Virtual reality and economic injustice in a world with limits

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Decorative photograph of a pile of carved stonesIt is sometimes suggested that materialism and greed are key drivers of our social and political system that largely refuses to acknowledge that we live in a world of limits.  However, Rowan Williams has proposed that we have a ‘culture that is resentful about material reality, hungry for anything and everything that distances us from the constraints of being a physical animal subject to temporal processes, to uncontrollable changes and to sheer accident.’  In other words, it is our desire to be in control of our lives and surroundings that drives us to accumulate wealth and build our strongholds.  Education and learning lead to an understanding of the complexity of the world, a realisation that we cannot control the world and perhaps to unavoidable insecurity, particularly for those people who thought they had some distance between themselves and uncontrollable events.  It is more comfortable to believe that we are in control, adhere to the current out-dated paradigm, and ignore evidence to the contrary. This is equivalent to living in a virtual reality.  This approach not only accelerates uncontrollable changes to the planet but also leads to economic disparities because, as Williams states, economic justice will only arrive when everyone recognises a shared vulnerability and limitation in a world that is not infinite.

Source: Rowan Williams, Faith in the public square, London: Bloomsbury Publishing, 2015.

Image: a pile of carved stones in the cloisters of Hereford cathedral where I bought a second-hand copy of ‘Faith in the public square’ while on holiday [see ‘Personale mappa mundi‘ on November 1st, 2023].

Machine learning weather forecasts and black swan events

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Decorative painting of a stormy seascapeA couple of weeks ago I read about Google’s new weather forecasting algorithm, GraphCast.  It takes a radical new approach to forecasting by using machine learning rather than modelling the weather using the laws of physics [see ‘Storm in a computer‘ on November 16th, 2022].  GraphCast uses a graph neural network that has been trained on 39 years (1979 -2017) of historical data from the European Centre for Medium-Range Weather Forecasts (ECMWF). It requires two inputs: the current state of the weather and the state six hours ago; then it predicts the weather six hours ahead with a 0.25 degree latitude-longitude resolution (about 17 miles) at 38 vertical levels.  This compares to ECMWF’s high resolution forecasts which have 0.1 degree resolution (about 7 miles), 137 levels and 1 hour timesteps.  Although the training of the neural network took about four weeks on 32 Cloud TPU v4 devices (Tensor Processing Units), the forecast requires less than a minute on a single device whereas the ECMWF’s high resolution forecast requires a couple of hours on a supercomputer.  Within a day or so of reading about GraphCast, we watched ‘The Day After Tomorrow’, a movie in which a superstorm suddenly plunges the entire northern hemisphere into an ice age with dramatic consequences.  Part of the movie’s message is that humanity’s disregard for the state of the planet could lead to existential consequences.  It occurred to me that the traditional approach to weather forecasting using the laws of physics might predict the onset of such a superstorm and avoid it becoming a black swan event; however, it is very unlikely forecasts based on machine learning would predict it because there is nothing like it in the historical record used to train the neural network.  So for the moment we should continue to use the laws of physics to model and predict the weather since climate change appears to be making superstorms more likely [see ‘More violent storms‘ on March 1st 2017].

Sources:

Blum A, The weather forecast may show AI storms ahead, FT Weekend, 18/19 November 2023.

Lam R, Sanchez-Gonzalez A, Willson M, Wirnsberger P, Fortunato M, Alet F, Ravuri S, Ewalds T, Eaton-Rosen Z, Hu W, Merose A. Learning skillful medium-range global weather forecasting. Science. 10.1126/science.adi2336, 2023.

Image: Painting by Sarah Evans owned by the author.

 

Empathy with the continuing background noise in society

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Image of book cover for 'a flat place' by Noreen MasudResearch has shown that skimming while reading in digital media reduces the inclination and perhaps ability to engage in higher level reading, while a lack of higher-level reading practice compromises the efficacy of skimming when reading. Higher-level reading implies critical and conscious reading, slow reading, non-strategic reading and long-form reading, according to Schuller-Zwierlein et al, 2202.  The psychologist, Steven Pinker has argued that we learn empathy by immersing ourselves in other people’s minds through reading.  During a recent weekend break, I immersed myself in Noreen Masud’s beautiful book, ‘a flat place’.  It is a memoir about childhood trauma, patriarchy and colonialism told through stories associated with flatlands outside Lahore, at Orford Ness, the Cambridgeshire fens, Morecambe Bay and Orkney.  I read it while staying in the flat landscape around Dunham Massey between Warrington and Manchester which made the physical topography described by Masud resonate with me.  However, her reflections on her and our psyche were also deeply significant – she opens one chapter with a quote from Laura S Brown’s article, ‘Not Outside the Range: One Feminist Perspective on Psychic Trauma’, which perhaps is core to her story: ‘…the constant presence and threat of trauma in the lives of girls and woman of all colors, men of color…, lesbian and gay people, people in poverty and people with disabilities has shaped our society, a continuing background noise rather than an unusual event’.

Brown LS. Not outside the range: One feminist perspective on psychic trauma. American Imago. 119-33, 1991.

Masud N, a flat place, Hamish Hamilton, 2023

Schüller-Zwierlein A, Mangen A, Kovač M, van der Weel A. Why higher-level reading is important. First Monday. 27(5) Sep 5, 2022.

Chirping while calculating probabilities

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Decorative image of a pink roseA couple of weeks ago, I visited the London headquarters of IBM in the UK and Ireland for discussions about possible areas of collaboration in research and education.  At the end of our meeting, we were taken to see some of their latest developments, one of which was their Quantum System One computer.  We had seen its casing, a shiny silver cylinder about half metre in diameter and a metre and half long with a hemispherical lower end, hanging in a sealed glass cube in the lobby of the building.  The computer we viewed was also suspended from the ceiling of a sealed glass cube in order to isolate it from vibration, but was without its cylindrical cover so that we could see its innards which need to be cooled to cryogenic temperatures.  The room in which it was displayed was darkened and a soundtrack of the computer operating added to the atmosphere – it sounded like birds chirping.  IBM are already operating quantum computers, starting in 2019 with a 27-qubit processor and achieving 433 qubits last year with plans for 4,158+ qubits in 2025 in their roadmap.  There are about 80 companies focussed on quantum computing worldwide, including Universal Quantum who are working on a million qubit computer.  Qubit is short for quantum bit and is the quantum mechanical analogue of a classical computer bit.  A computer bit works in binary and can only have a value of 0 or 1.  Whereas a qubit holds information about the probability amplitudes for 0 and 1 which will always have a sum of 1.  The use of probability amplitudes allows complex systems to be described more efficiently and larger solution spaces to be explored.  IBM’s quantum processors are thin wafers about the same size as the one in your laptop but their need for cryogenic temperatures and vibration isolation means we will not be using them at home any time soon.