‘Start with user needs’ has been the mantra of digital government since the early heady days of GDS. It’s a thought which is simple, powerful and – this post argues – wrong. Or, more accurately, unhelpful: it’s a concept which both lacks precision in its own right and risks being too tightly coupled to the construction of solutions.
This is not some random hit job, but a deeply reflective post which brings out clearly where user research most adds value, by being still clearer about where it doesn’t. In doing so it draws out a point which is relevant and important to a much wider audience. It positions user research as a means of reducing risk – and that is important not just as a way of helping senior decision makers see the value in it, but because basing decisions on unexamined and untested assumptions leads to bad consequences (and has been doing since long before government was digital).
Alan Mitchell – Mydex
Debates about personal data have a tendency to be more circular than they are productive. There is – it appears – a tension between individual privacy and control and the power unlocked by mass data collection and analysis. But because the current balance (or imbalance) between the two is largely an emergent property of the system, there is no reason to think that things have to be the way they are just because that is the way they are.
Given, though, that we are where we are, there are two basic approaches to doing something about it. One is essentially to accept the current system but to put controls of various kinds over it to ameliorate the most negative features – GDPR is the most prominent recent example, which also illustrates that different political systems will put the balance point in very different places. The other approach is to look more fundamentally at the underlying model and ask what different pattern of benefits might come from a more radically different approach. That’s what this post does, systematically coming up with what will look to many like a more attractive set of answers.
Mydex has been building practical systems based on these principles for a good while, so the post is based on solid experience. But therein lies the problem. Getting off the current path onto a different one is in part a technical and architectural one, but it is even more a social, political and economic one. As ever, the hard bit is not describing a better future, but working out how to get there from here.
Adrian Brown – Centre for Public Impact
Everybody is in favour of evidence-based policy – by definition it must be far superior to the policy-based evidence with which it is often contrasted. This post is a brave challenge to the assertion that there is an evidence base for evidence-based policy. In particular, it argues first that weak evidence can be unwittingly assembled to appear misleadingly strong and in doing so close down policy options which should at the very least be kept open; and secondly that experimentation is a better approach, precisely because it avoids forcing complex issues into simple binary choices.
That’s not an argument that evidence is unimportant, of course. But it’s a good reminder that evidence should be scrutinised and that simple conclusions can often be simplistic.
This is the recording of an event at the Institute for Government this week, in which Jamie Susskind starts by briefly introducing the arguments of his book, Future Politics, and then discusses them with Gavin Freeguard – and as the book weighs in at over 500 pages, this might be a gentler way in. Susskind approaches the question of the title from the perspective of politics and law, coming back to the question, how much democracy is the right amount? That’s a harder – and more important – question than it first appears. Answers to it have been evolving for several thousand years, but digital technology gives it a new urgency, for reasons which range from the manipulative power of social media, the elimination of leeway, to bot-driven perpetual voting.
In the last century the fundamental question was, what should be done by the state and what should be left to the market and to civil society? … In our time, the key question will be this, to what extent should our lives be governed by powerful digital systems, and on what terms?
Dan Hill – But what was the question?
This is quite a demanding essay. It demands some time to read, at about 6,000 words, and it demands more time to reflect, not least because it is subtly challenging. How do we design our interaction with our urban environment in a world of new technologies? How do we balance optimisation for individuals against optimisation of wider systems? How, more broadly, do we ensure that social objectives drive the adoption and deployment of technology rather than being driven by them? Or to step back from the detail (and in some ways from the specific subject), there’s a pretty strong consensus on what user centred design means for individuals; much less so on what it might mean for groups of people whose lives and activities intersect and affect one another.
There are clear examples of what new approaches to design might look like and of how they have been applied. But there isn’t much here about the social and political approaches which create the space for those design approaches to flourish. It’s unfair to criticise this essay for not doing something which it makes no claim to do, but the concept of ‘strategic design’ it introduces perhaps has a further level still.
Alexis Madrigal – The Atlantic
It should by now be beyond obvious that technology is never just about the technology, but somehow the hype is always with us. This article is a useful counter, listing and briefly explaining seven reasons why autonomous vehicles may not happen and may not be an altogether good thing if they do.
It’s worth reading not only – perhaps even not mainly – for its specific insights as for its method: thinking about the sociology and economics of technology may give more useful insights than thinking just about the technology itself.
Catherine Howe – Curious?
This short post is more of an aside than a developed argument, but from this source it’s not surprising that even an aside contains a couple of memorable and provocative thoughts.
The first is an expansion of the title, which nicely echoes Emily Tulloh’s recent post:
Strategy is a tricky business. Too much and you end up endlessly thinking and not doing. Too little and you end up just reacting.
The second part of the post turns to the temptations and risks of being a leader in a hierachy:
It’s very seductive to be in a leadership position as the whole system is biased towards enabling you to be right
Been Kim – Quanta Magazine
The problem of the AI black box has been around for as long as AI itself: if we can’t trace how a decision has been made, how can we be confident that it has been made fairly and appropriately? There are arguments – for example by Ed Felten – that the apparent problem is not real, that such decisions are intrinsically no more or less explicable than decisions reached any other way. But that doesn’t seem to be an altogether satisfactory approach in a world where AI can mirror and even amplify the biases endemic in the data they draw on.
This interview describes a very different approach to the problem: building a tool which retrofits interpretability to a model which may not have been designed to be fully transparent. At one level this looks really promising: ‘is factor x significant in determining the output of the model?’ is a useful question to be able to answer. But of course real world problems throw up more complicated questions than that, and there must be a risk of infinite recursion: our model of how the first model reaches a conclusion itself becomes so complicated that we need a model to explain its conclusions…
But whether or not that is a real risk, there are some useful insights here into identifying materiality is assessing a model’s accuracy and utility.
David Birch – Wired
David Birch is one of a pretty small group of people who write sense about money and identity – and he is pretty much unique in doing so with wit and lightness of touch. This short article draws out the connection between identity and attribution. We will increasingly need to know and trust the attributes of robots and systems, we will increasingly be interested in what attributes people assert about themselves – and at the intersection of those needs there will be a particularly precious attribute:
In time, IS_A_PERSON will be the most valuable credential of all.
Emily Tulloh – Futuregov
This is a post about what’s involved in doing service design and, taken at face value, it’s a pretty good one. But it also works as an extended metaphor for other kinds of change development, and for strategy in particular. Figuring it out and making it real are presented here as the fundamental stages of service design – but pretty much everything said about them works in terms of strategy too.
One version of that parallel is drawn within the post itself, with figuring it out equated to strategy and making it real equated to delivery. But it also works – and arguably works better – to see strategy as the parallel to the whole service design process: a strategy which does not take account of its own approach to delivery is one with a pretty important gap.1216ethn
Successful strategy involves both the destination and the journey, and because of that (though not only that) successful strategy is inextricably linked with successful leadership. This text of a recent speech is not only a powerful account of one person’s development as a leader, but is also a manifesto for a kind of leadership which is very different from the norm of the civil service (which is the context for both Clare and her audience). Clare talks about conformity and rebellion – and about ‘tempered radicals’ who tread a fine line between the two. That’s a place occupied by strategists too: being as constructively disruptive as is humanly possible up to and beyond – but not too far beyond – the capacity of their organisation to manage change effectively.
Bas Leurs and Kelly Duggan – Nesta
Testing, piloting, prototyping and a few more words besides all mean something similar, but all mean something different – though whether we would all agree on quite what the differences are is another matter.
This post sets out to distinguish and to map the scope of four approaches and to argue for greater rigour in their usage. The distinction is definitely useful and the rigour is definitely desirable, though the quest for absolute rigour of specialist language in general usage tends to end in disappointment. But that’s not a reason not to be as clear as possible, and it’s certainly not a reason for practitioners to be anything other than precise both in their understanding of what they are doing and in how that understanding is shared.
Audree Fletcher – Medium
This is a short, elegant, epistolary post on how design and policy come together – or rather about how they might do so better. There often is a gap between policy thinking and design thinking, though one that’s more an accident of history and career paths than of underlying incompatibility. But the contrast sketched here perhaps over-emphasises aspects of the difference: many politicians are interested in more evidence-based and iterative policy development, the trick (as the post recognises) is doing that in a way which creates a space for things not to work without being labelled as failures. And that should be one of the ways in which more traditional policy making skills complement design-based approaches.
Of course it doesn’t always work in that relatively benign way, far from it. But there are great insights here into how it might work better more often.
Steph Gray – Postbureaucrat
A couple of weeks ago, Steph announced his return to front line blogging. That seemed promising; this post shows the promise too be real. Even wheels need to be improved and even wheelwrights need to get better at what they do (or, of course, to be supplanted by jetpackwrights). Doing that in a monoculture may be efficient in the short term, but there’s a price to be paid, and the price can turn out to be high. That is emphatically not let a thousand flowers bloom, and let the devil take the hindmost – the points in the post about how to shape and manage diverse approaches are as important as the recognition that there is value in the diversity. The goal is “inefficient short-term competition in pursuit of long-term optimisation” and there is plenty of good advice here about how to achieve both.
Kit Collingwood and Robin Linacre – Data in government
There is lots being written – a small subset of it captured on Strategic Reading – about data and its implications as a driver of new ways of doing things and new things which can be done. There’s a lot written about the strategic (and ethical and legal…) issues and of course there is a vast technical literature. What there seems to be less of is more practical approaches to making data useful and used. That’s a gap which this post starts to fill. it’s not only full of good sense in its own right, it’s also a pointer to an approach which it would be good to see more of: given a strategic opportunity or goal, what are the practical things which need to be done to enhance the probability of success? Strategising is the easy bit of strategy; getting things done to move towards the goal is a great deal harder.
Ben Proctor – The Satori Lab
This is an apparently mundane post about basic tools needed to support effective team working, regardless of location. At first sight, that’s not strategic at all. Actually though, it’s highly strategic, in both a direct and a metaphorical sense.
Doing a thing well requires the right tools and infrastructure for the job. It’s not good enough to have lofty ambitions for remote collaboration without being willing put in place the foundations that will allow it to succeed. That’s both a specific lesson and a more general metaphor for organisational change: you can’t get away with wishing for the end without committing to the means, and putting the means in place is serious work, without which strategic aspirations go nowhere.
Simon Willis – Medium
Most people blog by collecting nuggets of experience and sharing them in short posts over time. After a while, the posts accumulate into a big enough corpus that you get some sense of an overall picture and approach. This essay takes a very different approach, distilling 25 years experience into 4000 words of powerful argument. In twenty crisply argued propositions, the insight which comes from having created and led innovation teams shines through – as does the level of challenge to host organisations whose systems and instincts will invariably be configured to undermine and enfeeble such teams.
Anybody with any aspiration to innovate in a large organisation will find much to recognise here. And pretty much anybody with such aspirations will find much to reflect on and learn from. Running through the whole piece is the idea that innovation is fundamentally about people and how they behave with each other, culminating in the two final points:
Treat all people with respect.
Understand that great innovations are rooted in relationships and that all real relationships are non-transactional relationships.
Nick Barrowman – New Atlantis
There is increasing – if belated – recognition that analysis and inference built on on data is vulnerable to bias of many different kinds and levels of significance. But there is a lingering unspoken hope that data itself is somehow still pure: a fact is, after all, a fact. Except that of course it isn’t, and as this post neatly argues, while raw data may sound less underhand than cooked data, its apparent virtue can be illusory:
In the ordinary use of the term “raw data,” “raw” signifies that no processing was performed following data collection, but the term obscures the various forms of processing that necessarily occur before data collection.
Benedict Dellot – RSA
There is no shortage of material on the future of work in general, or on its displacement by automation in particular, but much of it has a strong skew to the technocratically simplistic (though posts chosen for sharing here are selected in part with the aim of avoiding that trap).
There has been a steady stream of material from the RSA which takes a more subtle approach, of which this is the latest. It takes the form of a set of short essays from a variety of perspectives, the foreword to which is also the accompanying blog post. The questions they address arise from automation, but go far beyond the first order effects. What are the implications of the emergence of a global market for online casual labour? Does automation drive exploitation or provide the foundations for a leisured society? Given that automation will continue to destroy jobs (as it always has), will they get replaced in new areas of activity (as they always have – so far)?
Buried in the first essay is an arresting description of why imminent exponential change is hard to spot, even if things have been changing exponentially:
because each step in an exponential process is equal to the sum of all the previous steps, it always looks like you are the beginning, no matter how long it has been going on.
And that in many ways is the encapsulation of the uncertainty around this whole set of questions. There is a technological rate of change, driven by Moore’s law and its descendants, and there is a socio-economic rate of change, influenced by but distinct from the technological rate of change. It is in their respective rates and the relationship between them that much controversy lies.
Politicians are unusual people. One of the ways in which they are unusual is that they have a tendency to be very strongly tribal. Another is that that makes it easy for them to think that that is normal. Politicians of one tribe in some ways find it easier to understand (and in some ways respect) politicians of a competing tribe than they do people whose instincts are less tribal.
This post (originally a series of tweets) is a reflection by somebody once of one of the tribes who now sees political tribalism as a big problem. There’s food for thought here both for members of the tribes and for those who seek to understand and work with them. That latter category includes, of course, non-political public servants who work with politicians and in political systems. They (we) are the very opposite of tribal (in this category of tribes – there are of course many others). At its best, that’s a powerful symbiosis, at its worst it’s a recipe for deep confusion and mutual misunderstanding.