A ground-breaking research project from Chatham House, supported by The Power of Nutrition, is exploring the business case for tackling undernutrition, micronutrient deficiencies and overnutrition. Companies across all sectors hold huge, transformative power to save countless lives and transform their own financial prospects. To act, they need more compelling evidence of the potential for targeted investments and strategies to promote better nutrition and create healthier, more productive workforces and consumers.

At this workshop, Chatham House will engage business decision-makers in a scenario exercise that explores different nutrition futures and their commercial prospects in each before examining what different strategies business can pursue to maximize future profitability through investments in nutrition.

Attendance at this event is by invitation only.

Complex systems models have played a significant role in informing and shaping the public health measures adopted by governments in the context of the COVID-19 pandemic. For instance, modelling carried out by a team at Imperial College London is widely reported to have driven the approach in the UK from a strategy of mitigation to one of suppression.

Complex systems modelling will increasingly feed into policymaking by predicting a range of potential correlations, results and outcomes based on a set of parameters, assumptions, data and pre-defined interactions. It is already instrumental in developing risk mitigation and resilience measures to address and prepare for existential crises such as pandemics, prospects of a nuclear war, as well as climate change.

The human factor

In the end, model-driven approaches must stand up to the test of real-life data. Modelling for policymaking must take into account a number of caveats and limitations. Models are developed to help answer specific questions, and their predictions will depend on the hypotheses and definitions set by the modellers, which are subject to their individual and collective biases and assumptions. For instance, the models developed by Imperial College came with the caveated assumption that a policy of social distancing for people over 70 will have a 75 per cent compliance rate. This assumption is based on the modellers’ own perceptions of demographics and society, and may not reflect all societal factors that could impact this compliance rate in real life, such as gender, age, ethnicity, genetic diversity, economic stability, as well as access to food, supplies and healthcare. This is why modelling benefits from a cognitively diverse team who bring a wide range of knowledge and understanding to the early creation of a model.

The potential of artificial intelligence

Machine learning, or artificial intelligence (AI), has the potential to advance the capacity and accuracy of modelling techniques by identifying new patterns and interactions, and overcoming some of the limitations resulting from human assumptions and bias. Yet, increasing reliance on these techniques raises the issue of explainability. Policymakers need to be fully aware and understand the model, assumptions and input data behind any predictions and must be able to communicate this aspect of modelling in order to uphold democratic accountability and transparency in public decision-making.

In addition, models using machine learning techniques require extensive amounts of data, which must also be of high quality and as free from bias as possible to ensure accuracy and address the issues at stake. Although technology may be used in the process (i.e. automated extraction and processing of information with big data), data is ultimately created, collected, aggregated and analysed by and for human users. Datasets will reflect the individual and collective biases and assumptions of those creating, collecting, processing and analysing this data. Algorithmic bias is inevitable, and it is essential that policy- and decision-makers are fully aware of how reliable the systems are, as well as their potential social implications.

The age of distrust

Increasing use of emerging technologies for data- and evidence-based policymaking is taking place, paradoxically, in an era of growing mistrust towards expertise and experts, as infamously surmised by Michael Gove. Policymakers and subject-matter experts have faced increased public scrutiny of their findings and the resultant policies that they have been used to justify.

This distrust and scepticism within public discourse has only been fuelled by an ever-increasing availability of diffuse sources of information, not all of which are verifiable and robust. This has caused tension between experts, policymakers and public, which has led to conflicts and uncertainty over what data and predictions can be trusted, and to what degree. This dynamic is exacerbated when considering that certain individuals may purposefully misappropriate, or simply misinterpret, data to support their argument or policies. Politicians are presently considered the least trusted professionals by the UK public, highlighting the importance of better and more effective communication between the scientific community, policymakers and the populations affected by policy decisions.

Acknowledging limitations

While measures can and should be built in to improve the transparency and robustness of scientific models in order to counteract these common criticisms, it is important to acknowledge that there are limitations to the steps that can be taken. This is particularly the case when dealing with predictions of future events, which inherently involve degrees of uncertainty that cannot be fully accounted for by human or machine. As a result, if not carefully considered and communicated, the increased use of complex modelling in policymaking holds the potential to undermine and obfuscate the policymaking process, which may contribute towards significant mistakes being made, increased uncertainty, lack of trust in the models and in the political process and further disaffection of citizens.

The potential contribution of complexity modelling to the work of policymakers is undeniable. However, it is imperative to appreciate the inner workings and limitations of these models, such as the biases that underpin their functioning and the uncertainties that they will not be fully capable of accounting for, in spite of their immense power. They must be tested against the data, again and again, as new information becomes available or there is a risk of scientific models becoming embroiled in partisan politicization and potentially weaponized for political purposes. It is therefore important not to consider these models as oracles, but instead as one of many contributions to the process of policymaking.

In 2017 Trump expressed pity for the ‘beautiful babies’ killed in a gas attack on Khan Shaykhun in Syria before launching airstrikes against President Assad's regime. Images of suffering children in world politics are often used as a synecdoche for a broader conflict or disaster. Injured, suffering, or dead; the ways in which images of children circulate in global public discourse must be critically examined to uncover the assumptions that operate in these environments. This article explores reactions to images of children by representatives and leaders of states to trace the interconnected affective and political dimensions of these images. In contrast to attending to the expected empathetic responses prompted by images of children, this article particularly focuses on when such images prompt bellicose foreign policy decision-making. In doing this, the article forwards a way of thinking about images as contentious affective objects in international relations. The ways in which images of children's bodies and suffering are strategically deployed by politicians deserves closer scrutiny to uncover the visual politics of childhood inherent in these moments of international politics and policy-making.

In 2017 Trump expressed pity for the ‘beautiful babies’ killed in a gas attack on Khan Shaykhun in Syria before launching airstrikes against President Assad's regime. Images of suffering children in world politics are often used as a synecdoche for a broader conflict or disaster. Injured, suffering, or dead; the ways in which images of children circulate in global public discourse must be critically examined to uncover the assumptions that operate in these environments. This article explores reactions to images of children by representatives and leaders of states to trace the interconnected affective and political dimensions of these images. In contrast to attending to the expected empathetic responses prompted by images of children, this article particularly focuses on when such images prompt bellicose foreign policy decision-making. In doing this, the article forwards a way of thinking about images as contentious affective objects in international relations. The ways in which images of children's bodies and suffering are strategically deployed by politicians deserves closer scrutiny to uncover the visual politics of childhood inherent in these moments of international politics and policy-making.

A ground-breaking research project from Chatham House, supported by The Power of Nutrition, is exploring the business case for tackling undernutrition, micronutrient deficiencies and overnutrition. Companies across all sectors hold huge, transformative power to save countless lives and transform their own financial prospects. To act, they need more compelling evidence of the potential for targeted investments and strategies to promote better nutrition and create healthier, more productive workforces and consumers.

At this workshop, Chatham House will engage business decision-makers in a scenario exercise that explores different nutrition futures and their commercial prospects in each before examining what different strategies business can pursue to maximize future profitability through investments in nutrition.

Attendance at this event is by invitation only.

This meeting formed part of a programme of work which investigates the role of negative emissions technologies (NETs) in achieving the Paris Agreement climate targets. Previous meetings held in London and Brussels have looked at integrating negative emissions into EU policy-making, the implications and degree to which NETs, and in particular bioenergy with carbon capture storage (BECCS), can be an effective climate mitigation tool. This meeting focused on the possible deployment pathways of NETs and alternatives to BECCS for the US in particular, in the context of geographical constraints and socioenvironmental implications, the role of the private sector, and appropriate governance and finance mechanisms. 

The Asia-Pacific region continues to increase in geopolitical and geoeconomic importance. The rise of China and tensions with the US are affecting bilateral relationships and traditional alliances in the region. Whether seen from the perspective of the Quad – Australia, India, Japan and the US – or the Indo-Pacific concept embraced by a wide range of countries but with no shared consensus on scope and objectives or with ASEAN who insists on the importance of its own centrality, the region is redefining and reconceptualising itself.

With a diverse range of initiatives – including the Regional Comprehensive Economic Partnership (RCEP) and Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) – there are a plethora of regional agreements and institutional groupings that add further complexity.

As the Bretton Woods architecture continues to be dominated by Western powers, China is also spearheading parallel governance initiatives such as the Asian Infrastructure Investment Bank (AIIB), the Belt and Road Initiative and the Shanghai Cooperation Organization (SCO) as a means of enhancing its geopolitical and geoeconomic influence.

This one-day conference will focus on how such networks and alliances have been built, and sustained, in the Asia-Pacific region. In order to understand how new regional initiatives might open up opportunities for new forms of international cooperation, the conference will focus on the themes of cyber-technology and innovation, sustainable development and mitigating the impacts of climate change and new infrastructure initiatives. It will assess whether there is a zero-sum conflict between competing networks and agendas or whether a common approach can be developed.