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The use of algorithms and automation of public services is not new, but in recent years there has been a step change in processing power and a decrease in the price of these technologies, which means we are seeing more widespread use. These advances are reframing our perception of what matters in ways that impact the ethical dimensions of day-to-day life. In turn, these changes challenge long-standing assumptions about public service ethics and how it is taught. In this multidisciplinary authored paper, we argue that public service leaders must be attentive to ethical questions that converge around adopting "data-driven" techniques, including algorithmic decision-making. Algorithmic and technology focused ethics question assumptions about the current deficits within public service ethics pedagogy in public service programs and university programs and the future direction of the discipline. To do so raises longstanding but neglected questions about the public services' role in the state and recovering what Rohr refers to as the 'ethics of the office.' This, we argue, will have implications for teaching public service ethics.

Recent negotiations of 'data' in schools place focus on student assessment and NAPLAN. However, with the rise in artificial intelligence (AI) underpinning educational technology, there is a need to shift focus towards the value of teachers' digital data. By doing so, the broader debate surrounding the implications of these technologies and rights within the classroom as a workplace becomes more apparent to practitioners and educational researchers. Drawing on the Australian Human Rights Commission's "Human Rights and Technology final report," this conceptual paper focusses on teachers' rights alongside emerging technologies that use or provide predictive analytics or artificial intelligence, also called 'personalisation'. The lens of Postdigital positionality guides the discussion. Three potential consequences are presented as provocations: (1) What might happen if emerging technology uses teachers' digital data that represent current societal inequality? (2) What might happen if insights provided by such technology are inaccurate, insufficient, or unrepresentative of our teachers? (3) What might happen if the design of the AI system itself is discriminatory? This conceptual paper argues for increased discourse about technologies that use or provide predictive analytics complemented by considering potential consequences associated with algorithmic bias.

As we move further into the digital age, the acquisition of digital literacy (DL) and computational thinking (CT) skills is emerging internationally as an essential goal for students in contemporary school curricula. As the world becomes more uncertain and volatile due to impacts of artificial intelligence (AI), international unrest, climate change, global economic instability and unforeseen catastrophes such as the Coronavirus (COVID-19) pandemic, it is necessary to review, revise and refine school education curricula and policies. The issue of what is essential for students to learn, and how they learn it, is of growing importance to international organisations such as the Organisation for Economic Co-operation and Development (OECD) and the United Nations Educational, Scientific and Cultural Organisation (UNESCO) and is emerging as a significant driver for educational reform across the globe. The growing prominence of CT and DL skills across many industry sectors has prompted recent changes to international assessment frameworks such as the Programme for International Student Assessment (PISA) and the Trends in International Mathematics and Science Study (TIMSS). This paper will briefly discuss specific examples of alternative approaches to addressing CT in national curricula for the compulsory years of schooling and explain how CT has been adopted as a driver for mathematics curriculum change in Australia.

In the recent Australian 2021 census, the socio-technical construct of algorithmically driven decision-making processes made LGBTQI+ data as a category of diversity, inclusion and belonging an absent presence. In this paper, we position the notion of 'data justice' in relation to the entrenchment of inequalities and exclusion of LGBTQI+ lives and consider the implications of LGBTQI+ data being missing in action. As we look at the notion of 'data justice', we consider five critical socio-technical imaginaries with different kinds of data to think through the implications of technical democracy, data justice and post-automation. Finally, we consider the imaginary of citizenship when LGBTQI+ data is habitually missing in action from systematic power integrated into forms of governance. This paper positions 'data' not as a static 'object or process' but as a dynamic ecology that carries with it a multi-faceted set of coded meanings requiring constant review and reconsideration.

The Chameleon Educational Policy Reforms' (CEPR) 25th anniversary was celebrated at the Global General Assembly with the 2075 Decennial Analysis of Schooling (DecAS) announcement of the attainment of a benefit-cost ratio of >1.0. The attainment of a global positive net value of education is directly linked to the educational reforms established to 'provide the right access to the right education for all people' (CEPR, 2050). The Chameleon reforms, informed by The Algorithm, produce policies that instantly adapt to the learning environment and needs of students. Barriers that effect students' learning are removed, in stark contrast to historic processes that viewed students as the barrier to be removed from learning environments. The case studies presented in this paper are guided by three questions: 'Where are we now?', 'How did we get here?', and 'Are we there yet?'. Questioning the 'here and now', directs a look back from educational engagement currently governed by the CEPR to key moments and movements in the attainment of past grand policy announcements that no child be left behind to live in poverty. And 'yet', leads to critical consideration of the ongoing engagement with The Algorithm. Artifacts detailing the 2045 commencement of annual donations from the richest two percent to fully fund global education remain sealed. The results of the annual donations are, however, publicly available; and some would say exploited (Gerve, 2072). Achieving self-sustainable economic cost-benefit status for the CEPR may release the Donators from those agreements and untether society from the Donators.