On Healthware

There’s a hypothetical scenario I’ve been pondering for a while. I’ve actually been trying to write a short story about it, framing it from different perspectives. But that’s taking too long, and reality is fast catching up.

In the scenario, the British government has decided that the only way of making universal free health care affordable is by compelling citizens to have data on their bodily health and lifestyle tracked, with behavioural changes recommended to individuals by artificially intelligent “healthware” to keep them from from falling ill. The healthware learns how best to persuade people to act differently, fitting itself to individuals’ personalities to ensure maximum compliance. If people are consistently non-compliant, they have their access to free healthcare revoked.

Naturally, hospital visits are still required for genetic and particularly complex conditions, and in the wake of accidents or unexpected emergencies. But there are no more queues in GP surgeries or A&E. The number of people on medication drops to levels not seen for decades. The physical and mental health of the population soars, with higher productivity, longer life expectancy, and wellbeing to match (or better) the Scandinavians.

On the one hand, this sounds wonderful. On the other, it would herald the arrival of the sort of big state that socialist governments of the past could hardly dream of (their dreams looked more like this). The level of social control that would become possible – with our every behaviour monitored and, ultimately, made to fit a “healthy” norm – is intensely disquieting. Even more perturbing is the fact that, at least to me, this doesn’t seem particularly far-fetched.

In reality, healthware this sophisticated would come from a big tech firm before any government had even properly thought about it. I’ve posted a piece on Medium that comes at the possibility more from this angle. But I also wanted to take a few minutes to expand on why I think such a scenario is feasible, and offer a list of related things to read.

Technical feasibility

I’ve actually written before about the difficulties of applying a data-driven approach to a biological system as endlessly curious as the human body. That, though, was in the context of elite performance, and keeping someone within the bounds of reasonably good health ought to be more straightforward than turning them into an Olympian.

Naturally, it could take years for a system to be successfully trained with the sort of capacity outlined here. This is particularly the case given that the learning process would likely require real-time participants, and accordingly move only as fast as the rate at which people live and fall ill. Historical health records, along with some expert knowledge, could be used to speed up the process, but both may prove to be sub-optimal and useful only as a starting point. The concurrent analysis of the data of many, many individuals, and the pooling of the resulting knowledge (as has happened for the training of autonomous vehicles) will likely prove crucial – the more participants the better.

Eventually, a system should be sufficiently accurate for commercial roll-out. And over time it would just get better: optimising to take into account the individual quirks of your body, and benefitting from the more general findings from everyone else’s systems (perhaps attributing greater weight to data from family members and those physiologically similar to you). It could also keep abreast of the latest medical research findings (as IBM’s Watson does) in a way that would be impossible for a human, incorporating these into its predictions and recommendations to boost performance even further.

The bigger problem will be that there is currently far too much missing data on almost everyone to accurately predict health outcomes. Making wearable technology as ubiquitous as phones, and developing more ways of collecting health and lifestyle data automatically so you don’t need to rely on useless humans to input it manually, will be key (Apple is attempting to do both).

Motivation

From the perspective of business, developing healthware at this level of sophistication could make some of the most powerful companies in the world even more money. If Apple could even get close to it, the Apple Watch would become a must-have – which seems ample motivation for pushing on with it as smartphone sales stagnate. Health insurers would happily make use of all that data to aid their own predictive models, and big pharma’s displeasure at a possible decline in medication levels could be offset by having healthware recommend, and automatically deliver their drugs.

Government would also likely be supportive given the scope for relieving strain on health services. It might be that government – or health providers more generally – come to endorse, or even require the use of this sort of technology (hence the scenario painted above). Besides, the British government seems supportive of pretty much any new way to better track people and invade their privacy, so there should be no problem on that front.

Another force that might drive the development of this sort of technology is the longevity hype that’s apparently consuming Silicon Valley. You could almost imagine this sort of healthware being pursued as a vanity project by one of any number of tech-entrepreneurs-turned-billionaires looking for a data-driven approach to living forever, regardless of whether or not it would end up being profitable.

The patient-consumer

What about, well, normal people? As a starting point, a 2016 survey of American healthcare “consumers” found that a quarter own wearable tech, 88% have used some sort of “digital health tool”, and 77% are willing to share their health data with their doctor to improve care – with 60% happy to give that data to Google.

The number of people buying wearables will continue to grow (likely driven more by marketing campaigns and the waning allure of near-identical mobile phones than anything else), as will the adoption of digital health tools as they become ever more useful. The figures on willingness to share health data may not sound especially high, but they’re ample for an initial phase of developing sophisticated predictive healthware – and if any system proved to be effective, they’d likely go up.

Americans are, admittedly, much further down this road than the rest of the world. But given that so many of our recent technological trends (e.g. personal computers, smartphones) have come from the US, and have been driven by American companies, it wouldn’t be an enormous surprise if the rest of the “developed” world soon caught up.

OK, enough. A few things to read / listen to that haven’t been linked to in either this or the Medium piece:

2017 Internet Trends Report – Kleiner Perkins (Mary Meeker)   >   See slides 288-319 for a range of pointers as to where healthcare might be going. (The rest is interesting, too.)

Self-regulation in Sensor Society – Natasha Schüll   >   Cool talk, available as a podcast from Data & Society, on the softer, fuzzier form of tracking represented by wearable tech (“little mother”, as opposed to the “big brother” of CCTV etc.) and its implications for individual autonomy and selfhood.

Some decent long-ish reads from a range of publications: this from the FT (paywalled), which is from a while ago and probably the first thing I remember reading on the subject, focusing mainly on Babylon; this from the Atlantic, which is even older (2013!) and concentrates on IBM’s Watson (which is still going strong in the healthcare game); and this from Newsweek International last Friday, which has more of an American bent but covers a load of interesting startups I haven’t really discussed here.

Networks of Control – Wolfie Christl and Sarah Spiekermann   >   A longer, broader work focusing on the collection and use of personal data by businesses working in a range of areas. Considers whether this corporate surveillance can enable businesses to control consumer behaviour – which is relevant here.

Intervention Symposium: “Algorithmic Governance” – org. Jeremy Crampton and Andrea Miller   >   A bit academic, but some interesting thoughts here and in the collected essays giving some background to the notion of algorithmic control and its implications.

As usual, I’m always keen for cool new stuff to read, so hmu if anything jumps to mind!

The world’s problems are political

‘If people today still die from starvation, it’s only for political reasons.’ – Yuval Noah Harari.

I had a revelation yesterday. I was running along the South Downs Way, looking out across the English countryside and thinking about how to make the world a better place. This is pretty standard for me (lol), and since starting a Masters in artificial intelligence (AI) last September I’ve been particularly concerned with how far AI can help, rather than hinder (or just make money for businesses). But yesterday I decided that when it comes to solving some of the world’s most intractable problems, AI is small fry.

The roots of human suffering are not technological, but political. This is a situation that is, I think, peculiar to the 21st Century. In a recent Exponential View podcast, Yuval Harari argued that over the last few decades we have acquired the technological means to limit the three problems that have most affected society for all of human history – famine, plague, and war. No longer are these seen as unavoidable forces of nature, but as catastrophes that need never happen. The issue is that despite this progress, they still do.

Millions are starving in Yemen, South Sudan, northeast Nigeria and Somalia not because of some technological failing or lack of innovation – enough calories of food are being produced worldwide to feed everyone (see p.4 of this from 2008(!)) – but because of politics. There may be scope for the effective use of, say, drones in humanitarian action, but the fact that humanitarian action is needed in the first place is a question of political inaction and incapacity – primarily with regard to conflict in the Yemeni, South Sudanese and Nigerian cases, and climate change (and its consequences) in Somalia.

With the main technological hurdles overcome, there must exist some ordering of society, some allocation of the resources at our global disposal, such that suffering is minimised, and human potential and wellbeing maximised. In identifying what that ordering might be, AI could help. Running complex simulations of possible futures that incorporate global supply chains, resource consumption requirements, alternative forms of political organisation, and so on, could perhaps point the way.

But politics would always rear its head. The enactment in reality of any apparently ‘fair’ simulation would involve some powerful people losing a lot of money and influence. Those powerful actors would resist change, or at least seek to minimise the extent to which it affects them, just as weaker actors might look to elevate themselves excessively at the expense of the formerly strong (this goes for countries, companies and other organisations as much as for individuals). Even if a ‘just’ ordering of human civilisation was identified, the question would remain of how to make the transition.

A recent Dominic Cummings blog on effective systems management (applied particularly to Whitehall, so relevant in this context) reminded me of that famous James Madison quote from the 51st and most-cited of The Federalist Papers. “If men were angels,” Madison wrote, “no government would be necessary”. Identifying solutions to the world’s problems is one thing, but making people sufficiently angelic to implement those solutions is an entirely different beast. And that beast – a beast that we have yet to fully fathom – is politics.

Automation etc.

I mentioned in my 2016 reading round-up that I hadn’t yet had a crack at Martin Ford’s The Rise of the Robots. I finally put that right the other week, and the book prompted many, many thoughts. Which is always a good thing.

Quite a few of those thoughts were objections. I generally agree with Ford that the technological progress we’re seeing today far surpasses anything that has come before, and the mass automation of labour is a feasible possibility as a result. But I don’t see it as inevitable. For one thing, a backlash against automation could see it rolled back, rather than accelerated, before too long. I wrote a short piece explaining the thinking behind that, which you can read here.

That piece was, necessarily, a massive over-simplification of the lie of the land. You can’t really cover social change on this scale in 750 words. My purpose with it was more to suggest an alternative way of thinking about how things might pan out, rather than predicting what will happen.

One of the most interesting dynamics that I failed to cover was how all of this fits into the global / international economy. Some of the best bits of Ford’s book, I thought, were actually about offshoring, and how it could seriously shake up the world of work (if it isn’t doing so already) before automation does. We think about manufacturing going abroad, but one of the things that technology really has changed is the ability to do non-manual work remotely, arguably making the pool of potential applicants for, say, a software engineering role, global. Why limit yourself to UK graduates when you could take your pick of the best minds in Asia, or Africa, or anywhere else?

The question of how different governments shape their policies in light of and in competition with those of other governments will also be fascinating. If you’re elected on a platform of rolling back automation (as I suggest might soon happen in the piece), and you force companies to hire human workers over computers while other countries are actively promoting automation, those companies will either move elsewhere or risk becoming uncompetitive in a global market. If they move elsewhere, you end up with the same unemployment problem you would have had anyway. If they stay, domestic consumers will probably look abroad for products and services provided more cheaply and efficiently – so you’ll have maintained that vital consumer purchasing power only to reap no rewards. Unless you close yourself off from the world of international trade, or implement very stringent tariffs and what have you – but then you risk your country becoming irrelevant on the world stage (the Trump presidency should make a very interesting case study…). At which point, UBI might seem like it was the better idea after all. Although then what would you have done about all the mental health problems and social issues arising in a population of bored, unhappy, confused and unfulfilled humans?

In short, it’s complicated. My piece, and these ramblings, don’t even scratch the surface.

The other complicating factor will be the environment. Ford mentions climate change at the start and end of the book as something that could further exacerbate the problems of mass automation. What he doesn’t do, however, is consider the ways in which climate change might actually impose a natural limit on automation. Where is the energy to run all these robots going to come from? But this is something I really want to write about separately. So I’ll leave it there for now.

Any thoughts / comments / objections, fire away. If you’re interested (and if you’ve got this far?), I thought I’d include a very brief reading list with some interesting stuff that might be worth referring to.

 

The Rise of the Robots – Martin Ford   >   Obviously. It’s actually a pretty easy and entertaining read, albeit slightly repetitive at times.

The Future of Employment: How susceptible are jobs to computerisation? – Carl B Frey & Michael Osborne   >   This now-ubiquitous report from 2013, which estimated that 47% of US jobs are susceptible to ‘computerisation’, underpins Ford’s argument. The Oxford Martin School have a load of other interesting publications on technology and unemployment which are also worth checking out.

World Development Report 2016: Digital Dividends – The World Bank   >   In some ways, this could be seen as a follow-up to the above, but it takes a broader approach to the impact of technology and a much more international perspective. Very interesting on the topic of employment, though, particularly with regard to the susceptibility of jobs in the developing world to automation (see p.23 for a quick graphical overview).

New Robot Strategy  The Headquarters for Japan’s Economic Revitalization   >   A detailed plan of action for the integration of robots into multiple levels of Japanese society. Very interesting.

The Second Machine Age – Erik Brynjolfsson & Andrew McAfee   >   I wasn’t overwhelmed when I read this last year, but have been dipping back into it over the past week and actually think it’s very thoughtful in terms of its policy / long-term recommendations. Worth a look.

Please let me know if you’ve read anything good!