Smart mobility, age and data justice

Maria Sourbati,Frauke Behrendt

doi:10.1177/1461444820902682

Abstract

This article examines converging trends in ageing, digitalisation and datafication in the context of mobility and transport. While mobility data are increasingly captured by (public) transport and mobility as a service (MaaS) providers, Internet of Things (IoT) vehicles, apps and so on, the increasing entanglement of mobility and datafication happens unevenly, for example, in relation to age. This is particularly significant in the light of the rise of data-driven policy-making, and its potential impacts on mobility provision for older people. The article highlights new questions for public policy around data gaps and social inclusion and examines them through a UK case study. The results show that old age and mobility is an area with significant gaps in the data available to policy makers. A key recommendation is for commissioning bodies to develop a strategic approach to structured data gathering and analysis that addresses issues of exclusion from smart public service infrastructure.

Highlights

The constant increase in the median age of populations represents a global ‘mega trend’ of demographic change (Price Waterhouse Coopers, 2016)
Age remains a main demographic factor with regard to inequality of digital access, skills and cultures, and outcomes of digital engagement, alongside income and education (Dutton and Reisdorf, 2019). In this hybrid – both theoretical and empirical – article, we examine these wider converging trends in ageing, digitalisation and datafication, especially in the context of mobility and transport
We found two main reasons for this situation, one being the strong fragmentation of community transport providers that resulted in small providers with low data and Information and Communication Technologies (ICT) capabilities or skills and little or no facility to invest in either

Summary

Introduction

The constant increase in the median age of populations represents a global ‘mega trend’ of demographic change (Price Waterhouse Coopers, 2016). By 2050, there will be more above 65-yearolds than below 15-year-olds and the number of people over 100 will increase by 1000% Another line of constant increase, the use of digital ICT, has caused an exponential growth in the amount of digital data, often generated as a by-product of our mediated. In countries with high Internet diffusion, a growing majority of older adults use online digital media. Analysis of US data of the same year suggests that while some older groups, such as those who are younger, more affluent and more highly educated, use various technologies at rates similar to adults under the age of 65, this is not the case with the very old groups (Anderson and Perry, 2017). Age remains a main demographic factor with regard to inequality of digital access, skills and cultures, and outcomes of digital engagement, alongside income and education (Dutton and Reisdorf, 2019)

Objectives

Findings

Methods