Fair Energy Transition for All: FETA Project

Image from the FETA website

In this post I would like to take a quick look at the project FETA, Fair Energy Transition for All.

Energy Transition

Energy transition refers to the move towards carbon neutral energy production, and the concept under discussion is how this transition process can be made as fair as possible for the largest number of people.

How could it not be fair? We might ask this question, but we might come up with some simple suggestions: the transition is going to cost money, tax money and consumer money, and this added expense is not going to be felt equally across the population (we are talking about Europe here). If a government adds a cost (to use a current example) to the price of electricity in order to fund wind generation, this extra cost represents a different percentage of disposable income for different groups. If you spend 2% of your income on electricity it might not be noticeable, but if you spend 20% then it certainly will.

The current crisis with energy costs has already demonstrated the fragility of a population that relies on power for heat and electricity in any form, and any transition tax applied a year ago will today both raise more money and put more strain on poorer households. And subsidies for insulating houses, buying new white goods or towards the cost of an electric car require outlay on the part of the consumer, which means that it excludes those without access to such funds. And that says nothing about the skills needed to navigate the bureaucracy

Adding charges to bills and subsidising energy efficient purchases is a top down approach though, decisions taken by governments and energy company bosses (my rather cynical interpretation coming out here), but this is a a problem that FETA aims to address.

Some thoughts from the website:

For the energy transition to take place, policy measures need to be put in place that will have an impact on housing, energy, transport and other aspects of our everyday lives. However, the impacts of climate policies, such as rising fuel taxes or the closure of coal mines, affect socially and economically disadvantaged groups the most. This leads to economic and social conflicts: many people feel alienated by climate change policies, which they perceive as elitist issues, and they feel that the elites are out of touch with their lives and are not aware of their interests.

For climate action to be successful, widespread public acceptance is needed. European and national policy-makers need to develop climate change policies that everyone can relate to and benefit from! Policy-makers should listen to those whose voices are being left out of the current debate and include them in the policy and communication process. That is the only way in which a fair energy transition can be achieved – for all!

All of which boils down into three main questions:

  • How can the EU and its member states prevent climate policies from hitting the pockets of poorer households the hardest?
  • How can policies be designed so that everyone has an equal opportunity to enjoy the benefits of the energy transition?
  • How can the energy transition be combined with social justice?

To find answers, the project is conducting public participation events that involve 1000 participants in 90 focus groups spread across Europe, while the Bassetti Foundation (our funding partner) is working on policy proposals by running some expert workshops in Italy. The aim is to better understand the emotions, fears, views and needs of vulnerable people with regards to the energy transition and its current and potential impact on their living conditions, in order to provide input to national and European policy-makers, researchers and stakeholders to help them develop fair energy transition policies and enhance the communication with the target group.

The website offers more information and is well designed and really easy to follow.

Just down our street at Technology Bloggers we might say.

Responsibility-by-design

Throughout last year I worked on a European Standard called CWA 17796 Responsibility-by-design – Guidelines to develop long-term strategies (roadmaps) to innovate responsibly, for the CEN. It is now available to download and use.

CEN is an association that brings together the National Standardization Bodies of 34 European countries, providing a platform for the development of European Standards and other technical documents in relation to various kinds of products, materials, services and processes.

This is what they say about themselves: The CEN works together with national standards bodies to create documents established by consensus and approved by a recognized body that provide, for common and repeated use, rules, guidelines or characteristics for activities or their results, aimed at the achievement of the optimum degree of order in a given context.

This document is a workshop agreement that provides guidelines to develop long-term strategies (roadmaps) for innovating responsibly, thereby helping organizations to achieve socially desirable outcomes from their innovation processes. The roadmaps encourage a “responsibility-by-design” approach that integrates considerations of technical, ethical, social, environmental, and economic aspects all along the research, development, and design process leading to an innovation.

After an introduction, the agreement offers an overview of principles for Responsible Research and Innovation, (reflection, anticipation, inclusion and responsiveness), before moving on to a section detailing the framework proposed.

The agreement closes with a series on annexes in which easy-to-interpret tables offer examples of RRI actions, tools, guideline applications, SWOT analysis for implementation in industry, tools for stakeholder analysis, methods for stakeholder engagement, criteria for impact analysis and key performance indicators before concluding with resources from other initiatives and a bibliography.

The idea is that it is a guide, offering suggestions on possible approaches that might help to make innovation strategies more responsive and responsible, following on from years of research and policy suggestions promoted by the European Commission.

Practical and not abstract, for ten Euros it can be downloaded here.

Some Thoughts on Bias

A Little story of bias

A father was driving his two children to watch a football match when they were involved in a terrible accident. The driver was killed immediately, as was one of the boys. The youngest child was sitting in the back on his car seat, survived the accident but was seriously injured.

The young child was taken to hospital where he was rushed into an operating theatre where they hoped they could save his life.

The doctor entered the room and looked at the patient, froze and said “I cannot operate on this boy, he is my son!’

Bias within Data

If you asked the question of how the boy could be the doctor’s son you are falling in a trap of bias. The doctor in the story is the child’s mother (obviously), but that may not be the first solution that comes to mind. In many societies we are brought up to see doctors as male, and nurses as female. This has really big implications if we are using computers to search for information though, as a search machine that uses content generated by humans will reproduce the bias that unintendedly sits within the content.

The source of the bias could be from how the system works. For example, if a company offers a face recognition service and uses photos posted on the internet (for example categorized in some way by GOOGLE), there will be a lot more white males than girls of Asian background. The results will be more accurate for the category with the largest presence in the database.

If a banking system takes the case of a couple who declare an income together, it will presume that the man’s income is higher then that of the woman’s and treat the individuals accordingly, because from experience the data shows that men’s income is higher then that of women and this generalization will become part of the structure.

The problem with language is also easy to see. If the example above of the doctor problem can be in some way ‘seen’ in the vast amount of text analyzed and used for an algorithm, then proposals and offers will differ according to gender.

Let’s take how we describe ourselves for a moment. A male manager will use a set of descriptive terms to describe himself that will differ from those used by a woman, he might be assertive, but she is more likely to be understanding and supportive. A system that unwittingly uses a dataset based upon (or even referring to) language used in job adverts and profiles of successful candidates will replicate a gender bias, because more proposals will be sent to people who use the language that reflects the current make-up of the employment situation.

In short: More men will be using the language that the system picks up on, because more men (than women) in powerful positions use that type of language. The bias will be recreated and reinforced.

In 2018 the State of New York proposed a law related to accountability within algorithms, Take a look at this short description, and the European Commission released a white paper on Artificial Intelligence – A European approach to excellence and trust in 2020. It might be more important an argument than it first appears.

There is lots of literature about this problem if you are interested, a quick online search will offer you plenty of food for thought.