3.1 The growth and impact of technology
Computers’ speed and power have been doubling every 18 months to two years since the 1960s. We are always ‘on’ – streaming from multiple devices, having infinite storage. During the Covid-19 pandemic, most societies came to rely even further on internet-connected technologies and services. Although there are considerable differences in behaviour by geography, the ‘Digital 2022 global overview report [Tip: hold Ctrl and click a link to open it in a new tab. (Hide tip)] ’ revealed that the ‘typical’ global internet user now spends almost seven hours per day online, with the daily average increasing by four minutes per day (+1%) over the past year.
The use of social media is also growing. As of 2022, the average daily time on social media among internet users worldwide amounted to 147 minutes per day, up from 145 minutes in the previous three years (Statista, 2022).
This growth has detrimental effects on the climate – from the exploitation of natural resources to reproduction of poor labour conditions. The humanitarian organisation ALBOAN points out that:
The environmental rucksack of our technological equipment is very heavy – much greater than the device’s real weight. To produce one smartphone, we use 44.4 kg of natural resources. For one computer, it’s around one tonne.
In his talk ‘Studying digital education in times of climate crisis: what can we do?’ Professor Neil Selwyn gives further examples of the resource demands of technology.
Bitcoin uses an astronomical use of energy consumption, which, at the moment, is estimated to be on [a] par with Thailand, the 13th biggest country in terms of energy consumption. But crypto is not the only technology that has an environmental problem. In terms of just standard Artificial Intelligence (AI) modelling, for example, it is estimated that deep learning techniques now needed for training AI produce a carbon emission equivalent to New York City.
A covert human workforce is a crucial component of creating and maintaining technological services. For example, with AI-driven technologies, the more data you have – images, videos, text – and the more precisely it is labelled, the more sophisticated the algorithm is likely to be. The 2022 National Association of Software and Service Companies (NASSCOM) report found that over 80% of data annotation employees are from rural, semi-rural and underserved backgrounds (Mehrotra, 2022).