Tangentially related to industrial policy, which we will be discussing next 
week on The Mediating Trump podcast.
http://evonomics.com/building-public-goods-21st-century/

Building the Public Goods of the Twenty-First Century
Digital public goods in the age of the data revolution

By Nicholas Gruen

History plays tricks on us. Just as we think we’ve got things figured, 
everything changes. My favourite example is Malthus’s ‘principle of population’ 
which explained why most people were mired in poverty despite improving 
technology. As Malthus explained, population growth was exponential and so 
would eventually outstrip productivity growth and return the bulk of the 
population back where it started – at bare subsistence. A theory with 
considerable explanatory power over the whole of human history! And published 
in 1798 just as it became obsolete. The next century saw the takeoff in living 
standards lifting global living standards around twenty times since then!

Something similar happened with economic reform and its guiding idea that 
private goods – cars, cookies, holidays, houses – were the heart of our 
material living standards and that they were best produced by competitive 
markets. Under the sway of these ideas we swept away all manner of silly 
regulation – controlling everything from airline scheduling to shopping hours. 
But where market failures continued – for instance in transport, communications 
and energy, we look more like slaves to fashion – creating markets or the 
appearance of markets where there were none. But we’ve come to rue much of our 
handiwork.

Meanwhile there was a Big New Development. The Internet and digital technology 
came of age. And here’s the thing. Digital artefacts – whether they’re an 
algorithm, a website, an app or a coding language – are always and everywhere 
potential public goods. Once produced digital artefacts are essentially 
costless to replicate which raises the question of whether they can or should 
be made freely available to all.

In fact since the Internet matured one entrepreneur after another has actually 
chosen to give their service away, even though it could have been provided 
behind a paywall. We’re now in a world of burgeoning public goods privately 
provided – from platforms whether they’re for profit like Google, Facebook, 
Twitter, or not like Wikipedia to open source applications like Linux, Firefox 
and the Android Operating system. There’s a paradox here because, by the 
standard assumptions economists make, governments should have built these 
assets – because the economic value they generate ranges far beyond the revenue 
– if any – they bring to their creators. But governments wouldn’t have had the 
skills to have produced these things, nor the permission to experiment and fail 
in order to seed the vast success stories that we see before us.

However, by definition, the public goods of the 21st century that have so far 
been built privately are the low hanging fruit – those projects where the cost 
of production is so low compared with the total economic benefit created that 
they can be funded from small slivers of the value they create, whether that’s 
from advertising, philanthropy or from the benefit some patch of software does 
for its author before they donate their code back to the project. There are 
plenty more digital public goods where they came from, but they’re harder to 
build for two reasons. Firstly many digital public goods are cognate with 
standards. Where someone comes along and establishes a ‘killer platform’ that 
lots of people want to be part of – like Google, Facebook or Wikipedia – they 
get to define the standard. But in lots of situations there are numerous 
incumbent digital platforms and products and there would be great public 
benefit for them to be interoperable. But, as we’re coming to see, bringing 
that interoperability about – creating that digital public good is much more 
easily said than done. Secondly some digital public goods may cost more than 
the private gains they bring to any one party. I’ll provide examples of each 
case below.

Meanwhile, the great digital innovators are champing at the bit to gain 
commercial advantage in getting to the future first – by building it. Enter 
Google’s artificial intelligence subsidiary DeepMind which is delivering a 
clinical alert app for kidney injury to the Royal Free London NHS Foundation 
Trust. Yet, as recently outlined in a learned journal article, things look 
decidedly dodgy. In circumstances that are still poorly documented publicly, 
DeepMind was able to ingest vastly more patient data than was necessary to 
build the app – all of it without clear patient consent. As the article points 
out, the arrangement likely compromises the public interest. Yet though the 
authors are right that this is no way to develop healthcare technology in the 
21st century, it’s a much harder business to say how we should properly go 
about that task. And even if  satisfactory policy is necessary to success, so 
too is execution – which we’re learning is a lot harder again. So far we’re not 
very well advanced on either.

The article raises concerns about privacy and the domination of private over 
public considerations. On the first, if we’re serious about the actual risks to 
privacy, I expect they’re quite low. Google has a lot of interest in protecting 
its users’ privacy and a better record than the British Government. None of 
that excuses the Trust or Google in the cavalier way they’ve proceeded. However 
the alternatives the authors mention – which are tied up with obtaining greater 
consent – don’t seem all that helpful. One of the fundamental benefits that the 
data revolution unlocks is the capacity for endless interrogation and 
reconfiguration of data assets to generate new knowledge – putting the 
extraordinary possibility of personalised medicine within contemplation. And 
keeping transactions costs near zero is essential to seizing those 
possibilities. Seeking people’s consent for each and every use of their data 
simply erects barriers to new knowledge for no identifiable benefit. If that 
was what was required of Fiona Stanley when she used old data to identify 
patterns that enabled us to reduce the incidence of spina bifida in regional 
Australia she would have been stopped in her tracks – the knowledge latent in 
data we already had would never have been uncovered.

Instead we should provide users with reasonable protection against identifiable 
harms, preeminently violations of their privacy. Given people’s justifiable 
wariness about their data being used or mis-used for private gain, I expect we 
do need some legitimating consent from consumers. But if so, we should think 
about the architecture of that consent – the transactions costs involved for 
all parties in its being given, and its generality once given. We’ll foreclose 
myriad opportunities for human betterment if we hanker for line-item consent 
like some people yearn for the return of reusable milk-bottles.

In the meantime, the big story in the excitement about DeepMind and the NHS is 
the way in which the interests and technical capabilities of private operators 
are dominating public interests and capabilities. But calling that out, as the 
authors rightly do, is only the first step towards better outcomes. We need to 
articulate what those public interests are, and then understand how best to 
build a world that optimises them. And while the Googles of the world have been 
building their preferred world for over a decade and show no signs of slowing 
down, the representation of the public interest has been far more tentative – 
politically, but also intellectually.

The Productivity Commission is in the process of legitimating a stronger 
regulatory role for government, calling for broad based right for consumers to 
access data about them. As the Commission’s Chairman Peter Harris said 
recently, this is “something of a new departure for the commission” and I think 
it’s on the right track. As he puts it, it’s all part of trying to balance the 
rights of producers and consumers and align public and private interests. Yet 
this still implies an old model in which the public sector sets the rules and 
the world is then built by firms or other organisations competing with one 
another. As I wrote a few years ago in all those areas where market failure 
abounds – and that’s certainly the case in health – “output is better thought 
of as the joint product of competitive and collective (collaborative and 
regulatory) activity. Each sector requires the evolution of quite different 
institutions in which public and private, competitive and collaborative 
considerations concatenate at every level from high policy down to the 
life-world of workplaces”.

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If that’s the case, how much work is there to do to really seize the potential 
that lies before us in big data for health let alone all the other areas of the 
digital economy? Many moons ago we twigged that a widely used, universal 
e-health record would be a fundamental, infrastructural public good for the 
future. But we’ve been at it for over a decade, sinking about a thousand times 
as much money as Google took to get online and yet the results remain modest. 
As the PC report is showing, we need more than grand pronouncements and more 
than simple expenditure to bring these things into existence. We need the whole 
system to start coalescing around these new public goods. I’ve suggested a slew 
of digital public goods that might be built by governments taking the lead in 
configuring public private digital partnerships or in simply using their 
convening power to help standards evolve and encourage public reporting against 
them. Generally these ideas are low risk and would be net fiscal contributors 
over any reasonable time frame. Most people exposed to them find them 
compelling. They’re far from the last word on how to build the public goods of 
the 21st century. But somehow they never find their way into the policy in-tray.

And ultimately this is but one potential line of development. As the Internet 
of Things burgeons and generates more and more data about us – from our 
smartphones to our Fitbits, making that data accessible to consumers is the 
first stage towards being able to combine it with other data and recombine it 
to generate worthwhile insights to improve our convenience in living our lives, 
but also our health and the health of others. Health professionals are 
increasingly using free online services like HealthKit for managing their 
practices. One might imagine that much of the most useful available data would 
assemble itself onto some platform for the greater good driven by the 
self-interest of all the players. But given the transactions costs involved in 
negotiating and dividing up the benefits to the owners of the data, to say 
nothing of the technical challenges of interoperability or the complications of 
privacy concerns and the ‘anti-commons’ created by the legal obsolescence of 
our intellectual property regime in a digital world, the chances of this 
happening are vanishingly small.

The kinds of rights proposed by the PC will likely help, but there’s plenty 
more governments can do by using their considerable sway in sectors like health 
– as funders, regulators, insurers and as conveners – to:

delineate common goals;
protect people’s legitimate interests, for instance in privacy, with firm and 
effective but parsimonious regulation;
accelerate the evolution of common standards; and
encourage those they can influence to take up those standards.
Only then will we be able to endlessly combine and recombine our data to find 
the hitherto undetected patterns and connections that can unlock a better life 
for us all.

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