Harnessing the Economic Value of IoT
In the second content partnership with IoTUK, PETRAS is examining how the IoT is changing the face of the digital economy in all sectors. How can we harness the economic potential of the internet of things as more and more devices are connected? In our introduction blog, Dr Razvan Nicolescu talks about potential scenarios which are already being impacted by IoT.
Let’s start off with a story. Meet Angela. She wakes up in the morning, perhaps a little groggy from a late night. She gets up, she gets her breakfast; she goes and gets ready for work. She leaves the house and she gets into an autonomous vehicle. The car pulls out of the parking space, drives 100ft, pulls into a car park. She gets out and walks away.
This can be represented like this:
We won’t break down this sequence into further components to work out relations and processes as scientists and engineers would normally do. Rather, we want to make sense of some of the interdisciplinary aspects this scenario involves.
Angela didn’t start the car. She seems, at the first glance, to be an average pedestrian. However, the vehicle might be part of a car-sharing scheme or made available by her employer, or by her preferred supermarket. In such scenarios, both Angela and the vehicle know they should soon make contact.
There’s a lot going on under the bonnet. There’s scheduling, confirmation, purchase of smart services – such as dynamic insurance for the ride, or customised telemetry services, as well as a series of consent agreements and notifications. These processes require authentication, encryption, data processing, storage and routing to third-party applications and platforms.
Once Angela is on board she enters into a specific Autonomous Driving Domain (ADD) that complies with national and international legal systems and policies but is set-up and maintained specifically for Angela and for this particular ride only. The next rider will have different conditions; even Angela’s next ride will have a different ADD. Here we can see the realisation of new economic business models that go beyond ADD with micro-economic scenarios. With this level of flexibility and customisation, there are myriad possibilities.
These new business models might not even be owned by one vendor. They could be transactioned and exchanged, in whole or in part, on a given market. Angela might ride for free because she exchanges her Autonomous Driving service with another service in which she “produced” electricity for a local power service using her domestic IoT plugs. All these transactions can be stored and exchanged over a blockchain infrastructure.
Let us now zoom-in even more and single out one particular topic from the Autonomous Driving Domain: the insurance aspect. There are several things that could be covered by insurance policies: Angela herself, the vehicle itself, goods and personal belongings, as well as third parties such as other vehicles and pedestrians. Angela can also share her car with her family or her best friend when she travels to visit her. So, dynamic insurance policies can be easily set-up with a high granularity that reflect drive histories, drive patterns, but also the time and route of the journey.
The current way of underwriting insurance policies may not be sustainable in an IoT-aware environment. The existing policies are static, rigid, and cannot rely on meaningful historical data. Instead, IoT-based insurance policies can be designed and managed in real-time using the vast range of IoT data generated during the short car ride.
Dynamic insurance policies can be set up not only in relation to data generated by Angela and the vehicle, such as the type of car, but also by other external factors, such as crime rates in the areas the vehicle is operating, or current weather conditions.
Because of IoT, these factors can be quantified, harnessed, and analysed in ways that would impact the way insurance policies are delivered, operate, and mitigate. These aspects would not only improve significantly issues such as accountability and litigation but they can also inform local policies and public services.
However, bias in machine-learning algorithms may lead to incorrect, unethical decisions (e.g. culture-specific but safety-irrelevant driving behaviour). And insights from data may challenge existing laws (e.g. those women are better drivers but that insurance rates cannot be lowered for them due to discrimination law). We’re looking into designing dynamic insurance together with Lloyd’s Register Foundation in our latest PETRAS project.
At PETRAS, we are studying these new scenarios. Our work focuses on the relation between value and economics in respect to IoT technology. However, as you can see, this relation is not straightforward and exclusive. We’re breaking the concepts down into components that inform, sustain and continually transform the notion of value and economics. These components belong to the social, economic, and technical domains.
We can already see that entrepreneurs, big companies, and members of the public alike have very particular views, work attitudes, and consumer practices in relation to digital technologies. We’re also seeing how emerging digital technologies challenge established financial and economic mechanisms and initiate new markets and business organisations. There’s also the technical effort and innovation required to make technologies work and make them available to the public. Our work puts together these three viewpoints and shows how they inform each other in advancing our economy as we see the coming future of IoT transformations.
Razvan Nicolescu is a digital anthropologist working at the Department of Computing, Imperial College London. He obtained his BSc and MSc in software and networks for telecommunications (University Polytechnics, Bucharest) and his PhD in social anthropology (University College London). Razvan has a research interest in the impact of new digital technologies on social relations and political economy, notions of governance and informality, social and economic inequality, social and cultural norms, and feelings. He is the author of Social Media in Southeast Italy: Crafting Ideals (2016, UCL Press) and co-author of How the World Changed Social Media (2016, UCL Press). His current research focuses on the use of blockchain technology in intelligent transportation systems and the design of dynamic cyber insurance policies using IoT.