Data and AI

How much faith should we have in data?

An excellent talk by the chief executive of the Open Data Institute, reflecting on how to increase our safeguards against algorithmic bias in big data applications.

Jeni Tennison – ODI Fridays

Future of work

The future of jobs

A global study of future trends in jobs, based on survey evidence from senior HR people around the world. There is a fairly detailed microsite with supporting analysis of various kinds, as well as the main report itself.

World Economic Forum

Data and AI Future of work Innovation

JPMorgan Software Does in Seconds What Took Lawyers 360,000 Hours

A telling example of the kinds of work automation is now reaching: automated interpretation of complex legal documents removing the need for skilled human scrutiny. Also interesting on the focus on technology innovation – high levels of investment and explicit recognition that some initiatives will fail.

Hugh Son – Bloomberg

Data and AI Future of work

 Would life be better if robots did all the work?

Socratic dialogue on Radio 4, exploring the ethical issues around the automation of work. In a world where so much social, as well as economic, value comes from work, what happens if the humans aren’t needed any more? And would that be an improvement (and if so, for whom)?

Michael Sandel – The Public Philosopher

Organisational change Service design

Policy v5.127: Could government make services like Dyson makes vacuum cleaners?

A good summary of the people and methods bringing design thinking into government, with mini case studies of where it’s starting to make a difference. The provocative question in the title never quite gets answered, but there is a bit of a flavour that while there’s been a lot of progress in some areas, the vacuum cleaner of government itself hasn’t moved far beyond version 1.0.

John Lapping – Pieria

Data and AI Service design

In praise of cash

Does paying for things by card (and phone and watch and…) represent liberation from the need to carry coins around and enable faster, simpler transactions? Or is it a dangerous slide towards the privatisation of money and the advent of universal financial surveillance? And, most importantly it seems, can you get a coke from a machine when you want one?

Brett Scott – Aeon

Data and AI

Machine intelligence makes human morals more important

Zeynep Tufekci is a computer programmer turned sociologist, whose book Twitter and Tear Gas is coming out in a couple of months. This TED talk is the video parallel of Cathy O’Neil’s book, Weapons of Math Destruction. The core point is the same – that machines we don’t understand, trained on imperfect data, are as likely to be amplifying human biases as to be emobodying objectivity.

Zeynep Tufekci – TED

Presentation and communication

Do the hard work to help people learn

Most advice about presentations (and powerpoint) assumes you are standing between a large audience and a big screen, recounting a single narrative with a beginning middle and end. This post is about when you are having a conversation with a small group, when it’s faciliation as much as presentation.

Lots of good advice, including most critically, when powerpoint is just the wrong medium. Now where’s the overhead projector and a chinagraph pencil when you really need them…?

Matt Edgar

Future of work

Should economists be more concerned about artificial intelligence?

There is both growing concern among economists about the potential speed and extent of the disruption caused by automation and also a temptation to draw conclusions from previous industrial revolutions, when apparently similar concerns about apparently similar risks proved unfounded. The not very illuminating conclusion is that it would be a mistake to dismiss the risks too lightly.

Mauricio Armellini and Tim Pike – Bank of England

Data and AI

Weapons of Math Destruction

A polemic against the misuse of big data models by a reformed hedge fund quant – the book’s subtitle, ‘how big data increases inequality and threatens democracy’, is a pretty good indicator of what is to come. Using examples from policing to insurance and teacher evaluation, she shows that the underlying models often encode and reinforce prejudices, rather than being the embodiment of objectivity often claimed for them. It’s very US focused, both in its examples and in its style (a half way decent copy editor could easily make it a third shorter), but it’s a good, simple and readable introduction to some important issues.

Cathy O’Neil – Weapons of Math Destruction

Service design

A view from the other side: perspectives on an emergent design culture in Whitehall

An academic case study of the first year of the Cabinet Office Policy Lab, reflecting on how civil servants see design thinking and the emergence of a design culture for policy. That leads to some interesting reflections on the traditonal model (and culture) of policy making, the power of words (particularly when elegantly assembled), and the difficulty of introducing what may appear to be frivolity to the policy making process.

Jocelyn Bailey and Peter Lloyd – Uscreates/University of Brighton

Future of work Organisational change

Work in progress: Towards a leaner, smarter public-sector workforce

Public services should be designed around the needs of users and to make best use of technology. The result will be improved productivity, the opportunity to break away from traditonal mindsets – and a quarter of a million fewer administrative jobs.

Kate Laycock, Emilie Sundorph and Alexander Hitchcock – Reform

Future of work

Beyond Automation

Or, what should you do to remain gainfully employed? A question answered in ways optimised for slightly anxious readers of the Harvard Business Review, which essentially comes down to collaboration between machines and knowledge workers.

Thomas Davenport and Julia Kirby – Harvard Business Review

Future of work

Harnessing automation for a future that works

Automation will lead to mass redeployment, not mass unemployment. A large proportion of tasks are susceptible to automation, but a much smaller proportion of jobs. And the changes will play out over decades, not years.

James Manyika, Michael Chui, Mehdi Miremadi, Jacques Bughin, Katy George, Paul Willmott, and Martin Dewhurst – McKinsey


Future of work Universal basic income

The Automation Argument for a basic income. Does it add up?

A dissection of the ‘automation argument’ for a basic income – interesting not so much for arguing that automation won’t lead to a life of well-rewarded idleness as for suggesting that a basic income is an inadequate, and ultimately very conservative, approach to the problems automation might bring. Also notable for including a reference to the shoe event horizon.

Katharina Nieswandt – World Economic Forum

Presentation and communication

Doing Presentations

A new compendium of clear and simple guidance on doing presentations well. Very much within the GDS philosophy of a small number of big words, where slides and presenter are interdependent – not suprisingly since the people behind the site helped form that philosophy.

Doing Presentations

Universal basic income

The future of not working

Universal basic income – examined not in Scandinavia but in rural Kenya. This is either Silicon Valley on a very long distance guilt trip or a radical approach to extreme poverty. Are there implications for rich countries?

And despite the title, this isn’t really about not working at all – all the stories are about people being liberated to work smarter once given the margin which allows them to make the change.

Annie Lowrey – New York Times

Behavioural science Service design

The new science of designing for humans

Behavioural science meets service design meets engineering. Some interesting ideas (though the experimental guinea pigs are, as so often, students – that might, or might not, tell us much about the wider population.

Piyush Tantia – Stanford Social Innovation Review