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What constitutes good intelligence is best understood by practitioners but has not been explored through empirical analysis and in the context of a digital age. This paper presents the first research inside all the agencies that form the Australian National Intelligence Community exploring how they are impacted by big data. Intelligence is often opaque to outsiders, yet understanding the characteristics of good intelligence is important to societies that rely on intelligence agencies for national security. This paper reflects the previously unheard perspectives of members of the agencies that form the Australian National Intelligence Community – where there is a significant empirical gap. Semi-structured interviews with 47 participants explored the impact of big data on intelligence and decision-making in Australia. This paper finds that intelligence must meet the following characteristics, many established in historical literature, in order to be considered good intelligence; (i) timely, (ii) purposeful, (iii) actionable, (iv) accurate, (v) provides value-add for an intended audience, and, (vi) is unbiased. This article explores and unpacks each of these characteristics of good intelligence and finds they remain critical in a big data era. [ABSTRACT FROM AUTHOR]

.Commercial platforms are being increasingly used in classrooms as teaching and learning tools. Beyond shifts in practice to accommodate this, the teacher becomes a tool of the platform – generating and collecting data for commercial entities. It is time to move from commercial platforms working through teachers to influence education, towards working with teachers in the ethical use of educational data. The purpose of this paper is twofold. Firstly, we draw on semi-structured interviews to present an exploratory typology of teacher influencer behaviour. Secondly, we argue that there is potential for teacher influencers to act as advocates. We introduce the conceptual notion of an 'educational data advocate'. We call for Teacher Influencers to be recognised as a source of expertise to understand the implications of the use of data-driven educational technologies. By doing so, a new pedagogical economy that promotes ethics and rights alongside educational and commercial outcomes may be generated. [ABSTRACT FROM AUTHOR]

In Australia, as in other places in the world, we accumulate and curate Big Data – in the public and private spheres; as consumers and citizens; for profit, for proof and for the promises it holds. Yet, data are only ever a partial snapshot of the lives of humans, communities, environments and places. Data has its place, but in order to use data to effect change, we need to understand which questions to ask, which assumptions to suspend, which data to collect and how to interpret them, we need knowledge of the broader context. Taking a systems‐level view of data allows us to ask questions about it as a technical and sense making apparatus, as well as about the consequences of data collection, storage and use. This article advocates for a cybernetic approach to thinking about and using data. Cybernetics can be broadly understood as the study of feedback, communication and control in a system. A cybernetic approach to Big Data means de‐centring data to focus on a broader system of cultural, technological and environmental dimensions. In this approach, the system itself is the core unit of analysis, and also a vantage point or an approach through which to encounter and re/structure such systems. Employing a cybernetic approach allows us to move beyond attempts to order and reorder information, and instead see it as making implicit knowledge explicit, and then knowing that the hard work is what to do with that knowledge. Through this we are able to conceptualise more complex inputs, outputs and interactions, than simply those captured in a dataset. The insights drawn from a particular dataset or datasets, or from a particular model or algorithm (however well parameterised) never represent the whole truth, and a cybernetics framing enables practitioners to say, if that is the case, what now? A cybernetic approach suggests we should preference deeper understanding, not simply more truth. [ABSTRACT FROM AUTHOR]