Australian citizens aren’t sold on a data-powered economy
Article by Tableau Software A/NZ MD Nigel Mendonca
If Australia truly harbours ambitions to become a data-powered economy, it has some serious work to do.
There are two main paths for an economy to become data-powered. One is for change at a grassroots level, where the collective actions of individuals and companies build up to a critical mass that shifts the dial at a potentially national level. The second is for a top-down change where government policy sets the tone for what is and isn’t desirable and permissible.
Based on the evidence, the government may not be upholding its end of the bargain
A new poll by the Social Research Centre at Australian National University (ANU) raises significant concerns around government as custodians of data. Only 29.3 per cent of respondents believed the Australian government could be trusted to use data responsibly, and only 26.8 per cent believed the government was “open and honest about how data are collected, used and shared”.
Many respondents feared a breach or misuse of public data holdings. “If government, researchers and private companies want to make use of the richness of new types and sources of data, there is an urgent and continuing need to build up trust across the population and to put policies in place that reassure consumers and users of government services that data can be stored and managed with appropriate security and access safeguards in place,” the researchers said.
Though this is not exactly an ideal starting point, it is symptomatic of problems that governments encounter more broadly as they attempt to become more open and data-driven.
An enduring challenge is that some governments have not been good at outlining or selling the benefits of their data-powered economy ambitions. “As governments move swiftly ahead with data integration, it is imperative that they demonstrate that ‘huge value’ to the whole of society in ways that even the least tech-savvy among us can easily grasp because the “downside” is presently much better understood” than the upside, one commentary from 2017 states. Two years on, it appears little has changed.
Yet, the optimal use of data can create public good
Public data useful not just for policymakers: it can also be used by businesses and by citizens to better engage with other individuals and organisations. Nations generally have an opportunity and a requirement to make data available and be transparent about the data they have. They should be asking how they can make as much data as possible available to more people, rather than locking access down to a select few.
Some governments perform better than others in this space. Singapore and the United Kingdom, in particular, have been frontrunners in making government data sets open and accessible to the general public, and have seen an uptick in innovation as a result.
Australia could do worse than take clues from these countries in how they resolved - and continue to de-escalate - any perception problems that might arise along the way.
Governments that not only open public datasets but also enrich them with data from other sources can achieve a multiplier effect on the public good. As a general rule, the more you can enrich data with other sources, the better it becomes. Likewise, the more people that can touch that data and transform it, the higher the chance of innovative outcomes.
Naturally, governments also need to lay down some ground rules and set base level policies around the responsible use of data. Governments must try to police what data is collected, how it is collected, who is able to manage and handle it, and for what duration.
It’s a bit like what would happen if I gave you a car: you could use the car responsibly or cause accidents. Therefore, I need to set speed limits, ensure people don’t drink and drive and ensure drivers wear seat belts. We almost need to have the same thing with data. You still want to let people go from A to B, but without causing harm along the way.
Great things can still happen within clearly defined ground rules. For example, I’m currently using open deidentified data to analyse levels of loneliness experienced by citizens in different parts of the world. We’re exploring to what extent - if any - factors such as technology, social circle and even weather can impact a person’s loneliness.
It’s the kind of research project one might typically expect to find in academia, and yet - with the benefit of open data - this becomes a project that can be undertaken by anyone with a keen interest, adding to the social research knowledge base in the process.
I don’t know what we’ll find, but it’s entirely possible our analysis could lead to policy change. It might be used as a basis to create new solutions to identify loneliness, perhaps at a faster pace than previously, and to connect at-risk people to government services more quickly. This is the exciting thing about open data: it encourages innovation outside traditional avenues.
Given the propensity for “happy accidents” to emerge from research endeavours, this kind of activity should be actively encouraged. Yet Australia could miss its next accidental discovery if it can’t shift the dial on perception around open data. It’s past time for a change of strategy.