Skip to main content

From meatless meat to trustless trust – can Blockchain change the way that we work together to create knowledge in smart cities?

Smart Cities apply technology, connectivity and data to the urban experience, but they could easily become Fake Cities. Their factories still produce things – but they are staffed by robots. Their cars still take you where you want to go – but they are driven by autonomous systems. You can hold their digital products in your hands – but only via a smart phone.
In the worst case, Smart Cities trade down authentic human experiences for something artificial, virtual and ersatz. But can the Smart City ever trade-up and improve on the original?Take food as an example. Scientists are perfecting cultured cells to grow synthetic meat in laboratories. Far from producing an unpalatable substitute, the result is said to be nutritious and tasty. As the world’s population grows rapidly, meatless meat is seen as a carbon and resource efficient alternative that could represent “the future of food”.
In their recent report partners in the UnLoCK consortium considered whether Blockchain and Distributed Ledger Technologies could similarly transform another basic human need – by creating “trustless trust.”
But might this be needed?
The argument goes that Smart Cities join-up multiple systems, more than have ever been connected before. The scale and complexity of the resulting ecosystem means that not all participants can expect to have pre-existing relationships with each other. In this context, it is difficult to know who or what to trust.
The blockchain is seen as a way for Information to be securely shared between peers. The important point is that rather than investing trust in one privileged partner, such as a bank, the focus moves to collectively creating a trusted system; one where peers collectively own and update the Distributed Ledger as a single version of the truth.
The UnLoCK consortium partners identify numerous areas where they would like to experiment with the application of this technology, from understanding the environmental provenance of goods and services within supply chains associated with new local approaches to house building, to systems that afford ‘smart citizens’ greater ownership and control of their personal data.
The consortium partners are planning further discussions to explore how to move from theory towards a working prototype. For more details of the UnLoCK consortium contact, Lisa Kehoe and Stephen Hilton
This blog was written by Stephen Hilton, Director of Bristol Futures Global, and a University of Bristol Cabot Institute Fellow.
This blog was reposted with kind permission from PolicyBristol. View the original blog post.

Popular posts from this blog

Converting probabilities between time-intervals

This is the first in an irregular sequence of snippets about some of the slightly more technical aspects of uncertainty and risk assessment.  If you have a slightly more technical question, then please email me and I will try to answer it with a snippet. Suppose that an event has a probability of 0.015 (or 1.5%) of happening at least once in the next five years. Then the probability of the event happening at least once in the next year is 0.015 / 5 = 0.003 (or 0.3%), and the probability of it happening at least once in the next 20 years is 0.015 * 4 = 0.06 (or 6%). Here is the rule for scaling probabilities to different time intervals: if both probabilities (the original one and the new one) are no larger than 0.1 (or 10%), then simply multiply the original probability by the ratio of the new time-interval to the original time-interval, to find the new probability. This rule is an approximation which breaks down if either of the probabilities is greater than 0.1. For example

1-in-200 year events

You often read or hear references to the ‘1-in-200 year event’, or ‘200-year event’, or ‘event with a return period of 200 years’. Other popular horizons are 1-in-30 years and 1-in-10,000 years. This term applies to hazards which can occur over a range of magnitudes, like volcanic eruptions, earthquakes, tsunamis, space weather, and various hydro-meteorological hazards like floods, storms, hot or cold spells, and droughts. ‘1-in-200 years’ refers to a particular magnitude. In floods this might be represented as a contour on a map, showing an area that is inundated. If this contour is labelled as ‘1-in-200 years’ this means that the current rate of floods at least as large as this is 1/200 /yr, or 0.005 /yr. So if your house is inside the contour, there is currently a 0.005 (0.5%) chance of being flooded in the next year, and a 0.025 (2.5%) chance of being flooded in the next five years. The general definition is this: ‘1-in-200 year magnitude is x’ = ‘the current rate for eve

Coconuts and climate change

Before pursuing an MSc in Climate Change Science and Policy at the University of Bristol, I completed my undergraduate studies in Environmental Science at the University of Colombo, Sri Lanka. During my final year I carried out a research project that explored the impact of extreme weather events on coconut productivity across the three climatic zones of Sri Lanka. A few months ago, I managed to get a paper published and I thought it would be a good idea to share my findings on this platform. Climate change and crop productivity  There has been a growing concern about the impact of extreme weather events on crop production across the globe, Sri Lanka being no exception. Coconut is becoming a rare commodity in the country, due to several reasons including the changing climate. The price hike in coconuts over the last few years is a good indication of how climate change is affecting coconut productivity across the country. Most coconut trees are no longer bearing fruits and thos