The world of diplomacy is rich in data. The United Nations and other international forums have detailed records of debates, speeches and negotiations going back decades. Then there are databases recording demographics, trade, finance, spending and common declarations made by international organisations. Beyond these forums, important sources include records of human rights violations and other data used by international justice organisations.

Future Horizons:

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5-yearhorizon

Higher education establishments broaden skill sets for scientists and diplomats

Efforts to build capacity for computational diplomacy bear fruit in the form of an increased range of courses and training programmes across relevant disciplines, and in understanding of how disciplines can be integrated as mutually supportive frameworks. Predictive modelling improves at the sub-national level with AI systems providing natural language translations of model outputs.

10-yearhorizon

Computational techniques uncover new insights into multilateralism

Computational diplomacy leverages advances in natural-language processing, network science and time-series analysis to uncover new insights into the structure and dynamics of multilateralism. By analysing diplomatic discourse, institutional networks and temporal patterns, the field will enable data-driven operationalisation of the study of cooperation, influence and legitimacy. This will support the emergence of a dynamic, systems-oriented understanding of global governance.

25-yearhorizon

Computational diplomacy reshapes international relations as a science

The successes with text mining and other data-driven applications allow experts to create a robust theory of diplomacy that makes testable predictions and creates useful frameworks for diplomatic interactions and for improving understanding of international relations. Predictive forecasts become a ubiquitous tool for policy-makers, who will know in advance the effect of their actions and how they may inflame or cool tensions.

The cost of processing this data means it has not been well used to inform the process of diplomacy, to amplify cooperation and to improve outcomes. Nevertheless, organisations like the UN, the World Bank and other policy-makers are working hard to integrate quantitative methods into their organisations, which will accelerate the practice of computational diplomacy and its use of big data, machine learning and computational thinking.

There is much low-hanging fruit here. The networks of actors on the international stage and their institutional relationships are already beginning to be mapped,^1,2,3 giving a deeper understanding of the connections that can influence negotiations. Also being mined for insight are resolutions adopted by various international organisations. Relevant examples include the United Nations General Assembly and Security Council resolutions histories,⁴ sponsorship data⁵ and debate themes, as well as the resolutions adopted by the World Health Organization.^6,7 This work is beginning to deliver quantitative results, a crucial step for reproducibility.^8,9,10

Much more can be done. Combining a data-driven approach with computational modelling can facilitate a more fundamental understanding of how multilateral governance systems work and how they can be improved, for example.¹¹ The growing use of AI is likely to have a significant impact here,¹² but developing the multidisciplinary expertise that can manage and exploit diplomatic processes is a significant challenge.