Nudge is an interesting theory framework for user experience design. Here's a great introduction #ux #nudge

"This is the first internationally published paper (it was previously published in a Spanish conference of a series that deals with a system, intended for volunteer computing, that uses a pool for implementing distributed evolutionary algorithms. The basic idea is that the population resides in a pool (implemented using CouchDB), with clients pulling individuals from the pool, doing stuff on them, and putting them back in the pool. The algorithm uses, as much as possible, CouchDB features (such as revisions and views) to achieve good performance. All the code (for this and, right now, for the next papers) is available as open-source code."

"The clicktivism of very targeted campaigns, like Londoners on Bikes, Move Your Money or the Big Switch will transform our democracies. The important lesson from micro-campaigning is that identity follows political relevance, not the other way around. "

An excellent summary/reminder/introduction to the cognitive biases and heuristics covered in the book and what a NUDGE means.

The Nudge Unit has been running dozens of experiments and the early results have been promising*. In one trial, a letter sent to non-payers of vehicle taxes was changed to use plainer English, along the line of “pay your tax or lose your car”. In some cases the letter was further personalised by including a photo of the car in question. The rewritten letter alone doubled the number of people paying the tax; the rewrite with the photo tripled it.

Another set of trials in Britain focused on energy efficiency. Research into why people did not take up financial incentives to reduce energy consumption by insulating their homes found one possibility was the hassle of clearing out the attic. A nudge was designed whereby insulation firms would offer to clear the loft, dispose of unwanted items and return the rest after insulating it. This example of what behavioural economists call “goal substitution”—replacing lower energy use with cleaning out the attic—led to a threefold increase in take-up of an insulation grant.

Decision Architecture
Historically, the UX design toolbox has not included a focus on the importance of designing for decision-making. This needs to change. User decision-making plays a critical role in the achievement of website objectives.

It’s important to understand that there is no such thing as a neutral design. Every design has an effect on user decision-making, regardless of whether designers have proactively designed for effective decision-making. It’s no different from designing for usability. Every website is more or less usable, regardless of whether it was designed for good usability.

Architecting for decision-making results in a win/win/win outcome for designers, for businesses, and for users. This is why decision architecture—architecting for an optimal user decision-making experience—deserves a prominent place in the UX toolkit.

This is the first time that the Government has explicitly sought to draw upon behavioural insights to tackle fraud, error and debt in a systematic way. The insights outlined in this document, applied in a range of different contexts and settings, show that not only is it possible to apply behavioural insights to reduce fraud, error and debt, but also that it can be done in a highly cost-effective way.

"This paper develops generalizations of empowerment to continuous states. Empowerment is a recently introduced information-theoretic quantity motivated by hypotheses about the efficiency of the sensorimotor loop in biological organisms, but also from considerations stemming from curiosity-driven learning. Empowemerment measures, for agent-environment systems with stochastic transitions, how much influence an agent has on its environment, but only that influence that can be sensed by the agent sensors. It is an information-theoretic generalization of joint controllability (influence on environment) and observability (measurement by sensors) of the environment by the agent, both controllability and observability being usually defined in control theory as the dimensionality of the control/observation spaces.…"

"Data collection at a massive scale is becoming ubiquitous in a wide variety of settings, from vast offline databases to streaming real-time information. Learning algorithms deployed in such contexts must rely on single-pass inference, where the data history is never revisited. In streaming contexts, learning must also be temporally adaptive to remain up-to-date against unforeseen changes in the data generating mechanism. Although rapidly growing, the online Bayesian inference literature remains challenged by massive data and transient, evolving data streams. Non-parametric modelling techniques can prove particularly ill-suited, as the complexity of the model is allowed to increase with the sample size. In this work, we take steps to overcome these challenges by porting standard streaming techniques, like data discarding and downweighting, into a fully Bayesian framework via the use of informative priors and active learning heuristics. We showcase our methods by augmenting a modern non-parametric modelling framework, dynamic trees, and illustrate its performance on a number of practical examples. The end product is a powerful streaming regression and classification tool, whose performance compares favourably to the state-of-the-art."

Organizational Consulting VALUE THROUGH COLLABORATION

‘Nudging’ on its own is unlikely to be successful in changing the population’s behaviour. That is the main conclusion of the House of Lords Science and Technology Sub-Committee’s report, Behaviour Change, published today.

The report - the culmination of a year-long investigation into the way the Government tries to influence people’s behaviour using behaviour change interventions – finds that “nudges” used in isolation will often not be effective in changing the behaviour of the population. Instead, a whole range of measures – including some regulatory measures – will be needed to change behaviour in a way that will make a real difference to society’s biggest problems.

But cognitive biases aren’t something which ignorant citizens have and which wise governments are free of. Policy-makers are also prone to them - either because they are as irrational as everyone else or because they have to pander to an irrational electorate. One of my big complaints against Nudge is that it fails to appreciate this sufficiently, and so panders to the ideological fiction that policy-making is or can be entirely rational and evidence-based.

XY is a family of array-oriented, concatenative programming languages with first-class continuations. XY 1 has quotations, lists, functions, and patterns. XY 2 is flat. XY 0 has quotations and shuffle-symbols but dispenses with lists and patterns.