Using machine learning, online targeting systems predict what content is most likely to interest people, and influence people to behave in a particular way. This research report shows that people welcome the convenience these systems offer, but express concern when they learn about the systems’ prevalence, sophistication and impact.

This paper presents an interdependent set of technical, organisational, and social challenges to be addressed en route to library operationalisation of data science, machine learning, and artificial intelligence (AI).

The fallout from disinformation and online manipulation strategies have alerted Western democracies to the novel, nuanced vulnerabilities of our information society. This paper outlines the implications of the adoption of artificial intelligence (AI) by the the legacy media, as well as by the new media, focusing on personalization.

The analysis presented in this report demonstrates a new way to identify the kinds of tasks and occupations likely to be affected by AI’s machine learning capabilities, rather than automation’s robotics and software impacts on the economy.

Analysing the relationship between American start-up ecosystems and venture capital investment, and in particular looking at the impact that specialisation can have in building successful ecosystems, such as in St Louis (Missouri), offers insight as to how Australia can catalyse the development of the local sector.