When discussing ‘Smart Cities’ there are many examples that can be used, applying Miller (2011) and Manovich (2001) means that these examples can be analysed from multiple angles.
The first case study is that of the Barcelona residents who used smart technology to measure the noise of the nightlife outside their homes which was preventing them from sleeping. They took the information to the council and proved that the noise levels were affecting their health. The council then made changes based on this data and the residents’ lives have noticeably improved. Manovich’s theories have been expanded in many directions and Miller has divided them into three more categories: technical processes, cultural forms, and immersive experiences. (2011: 14) In this case study the ‘partygoers’ were interacting with smart technologies, the sound recorders/measuring equipment unknowingly which contributed to the dataset which brought and end to their nightlife.
“Interactivity” is embedded in the structure of technology (Miller, 2011: 16) however the forms in which Miller and Manovich describe is different to this example: the context of the interactivity in this case was surveillance, which in itself meant that citizens are interacting with the technologies unknowingly. This is indicative of how many people interact with ‘smart’ technologies daily.
The second example was a smart meter that Thames Water launched to help people measure and reduce their water consumption. In advance of this launch a select group of people from certain London boroughs were given free water-saving devices to save money, alongside house visits and interviews to see how they engaged with the devices. The results showed three types of reaction: engagement, resistance, and indifference.
The use of the “database” is prevalent throughout this example. Databases are vast collections of information which create meaning when layered with other datasets. (Miller, 2011: 20) The use of database is so common in our technological interactions that Miller argues that it is “becoming a cultural form in of itself” (2011: 21). Firstly, there was information about household water usage and location. It was then layered over learnings and assumptions of social and cultural norms to create narratives around people’s water usage.
Interestingly resistance to the house visits and water saving tips came from marginalised people who had insecure living arrangements. Indifference came mostly from the richest people in the area who did not feel the need to save money on water. Many respondents felt that water consumption was a private matter and they were unwilling to share data or discuss the topic. This shows that data driven technologies based on self-reporting is still influenced by cultural norms outside of technology and stereotypes surrounding individual consumption.
These two examples demonstrate that in some areas of society there is still space needed to allow for cultural norms rather than just straightforward data collection. Also, in the Barcelona example, it shows that much of the data collected on us is done so covertly as we are interacting with devices every day unknowingly.
Miller, V. (2011) ‘Understanding Digital Culture’ Key Elements of Digital Media London, Sage publications. pp 12-21.
Taylor, L. (2018) ‘Smart Cities’ Thinking Allowed podcast 25th July 2018. BBC Sounds accessed 10/02/2020: https://www.bbc.co.uk/sounds/play/b0bbr3zn