Smart City Factors 2
Following on from my earlier post in this series on Privacy and the Smart City
Previous post: Smart City Factors 1
Or — start at the first post
The Blood, Heart, and Brain of the Problem
The ideal of the smart city is built around the need to create sustainable living. The human population is growing exponentially, and along with that comes resource needs, allocation of resources, and waste generation. How to manage this will be technical, but there has to be a sociological layer of control to prevent a privacy catastrophe. The basic factors driving the need for smart cities and how personal data convergese with these are:
● Increase in world population
This is the fundamental driver as this is what determines the resource requirements of our populations. The data generated by the population will be used to inform smart decisions.
● Sustainability
Resources are generally finite, or at least need to be managed, to ensure fair allocation. Sustainable use of resources is the ground stone of smart city success. Personal data can help to understand resource use, ultimately allowing fine grained management of finite resources and control of other types.
● Issues of energy and resourcing for large populations
Energy is one of the most problematic and complex resource allocation areas that we need to manage. Personal data that shows energy use can be used to optimize and manage energy resources in a smart city.
● Housing issues — how to house people
As our population expands, we need to create more efficient housing for individuals. No one wants to live in a world where basic housing needs, like temperature control, are not available. Housing, data, and smart cities are intrinsically linked. Technologies that specifically address housing will need to aggregate data across services and compare/analyse this with reference to the various providers in the housing ecosystem. For example, in the UK, the ‘Housing Data Standard’ (1) has been setup to look at the data standards required for the industry.
● Communicable diseases and evolutionary medicine for smart city living
Communicable diseases, like chickenpox, first became an issue when human populations surged and we started to live more closely together. Today, various factors are involved in communicable disease, including, water supply, sanitation, and climate. Flooding for example, can lead to sewage overflow and contamination of drinking water.
As traditional disease weapons, such as antibiotics, start to become less effective, we are turning to other methods to help remove the factors behind the spread of communicable diseases. These factors include improved living conditions, management of waste and water, and better healthcare options; the optimization of which is data dependent. The discipline of evolutionary medicine may also hold some keys to diesase control.
● Transportation / Safety
Smart city development has placed emphasis on transportation for good reason — congestion rates in cities are horrendous. Looking at USA congestion tables (2) gives a clue as to why this is an issue worthy of smart city resolution. For example, in Washington DC, the average commuter lost 82 hours of their life, per year, because of traffic congestion. Smart city projects across the world are looking at improving transportation in, out, and within our cities. Much of this work is based on having enough data to optimize transport issues like parking, public transport needs, and potentially reducing traffic by facilitating remote working.
● Urban resilience in light of natural disasters and climate change
Our packed cities are susceptible to natural disasters. Climate change is a two-way street for cities; they both add to it and are impacted by it. Cities consume 78% of the world’s energy resources and produce more than 60% of carbon dioxide output (3). Smart cities need to tackle this discrepancy by improving energy consumption, and reduce carbon dioxide and other pollutant outputs, whilst managing climate change impact on citizens. Utilizing big data and analytics can help to alleviate these issues and optimise efficient energy use.
Looking at these factors you can see that none of them stand alone. They each have a touchpoint with one or more of the other factors. The smart city and the technology and data it replies upon, is like an intricate web of interlocking variables. The movement of data across multiple systems along with data aggregation, again, shared across multiple processes, creates a complex data lifecycle. One that is difficult to follow, with potential for multiple failure points in applying privacy protections and that will become the weak link for the city and our privacy. Data that starts off at one point may well be utilized across the entire city, to improve our living conditions and optimize health; but does this have to come at a cost to our private lives and data protection?
Better Privacy, Better Smart Cities
The question is, can we have the data openness and sharing, needed to develop the smart city, but retain the choices needed to offer privacy to the citizens of those cities?
Seattle city in Washington, USA, has a model which seems to have solved the conflict between data openness and privacy. An initiative, ‘What Works Cities’ (WWC) (4) is a U.S. national initiative launched by Bloomberg Philanthropies in 2015. The project looks at ways to use data within cities to improve services and inform local decisions. Seattle received a silver award from the WWC initiative. The city has also partnered with the Future of Privacy Forum (FPF) to look at how they utilize these data and how privacy is impacted by the use of open data. The FPF, released an open data risk assessment on Seattle’s Open Data Program. The paper looked closely at the data privacy risks associated with using citizen data for city improvements. There were a number of recommendations which came out of the assessment, including:
● Building a culture of privacy across the city and encourage privacy leadership. Include this training in the data lifecycle for better management and communications.
● Develop management initiatives that implement risk assessments.
● Set in place measures to identify risk areas and to fully utilize techniques such as de-identification.
● Encourage the improvement of data quality.
● Invest in education and communication between government and individuals around data openness and its implications.
Smart City Limits
We are already at a juncture in our history where we freely offer up our data, be it personal, behavioural, or biometric, to be used by technology providers. This ‘habit’ of letting our personal information seemingly fall through our fingers is likely to carry on, but to an extent never before envisioned as our cities become smarter.
As I write, the most famous of all social media platforms, Facebook, has been hauled over the coals for privacy violations. Facebook allowed the personal information of 87 million users to be sold off to the highest bidder (5) without users truly understanding how these data were being used or having fully consented to that use. Privacy is a complicated and multi-faceted concept. The effects of the loss of privacy are rarely felt immediately. If we are to go forward into a world that is ever-more dependent on information to make it run, we need, on an individual level, to understand the pros and cons of saying “I consent to share”
Watch out for the next part of my series on smart city privacy which wil look at Smart cities around the world.
Resources
(1) HACT: http://www.hact.org.uk/datastandard
(2) Texas A&M Transportation Institute: https://mobility.tamu.edu/
(3) UN Habitat, Climate Change: https://unhabitat.org/urban-themes/climate-change/
(4) What Works Cities: https://whatworkscities.bloomberg.org
(5) Facebook, Mark Zuckerberg statement: https://www.facebook.com/zuck/posts/10104712037900071