From paradox to principles: where next for scientific advice to governments?

Scientific advice to governments has never been in greater demand; nor has it been more contested. From climate change to cyber-security, poverty to pandemics, food technologies to fracking, the questions being asked of scientists, engineers and other experts by policymakers, the media and the wider public continue to multiply and increase in complexity. At the same time, the authority and legitimacy of experts are under increasing scrutiny. This thematic article collection (‘special issue’) brings together perspectives on the theory, practice and politics of scientific advice that build on the conclusions of the landmark conference in Auckland in August 2014, which led to the creation of the International Network for Government Science Advice (INGSA). We hope that new papers will continue to be added to this collection over the next year and beyond, making it a living, fully open access repository for new scholarship and policy thinking—and an important contribution to the emerging science and art of scientific advice

“Excellence R Us”: university research and the fetishisation of excellence

The rhetoric of “excellence” is pervasive across the academy. It is used to refer to research outputs as well as researchers, theory and education, individuals and organisations, from art history to zoology. But does “excellence” actually mean anything? Does this pervasive narrative of “excellence” do any good? Drawing on a range of sources we interrogate “excellence” as a concept and find that it has no intrinsic meaning in academia. Rather it functions as a linguistic interchange mechanism. To investigate whether this linguistic function is useful we examine how the rhetoric of excellence combines with narratives of scarcity and competition to show that the hypercompetition that arises from the performance of “excellence” is completely at odds with the qualities of good research. We trace the roots of issues in reproducibility, fraud, and homophily to this rhetoric. But we also show that this rhetoric is an internal, and not primarily an external, imposition. We conclude by proposing an alternative rhetoric based on soundness and capacity-building. In the final analysis, it turns out that that “excellence” is not excellent. Used in its current unqualified form it is a pernicious and dangerous rhetoric that undermines the very foundations of good research and scholarship

Ethical principles in machine learning and artificial intelligence: cases from the field and possible ways forward

Decision-making on numerous aspects of our daily lives is being outsourced to machine-learning algorithms and artificial intelligence (AI), motivated by speed and efficiency in the decision process. Machine learning (ML) approaches - one of the typologies of algorithms underpinning artificial intelligence - are typically developed as black boxes. The implication is that ML code scripts are rarely scrutinised; interpretability is usually sacrificed in favour of usability and effectiveness. Room for improvement in practices associated with programme development have also been flagged along other dimensions, including inter alia fairness, accuracy, accountability, and transparency. In this contribution, the production of guidelines and dedicated documents around these themes is discussed. The following applications of AI-driven decision making are outlined: a) Risk assessment in the criminal justice system, and b) autonomous vehicles, highlighting points of friction across ethical principles. Possible ways forward towards the implementation of governance on AI are finally examined

Tales of future weather

Society is vulnerable to extreme weather events and, by extension, to human impacts on future events. As climate changes weather patterns will change. The search is on for more effective methodologies to aid decision-makers both in mitigation to avoid climate change and in adaptation to changes. The traditional approach uses ensembles of climate model simulations, statistical bias correction, downscaling to the spatial and temporal scales relevant to decision-makers, and then translation into quantities of interest. The veracity of this approach cannot be tested, and it faces in-principle challenges. Alternatively, numerical weather prediction models in a hypothetical climate setting can provide tailored narratives for high-resolution simulations of high-impact weather in a future climate. This 'tales of future weather' approach will aid in the interpretation of lower-resolution simulations. Arguably, it potentially provides complementary, more realistic and more physically consistent pictures of what future weather might look like

Ethical Issues in Engineering Models: An Operations Researcher’s Reflections

This article starts with an overview of the author’s personal involvement—as an Operations Research consultant—in several engineering case-studies that may raise ethical questions; e.g., case-studies on nuclear waste, water management, sustainable ecology, military tactics, and animal welfare. All these case studies employ computer simulation models. In general, models are meant to solve practical problems, which may have ethical implications for the various stakeholders; namely, the modelers, the clients, and the public at large. The article further presents an overview of codes of ethics in a variety of disciples. It discusses the role of mathematical models, focusing on the validation of these models’ assumptions. Documentation of these model assumptions needs special attention. Some ethical norms and values may be quantified through the model’s multiple performance measures, which might be optimized. The uncertainty about the validity of the model leads to risk or uncertainty analysis and to a search for robust models. Ethical questions may be pressing in military models, including war games. However, computer games and the related experimental economics may also provide a special tool to study ethical issues. Finally, the article briefly discusses whistleblowing. Its many references to publications and websites enable further study of ethical issues in modeling

Storylines: an alternative approach to representing uncertainty in physical aspects of climate change

As climate change research becomes increasingly applied, the need for actionable information is growing rapidly. A key aspect of this requirement is the representation of uncertainties. The conventional approach to representing uncertainty in physical aspects of climate change is probabilistic, based on ensembles of climate model simulations. In the face of deep uncertainties, the known limitations of this approach are becoming increasingly apparent. An alternative is thus emerging which may be called a ‘storyline’ approach. We define a storyline as a physically self-consistent unfolding of past events, or of plausible future events or pathways. No a priori probability of the storyline is assessed; emphasis is placed instead on understanding the driving factors involved, and the plausibility of those factors. We introduce a typology of four reasons for using storylines to represent uncertainty in physical aspects of climate change: (i) improving risk awareness by framing risk in an event-oriented rather than a probabilistic manner, which corresponds more directly to how people perceive and respond to risk; (ii) strengthening decision-making by allowing one to work backward from a particular vulnerability or decision point, combining climate change information with other relevant factors to address compound risk and develop appropriate stress tests; (iii) providing a physical basis for partitioning uncertainty, thereby allowing the use of more credible regional models in a conditioned manner and (iv) exploring the boundaries of plausibility, thereby guarding against false precision and surprise. Storylines also offer a powerful way of linking physical with human aspects of climate change

Sustainable Urban Systems: Co-design and Framing for Transformation

Rapid urbanisation generates risks and opportunities for sustainable development. Urban policy and decision makers are challenged by the complexity of cities as social–ecological–technical systems. Consequently there is an increasing need for collaborative knowledge development that supports a whole-of-system view, and transformational change at multiple scales. Such holistic urban approaches are rare in practice. A co-design process involving researchers, practitioners and other stakeholders, has progressed such an approach in the Australian context, aiming to also contribute to international knowledge development and sharing. This process has generated three outputs: (1) a shared framework to support more systematic knowledge development and use, (2) identification of barriers that create a gap between stated urban goals and actual practice, and (3) identification of strategic focal areas to address this gap. Developing integrated strategies at broader urban scales is seen as the most pressing need. The knowledge framework adopts a systems perspective that incorporates the many urban trade-offs and synergies revealed by a systems view. Broader implications are drawn for policy and decision makers, for researchers and for a shared forward agenda