The Australian Productivity Commission has canvassed consumer control over data and highlighted concerns over the way data is being managed.
The Australian Productivity Commission is calling on government and industry to give consumers more control over their personal information. This recommendation is outlined in a just-released “Data Availability and Use” report.
This report has canvassed a new data framework offering consumer better control over personal data. A major overhaul of data-sharing arrangements is sought across the public and public sectors.
Under its review, the commission is holding public hearings on 21 November in Melbourne and on 28 November in Sydney.
Commission chair, Peter Harris, warned that individuals do not have ownership rights over personal information. This data is treated as an asset “When you create an asset you should have the ability to use it, or not, at your choice.”
He said consumers need rights to opt out of data-collecting activities, while acknowledging privacy laws. Australia cannot forgo the benefits of access under a misconception that denying this minimises the risks.
Consumers need better control over their information. This control gives them the right to access data, or direct it be sent to another party, such as a new doctor, insurance company or bank.
Presently, Australia is missing out on opportunities for improved health care, as well as safer and more efficient infrastructure and production of machinery.
Readily-available data can be utilised for maintenance, enhanced supply chain logistics, and developing the more tailored, data-driven products for financial and energy markets.
Proposed reforms include a contemporary approach to enabling agencies to share and release data. This is subject to stronger safeguards.
Among the reforms, the commission proposes a National Data Custodian with responsibility for accreditation and release. This includes a suite of national interest datasets. States and territories are invited to contribute to and use the national-interest datasets.