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Harnessing the power of data to deliver truly smart cities: Ensuring an ethical approach

© daria nepriakhina - unsplash

The power of data to deliver smart cities has enormous potential, but accessing and interpreting that data brings unique challenges. Martin Howell, Transport Market Director, Worldline UK&I, examines the importance of an ethical approach to traveller data access and use.

As Internet of Things (IOT) device usage continues to grow exponentially, so does data generation from those devices. Many organisations now have whole teams or departments dedicated to data management and analysis, clearly illustrating the importance of this function. While much data is being generated, questions remain over whether its true power is being effectively harnessed.

Irrespective of the sector, data presents a vast opportunity. Properly gathered, collated, and interpreted, data can be transformed into vital information giving a detailed picture of activities, behaviours, and performance, often in real time. This can inform operational decision-making, deliver best practice, and optimise overall customer and user experience. It can also identify behavioural changes and assist with planning.

One area where data has a potentially critical role to play is smart cities. In transport, effectively managed data can contribute significantly to a demand-responsive service delivering a safe, efficient and enjoyable experience for travellers.

The need to optimise passenger experience

Customers need to know they can get where they want rapidly, that they can easily pay for their travel and that their chosen transport mode will be clean and safe. They also need rapid information on anything that might impact their journey. The whole experience needs to be seamless, or they will simply go elsewhere or revert to private vehicle use.

It’s clear that information on traveller numbers, movements, behaviours and journey types can give a detailed picture allowing transport planners and providers to deliver services that anticipate and meet the needs of most, if not all, customers.

Seeing all customers connected as a network of journeys and data, with hotspot mapping to understand where bottlenecks may occur – for example, at peak travel times for work or during large events – would be vital to this process.

Successful data use in smart cities

It is easy to see the value of data in delivering smart transport and smart cities as a whole. Norway is a champion of open data, operating a national registry of open data from the public sector, covering areas such as the environment, health, geography, agriculture, traffic and demographics. As part of this, traffic data from the Norwegian Mapping Authority is made available to car-sharing companies to help determine demand for their services.

Going beyond open data

Much intelligence currently being applied is drawn from ‘open data’ – freely available data, usually via the internet, usable and shareable by anyone, anywhere, without restriction.

For example, Transport for London provides a wealth of open data on its website and app regarding current activity – whether services are running on time, in as close to real time as possible.

Beyond that, information is available on traveller counts and the busiest times on trains and in stations. However, information of this kind is rarely if ever available in real time and gives no clear picture around individual traveller behaviours, reasons for travel, journey types, and interests – what is described as ‘traveller data’. Much of this data comes from websites or mobile phones, so falls under the umbrella of ‘big data’.

The power of big data

A recent report by the Leveraging Big Data to Manage Transport Operations project, an international consortium of parties with an interest in this area, detailed challenges around using ‘big data’ in the transport sector, such as free will, personal data ownership and discrimination, and trust.

‘Big data’ refers to sets of data too large to be analysed using traditional computing approaches and which requires artificial intelligence tools or methods to harness its true value.

When responsibly managed, big data can be vital in optimising customer experience. Think of how Google and Facebook, for example, show adverts based on what you have been browsing recently.

Applications of this type in public transport go well beyond, for example, information on service delays via screens in carriages. The ability to change billboard information, for example, to suit the known interests of an approaching customer offers immense potential. And there are countless other ways where the entire customer experience could be personalised based on responsibly-analysed data.

There is a growing sentiment that data belongs to the individual to whom it relates – the person who created it – and should be private and anonymised unless that individual gives their permission for its use in a specific manner.

Many individuals are concerned their data is being harvested for nefarious advertising purposes or, even worse, criminal usage. Instead of placing the onus on companies who want or need data to improve their product offerings to act scrupulously, the reaction has instead been to fully lock up data that could possibly be linked to an individual.

© UTM/b

This means data-driven services such as public transport apps cannot act in the best interests of the customer. If the app cannot learn a customer’s route, how can it make suggestions to optimise their journey and alert them of alternatives? A guess can be made based on customer number observations, but the data will not be personalised or reflect individual needs such as shift patterns and accessibility preferences.

For this sort of experience to be delivered, customers should be encouraged to give consent for specific data to be used. However, that data must be securely held and never used for anything other than the express purpose for which consent was given. Indeed, there is a strong case for uncapped fines for companies who do not provide adequate security for data collected and used.

The importance of ethics

This challenge has been recognised internationally for some years and the Sustainable Mobility for All (SuM4All) Partnership, a coalition of 56 international organisations with a shared ambition to transform the future of transport and mobility, has brought together key parties to develop a best practice approach.

SuM4All published a report entitled ‘Sustainable Mobility: Policy Making for Data Sharing’ last year. This outlined a policy framework comprising five key areas: use and analysis; governance and accountability; data infrastructure; data standards: and data collection and merging. It also offered recommendations as a call to action for policy-makers.

A recurring theme within the report was the importance of ethics in data gathering, holding and use. In particular, the report noted that: ‘… judgements of the ethical implications are typically subjective, varying between countries, organizations, or even individuals. It is critical to be able to monitor and prevent ethical violations in the first place, as negative impacts may be difficult to undo or correct. Active policy making on ethical practices may help build customer trust in data sharing, and enhance reputation of entities that are in compliance.’

What this means is that organisations must be sensitive to the views of all individuals regarding the gathering and use of their data – and that best practice should be enshrined in law. Ideally, international consensus in this area should be achieved – it is a significant challenge, but the benefits would be enormous.

How to ensure an ethical approach

An ethical approach should therefore always be adopted when considering a big data approach. In particular, organisations must ensure that all data is collected, and used, fairly and lawfully.

The presence of appropriate controls and accountability processes must be established. Organisations should ensure the data is of good quality – valid and accurate, ideally verified through a separate data source. Biased data will not lead to effective decision-making. Big data must be processed and interpreted, and decisions on how that is done are not necessarily neutral. To achieve this, data scientists should collaborate with other experts to ensure a balance between privacy and effectiveness

Also, only the minimum quantity of data needed should be extracted. Just because data is accessible does not mean that it must necessarily be collected or used.

’Accessible’ and ‘ethical’ are not the same thing. Ethical organisations must focus on dignity, respect and privacy in data management. Above all, they should ensure that the individuals from whom data is collected actually benefit from its use.

Leading industry players hold the key to best practice in ethical data use in improving public transport. They should be brave enough to act and set their own standards rather than simply seeking to comply with Government regulation. Showing leadership in ethical data treatment will earn users respect and trust and ensure an optimised, data-led experience.

09.11.2022
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