A gentler way

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  • Energy pricing

    The increases in British energy prices in 2022 are unprecedented in our lifetime. The dual fuel price cap for electricity and gas supplied to a typical household is likely to be more than twice as high at the end of December as it was at the beginning of January. Within months electricity will cost more, even adjusted for inflation, than at any time since the 1930s.

    So the government plans to bring in subsidies, as of today (May 26) supposedly around £400 per household, or about one quarter of the typical pre-subsidy annual increase of £1500 per household. All households will benefit, with as-yet unspecified additional support for the poorest.

    Yet the gulf remains between the price of energy and its value, especially when the environment is taken into account. On the coolest days in May, many (most?) home owners and tenants will turn on the heating without giving very much thought to its cost. How many of us turn off computers and lights when we don’t need them, cut down on oven usage, or forego a trip in the car because of the cost of petrol? As of yet, in spite of this year’s price inflation, it is unlikely that we will be making major changes to our way of life.

    Meanwhile global wheat prices have risen by more than 60% this year, largely due to Russia’s invasion of Ukraine.

    Poverty vs the environment?

    How do we reconcile fuel poverty and the cost of living on the one hand and environmental devastation on the other? One approach is to subsidize food and energy in a limited and selective way, and tax it fiercely beyond certain levels and within certain categories. The taxes raised contribute towards the subsidies and also hospital services and clean energy. This general approach has the merit of being socially progressive.

    Take flying, for instance. One interesting idea – not mine – is that a person’s first (return) flight of the year could be priced at roughly today’s levels – subject, perhaps, to a distance-related levy. Each subsequent flight taken in the year by the same individual doubles in price: 2X, 4X, 8X, … The formula could be applied to both business and leisure flights. Frequent fliers would pay not just a bit more, but many times more for their average journey than those who go for a single annual holiday. Social arguments aside, there is a pleasing symmetry between the exponential nature of the pricing, the exponential increase in per capita energy consumption during the last century, and the exponential impact in terms of climate change.

    Similar thinking could be applied to home energy use – though it would probably depend on smart (daily) metering. The first daily 10 kWh (30 kWh) of electricity (gas) consumption in the home would be subsidized. (There would need to be a seasonal profile, and adjustment for number of occupants, but the details could be worked out.) Any extra usage during the day would be at a significantly higher rate. Couples living in large detached properties might need to turn off the heating in parts of the house to avoid large bills – or alternatively, let out rooms to lodgers. Those with poor insulation, which should be separately subsidized, would be strongly incentivized to improve it. Those of us with early smart meters, who only paid attention to them in the first week when they had novelty interest, would take notice of them properly, along with the rest of the population who experience the later roll-out.

    And to food. In this case, there are different categories to consider. The government could tax junk food at levels comparable to tobacco in percentage terms. If you want to eat red meat, that’s fine, but it is a luxury item that will also be heavily taxed. Staples like grains, potatoes and leafy vegetables would be subsidized. Anything that is bad for health or the planet would be expensive.

    Such an approach does not prevent people from ever enjoying themselves – it simply makes it (much) more expensive, so that luxuries are treated as such. Everyone is protected to a certain degree. The wealthy and middle classes pay proportionately more. Incentives are put in place that would be environmentally beneficial.

    One can but dream.

  • Computer vision

    We have allowed ourselves to become slaves to computers, and thereby to numbers and precision. In most contexts, precise numbers are spurious or misleading. Our obsession with them often leads to blinkered thought processes.

    Over the last decade, Big Data has become big business. A vast amount of time and energy is channeled into a narrow obsession with a specific class of questions and concerns – ones that can be quantified using a computer, the more numbers the better.

    Here’s an alternative approach to analysis, for businesses and individuals. Start by putting the computer to one side. Start with qualitative issues and ideas, and – where they matter – approximate numbers only, in order to get a feel for the key issues and their relative importance. Only then consider whether it’s possible and worthwhile trying to get more accurate numbers, which may or may not entail greater precision. And only then consider whether computers could help and whether it’s worth the investment in time and energy, and if so how much.

    Climate analysis

    Analysis of climate change and carbon targets provides a good example of our enslavement to computers. Over the last year, many institutions have become obsessed with measuring their carbon footprint. In some ways, this is good news. It’s great that awareness of the climate crisis has increased so much in twelve months. The desire to analyse is encouraging, and a natural starting point for target setting is to assess one’s (individual or corporate) current carbon footprint.

    Unfortunately, this good intent often leads to a fixation with the wrong question. Instead of “What matters most?” the question that is addressed is “What can my computer work out?”.

    And the latter question shapes the analysis that is undertaken. Using Paris terminology, Scope 1 and Scope 2 emissions are easy to define and determine – at least in comparison with Scope 3 – so most of the effort is concentrated on them. Yet for most institutions, with notable exceptions such as power generators and cement kilns, Scope 3 emissions are likely to be more significant. They are also harder to demarcate (how far upstream or downstream should the analysis extend?) and the corresponding data, being external to the institution, is harder to obtain.

    Instead of focussing effort on working out approximate values for Scope 3 emissions, the common tendency is to ignore them, or at least make them low priority. Oil companies for example continue to focus primarily on Scope 1 and 2, even though 90% of oil-related carbon emissions occur downstream, where the oil is consumed. And Scope 3 is relatively easy to estimate for an oil company; most other companies make little or no attempt to measure their Scope 3.

    Admittedly, there are other factors at play, one such being that companies don’t want to have targets for things they regard as outside their control. But, without being the only ones, data availability and ‘computability’ are certainly major drivers of how companies spend their time and energy.

    Following the alternative approach mentioned above, a company or individual can fairly quickly establish what matters most as regards their greenhouse gas emissions. For an oil company, it’s their Scope 3. For a builder, it’s likely to be the upstream manufacture of the materials (Scope 3 again). For a financial institution, it’s the emissions of the companies to which it lends money, a category conveniently labelled as “Scope 3 Category 15” in the Paris agreement. For a management consultancy, say, it’s likely to be its business travel (“Scope 3 Category 6”); for a government office, it’s probably employee commuting (“Scope 3 Category 7”). For a boarding establishment (e.g. a public school, nursing home or prison), it’s probably the food served on site, which in Paris features … nowhere.

    Once the question “What matters most?” has been addressed, the right priorities for action can be put in place. The oil company could (should) focus on targets for reducing hydrocarbon output. The British builder can decide to use British stone rather than stone imported from Asia. The consultancy can look at cutting back on business travel. The government office can bring in an enlightened approach to teleworking. The boarding school or care home can concentrate on the food it serves.

    For this to work, we need amongst other things a cultural awakening that a computer is a tool for thought, not the embodiment of it. Though numbers matter, it matters more to determine a rough answer to a major question than a precise answer to a minor one. But computers dominate our thinking and computers thrive on numerical precision. In consequence, the entire industry is obsessed with Big Data and some of the biggest questions are parked if the numerical data is unavailable, unreliable, or hard to interpret.