Pictorial paper: GeoPact - Location-aware Smart Contracts

09 July 2020 - Published by Evite van Winkoop
Ella Tallyn, Joe Revans, Evan Morgan and Dave Murray-Rust of the University of Edinburgh have explored the possibility of engaging publics in location-aware smart contracts through technological assemblies. They have developed Geopact: a new way of organizing the infrastructure for transport and services. Their finding have been presented in the pictorial paper which you can find below.

In this paper we focus on exploring the potential of location-aware smart contracts with publics at exhibitions. Smart contracts are agreements written in code that run on distributed ledgers (like the Blockchain) and these are considered ‘contracts’ because distributed ledgers are difficult to tamper with. These contracts tend to follow a simple “if this then that” model, so when certain conditions are fulfilled (if this) then the contract executes and performs an action (then that). We are specifically exploring location-aware smart contracts, that use location data in the conditions, which means they may be very useful for creating new transport systems. A simple example could be: when a vehicle with passengers has arrived at its destination on time, then charge the accounts of the passengers the price of a ticket. This technology presents many new exciting possibilities, but it is difficult to understand. In this paper we describe a system of physical and digital artefacts, called GeoPact, that we’ve designed to help communicate these ideas. We describe how we have shown GeoPact in exhibitions and how it has helped people understand and explore these technologies, and consider the possibilities for their use.

Link to the pictorial paper

Link to videopresentation

Ella Tallyn, Joe Revans, Evan Morgan, and Dave Murray-Rust. 2020. GeoPact: Engaging Publics in Location-aware Smart Contracts through Technological Assemblies. In Proceedings of the 2020 ACM on Designing Interactive Systems Conference (DIS ’20). Association for Computing Machinery, New York, NY, USA, 799–811. DOI:https://doi.org/10.1145/3357236.3395583