ‘balancing the books’, in the context of demographic change – as well as a failed economic model – it is clear that under such conditions large budget deficits would be permanent.

Ageing in Britain: Austerity beyond Austerity

In 2017, Britain’s Conservative Party lost their parliamentary majority. Seven weeks earlier when Theresa May called a snap general election, anything short of a landslide victory had seemed impossible. While there was much to commend in how Labour fought back from the brink, it is hard to ignore just how poorly the Tories fared – their nadir being one of the great unforced errors in modern politics: the ‘Dementia Tax’.

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While the proposal proved to be the election’s turning point, it was as much a response to long-term necessity as political naivety. Its logic was simple: people who need social care should pay for it themselves until the value of their assets, including their home, reaches a floor of £100,000. While a family would never be forced to sell a property during a patient’s lifetime – with the cost being recouped only after death – for many this was tantamount to introducing a new inheritance tax. That led to widespread anger, particularly among their voter base, because while seemingly progressive, the policy created a lottery in how medical services were paid for. If you had cancer the cost of treatment was socialised through the NHS, whereas if you had dementia you were on your own. The Tories included the policy in their manifesto, framing it as painful but necessary, because they incorrectly believed their lead to be unassailable.

And yet there was more to the Dementia Tax than political myopia. The emphatic changes it proposed, which so outraged long-time Tory voters and activists, at least represented a response to the crisis of ageing. Whoever governs, and whatever their ideological views, increased life expectancy and declining fertility rates – two trends which will ultimately impact every society – call into question the viability of socialised health and social care. June 2017 won’t be the last time a major political upset is caused by the politics of ageing.

Any presumption that the leading causes of death will remain static over the next century ignores just how much has changed over the last hundred years. Where infectious diseases like tuberculosis and influenza were once the biggest killers of all, they have retreated, with age-related illness accounting for around two-thirds of global mortality every year.

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Indeed by 2016 the leading cause of death in England and Wales was no longer heart disease, but Alzheimer’s and dementia – a significant shift. Already the sixth leading cause of death in the United States, it is reasonable to expect that elderly dementia will become increasingly prevalent as life expectancy improves (already in 2013 it was forecast that the global rate of dementia would triple by 2050). Given the economic cost of the condition already – \$818 billion in 2015 – it is clear that between squeezed public finances and a shrinking workforce relative to the elderly population, major change is inevitable.

Part of the reason why is that the challenges of ageing and healthcare are exponential.

Similar to how Moore ’s Law has meant extraordinary progress in digital technology, there is an exponential function between age-related medical conditions and the progression of years. This means ageing is a far greater issue than even pessimists might initially presume: the chances of sufering Alzheimer’s roughly doubles between the ages of seventy and seventy-five, and doubles again between seventy-five and eighty. For progressively older societies, with ever-larger concentrations of the ‘oldest old’, this poses an unprecedented challenge. Even if we can mitigate or potentially cure things like cancer, heart disease and stroke, the sheer accumulation of conditions like Alzheimer’s would ultimately prove too much to manage.

But here, as with the other crises of technological unemployment, climate change and resource scarcity, the Third

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Disruption ofers a solution which not only meets the challenge but goes well beyond it. As with those other responses – in energy, labour and resources – it is underpinned by the tendency to extreme supply.

The reason why is that while information ‘wanting to be free ’ might initially seem limited to relatively marginal areas such as music, film and literature – as well as new forms of collective action and even automation – it is set to be of greatest importance of all in healthcare. Perhaps that shouldn’t be a surprise. After all, every living organism is essentially a composite of material and information, the diference between the E. coli virus and your favourite pet a question of complexity and scale.

While digital information exists in the binary code of 0s and 1s, DNA is instead arranged in vast sequences of four types of nucleobase, abbreviated $\mathrm { C } , \mathrm { G } , \mathrm { A }$ and T. While over recent decades we have come to understand this biological data in ever-greater detail, we now stand on the brink of something even more remarkable: being able to easily change it.

(Genetic) Information Wants to Be Free

In 1953 Francis Crick and James Watson identified the molecular structure of DNA, ‘the basic copying mechanism by which life comes from life ’ as Crick would later write to his son. The following year, the first functional silicon transistor was built. From there the development of these two fields would become increasingly connected, as improvements in our capacity to understand the basis of life and genetic instructions came to depend on the progress of digital technologies.

This culminated in 2003 when the Human Genome Project completed mapping all 3.2 billion base pairs of the human genome. Formally launched in 1990 with a budget of \$3 billion, most of its progress was made in its final few years, enabled not only by improved techniques but massively improved computational power. Indeed, towards the end of the project it became increasingly clear that improvements in gene sequencing weren’t linear but, like Moore ’s Law in computing, exponential. What is more, 2003 turned out to be just the beginning. Despite being an information technology from the start, progress in genetic engineering over preceding decades had trailed developments elsewhere in computing. Yet the momentum gained over those final years of mapping the first human genome decisively changed that, taking the prospect of gene therapies from the realms of plausible speculation to reality.

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So while it took thirteen years and billions of dollars to sequence the first human genome, by 2007 the cost of performing the same process for a single individual had fallen to around \$1 million, a far steeper fall in the price curve than any other information technology As with the rice on the chessboard, the further progress went the more incredible its improvements became. This meant that by January 2015 sequencing an individual’s genome had fallen to \$1000 and two years later the biotech company Illumina unveiled a machine it expected to do the job for under \$100. Equally impressive as the improvements in price performance are how quickly the process takes: while it took thirteen years to map the first human genome, Illumina’s machine performs the same task in under an hour.

If all of this sounds dizzying, that’s because it should – since the turn of the millennium the falling cost of gene sequencing is even more astonishing than the exponential improvements of Moore ’s Law. While the performance of a computer chip per dollar is doubling every twenty-four months, the costs of sequencing a genome have fallen by a factor of between five and ten times a year. Even if that precipitous fall in price– performance slows down – perhaps aligning with trends elsewhere in computing for a further decade – sequencing a genome could cost as little as \$30 by the late 2020s. That alone would transform healthcare, although according to Raymond McCauley, who previously worked at Illumina, such a conclusion is unduly pessimistic. His view is that by 2022 sequencing a genome will cost as little as flushing a toilet. In other words, it’ll be too cheap to even think about.

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Illustrative of just how quickly the field is changing is the Earth BioGenome Project. First proposed in February 2017, it is explicitly modelled on the earlier Human Genome Project. But while the achievements of its predecessor were historic, any equivalence downplays the sheer scale of the latter’s ambition. Rather than map the genome of a human individual, the Earth BioGenome Project intends to sequence every life-form on Earth, from single-celled organisms to plants and complex mammals. While such an endeavour won’t come cheap, at several billion dollars it will cost far less than mapping that first human at the turn of the millennium.

But what benefits would having your genome regularly sequenced actually bring? How would it help provide healthcare and meet the challenges posed by age-related conditions? Initially it would allow for the earliest possible detection of conditions such as cancer before outward symptoms were even discernible, moving the disposition of medicine from reactive to predictive. Here stroke, cancer and even the common cold would no longer come without warning but could be foreseen and dealt with in ways previously unimaginable. This predictive practice would, most likely, begin the moment you were born.

For millennia humans have had a panoply of birth rites accompanying the arrival of a new child. Within the Islamic faith the call to prayer, or adhan, are the first words a baby should hear, while in Judaism a male infant should be circumcised eight days after birth in a brit milah ceremony. Across our planet new life is accompanied by ancient ritual. In the not-too-distant future, however, the first thing a newborn will be subject to – alongside various cultural customs – will be having their entire genome sequenced. Indeed, it is already common in a number of countries for a pinprick of blood to be taken at birth to test for conditions such as phenylketonuria (PKU) and cystic fibrosis.

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Expanding this to the entire genome, however, and then subjecting it to analysis by an AI would allow for the immediate isolation of risks specific to infant mortality, bringing this to fall even further. Relevant to the longer term it would create a detailed health profile – from allergies to risk of coronary heart disease and cancer in later life – as well as advising precision testing or treatments for conditions like asthma or short-sightedness. If that sounds like something for the distant future, it shouldn’t – the US National Institute of Health is currently spending \$25 million over five years trialling precisely such a treatment. And that’s before the price drops to less than a bar of chocolate.

Remarkably this would be just the start for preventative medicine. It turns out that just as unborn children release their DNA in the bloodstream of expecting mothers, so do cancerous tumours. That means that tissue biopsies, used to investigate suspicious lumps, would be replaced with liquid ones where DNA in blood would be used to detect, track and treat cancer. As with biopsies the same process could replace mammograms and colonoscopies, not just because of convenience and cost – but also efectiveness.

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\* In some cases, these diseases can be treated: any disability caused by PKU can be avoided by feeding the child a specific diet that prevents the build-up of phenylalanine (an amino acid) in the blood.

Besides significantly reducing cancer-related deaths, this process would be relatively inexpensive and easily rolled out across poor and wealthy countries alike. Meaning that just like the mobile phone, low-GDP countries would quickly enjoy healthcare services impossible in the most advanced nations just a few decades earlier. At present our vision of first-class healthcare is giant, expensive technology which can take up a whole room – not unlike the computers of the 1960s and 1970s. But from sequencing the genome of newborns to preventative treatment for cancer, handheld genome sequencers will allow for diagnostics that replace rooms’ worth of equipment. As with communications and energy infrastructures, the growth of cutting-edge healthcare in the Global South will look very diferent to existing infrastructure in places like Europe and the United States. Once more the technologies of the Third Disruption will efectively allow some of the world’s poorest countries to ‘leapfrog’ conventional parameters for development, meaning decades from now relatively poorer countries could have rates of cancer detection more impressive than the wealthiest societies of today. Whether they do, of course, depends on the politics of how the technology is distributed.

If handheld gene sequencers sound outlandish – reminiscent, perhaps, of the ‘tricorder’ in Star Trek – then don’t worry, because they already exist. The \$1,000 MinION sequencer, which fits in the palm of your hand and weighs just ninety grams, can sequence the genome of organisms such as the Ebola virus multiple times and at high speed.^\* While the technology can’t yet deal with the complexity of an organism such as a human, given prodigious improvements in price performance it is only a question of when such an innovation will appear.

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It’s worth pointing out that the genome of E. coli wasn’t sequenced until 1997, which represented the cutting edge of biotechnology at the time.

But while gene sequencing will change the provision of healthcare – creating preventative medicine that permits us to respond to illness before we even exhibit symptoms – the biggest breakthrough in biotechnology will be gene therapies. In terms of the leading causes of death, whose primary risk factor is age, this will create abundance in healthcare which even exceeds the exponential challenges posed by societal ageing.

Extreme Supply in Healthcare: Gene Therapies

Genetic engineering is nothing new. Indeed, we have knowingly altered the genome of various species for 12,000 years through selective breeding – a central innovation of the First Disruption. That gave us creatures fit for labour and crops like wheat which were hardy, easy to grow and nutritious. While we gained mastery in these fields before we had cities, writing or mathematics it wasn’t until the nineteenth century, through the work of Gregor Mendel, that we understood precisely how such mechanisms function.

After Mendel, however, understanding genetic inheritance increasingly resembled a science rather than an art. By the middle of the twentieth century our knowledge of the field was so impressive that humans grasped how they might be able to accelerate a process seen throughout nature – evolution – inside a laboratory. While DNA was understood to be responsible for heredity from 1952, and Crick and Watson’s double helix model was formulated the following year, the first genetically-engineered animals weren’t produced until the early 1970s. That breakthrough was arguably as profound as the transistor, the integrated circuit and even Watt’s steam engine. Within just a few short decades theoretical science had become applied technology.

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While of widespread popular interest and the basis for innumerable Hollywood films, this historic leap had little immediate impact in the provision of healthcare. The techniques required were prohibitively expensive and complex, meaning that for more than a generation advances in the field remained slow. But like anything subject to exponential development, what seemed like inertia soon gave way to a deluge of change.

Gene editing is a type of genetic engineering in which DNA is inserted, deleted or replaced in the genome of an organism. This is achieved by using restriction enzymes, or ‘molecular scissors’, of which – until recently – there had been three kinds: meganucleases, zinc finger nucleases (ZFNs) and transcription activator-like efector-based nucleases (TALEN). While there is significant variation in the price of each process, ZFNs and TALEN were developed more recently, all three remained out of reach for all but the wealthiest of institutions. Much like computers until the early 1970s, gene editing was the exclusive preserve of elite researchers and subject to massive overheads. As a result experimentation and trials were rare, expensive and slow.

That has changed in recent years, however, with the arrival of CRISPR-Cas9. CRISPR is a new approach which reduces the costs of gene editing by 99 per cent while cutting experiment times from months to weeks. While it is yet to be fully perfected and is not always suficiently precise, CRISPR is a programmable and easy-to-use technique for almost any lab, allowing scientists to edit genetic information with unprecedented eficiency. Just like SpaceX and rocket technology, CRISPR-Cas9 doesn’t permit humans to do anything particularly new. Rather, it illustrates how information wanting to be free disrupts mainstream views about scarcity and makes extreme supply possible. How we deal with biology, primarily our own, is set to be transformed just as radically as labour with automation, energy with renewables and resources with of-world mineral extraction.

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