0.4 A Note on Terminology
It can be challenging to find clear terminology in an area of rapid technological change.
‘Algorithmic and data-driven technologies’ will be used to cover diverse technologies that use contemporary computer processing to analyse large amounts of data algorithmically. This includes technology variously described as ‘artificial intelligence’ (AI), ‘machine learning’, ‘neural networks’, predictive analytics, ‘deep learning’, natural language processing, robotics, speech processing and other forms of automation, that are used for the purposes of making decisions.16
Other data-driven technologies that don’t explicitly use contemporary algorithmic technology – such as electronic records management software, online-counselling platforms, and even some forms of machine learning – remain relevant, as they form part of a broader communication ecosystem that can generate and transmit data concerning mental health.
We use the term ‘communication ecosystem’ to refer to the complex, global networks of information and communication technology. This contemporary communications environment encompasses disparate systems – such as the web, the Internet, and various public and private intranets – which are increasingly converging to create massive, complex, and interconnected flows of data. Other technical terms related to specific technologies will be defined as they arise throughout the report.
The aim of the report is to contribute to public governance. ‘Public governance’ includes law and policy but also extends to professional and ethical standards and guidelines, industry norms, civil society advocacy, and cultural expectations around what members of the public consider socially acceptable. Attention to the diverse relationships of power between these mechanisms can help identify the obligations of those employing data-driven technologies, and the rights of those who use and/or are subject to them.