AI@UN: Navigating the tightrope between innovation and impartiality

The UN is not short of risks. These include the lack of funding or geopolitical blockages in the UN Security Council. AI adds novel risks for the organisation in that it challenges the concept of impartiality – one of the UN’s keystone ideals – and potentially threatens the very modus operandi of the organisation itself.  

The UN’s impartiality will be tested as the UN reacts to the inevitable need to automate reporting, drafting, and other core activities central to its operation. Proprietary and opaque AI systems, as most current platforms are, fall short of the UN’s high benchmark on impartiality. Such systems may shape the ‘thinking’ of the UN Secretariat and, ultimately, influence decisions made by Member States. 

The solution to developing an open-source AI platform is through the contributions of countries, companies, and citizens worldwide. 

The following text outlines conceptual and practical steps to develop AI@UN.

Why is impartiality important for the UN?

The principle of impartiality is the linchpin of the UN’s credibility, ensuring that policy advice remains objective, grounded in evidence, and sensitive to diverse perspectives. 

The principle of bureaucratic impartiality can be traced back to the British civil service, which in many ways inspired the establishment and form of international administration, including the proscribed role of international civil servants and procedures. The founding document of the British civil service was the Northcote-Trevelyan Report of 1854, which introduced professional civil service principles, including impartiality.

The principle of impartiality has been inspired by governments worldwide. This principle is even more critical at the UN, where impartiality among governments could make or break the organisation.

AI and the evolution of digitalisation at the UN

AI is a new but different phase in the long history of using technology in the work of the UN. Before we focus on AI’s differences, the UN’s tech history includes the use of typewriters at the time of the League of Nations in the 1930s, and the use of telegraphs for communication.

Sometimes, like in October 1963, the UN used cutting-edge satellite technology, connecting the UN in New York and the International Telecommunication Union (ITU) in Geneva.

In the 2000s, the use of technology in the UN’s work got new digitalisation momentum centred around two main phases: the shift of data to the cloud in the 2010s and to online meetings in the 2020s.

Shift to the cloud

The first main shift in the UN’s technological evolution occurred in the early 2010s, when UN datasets and archives moved from internal servers to the cloud. It opened the question of how the technical and legal protection of this data could be guaranteed.

Technically, once data moved outside the UN’s physical premises, it became a matter of protection for providers of cloud services such as Amazon, Microsoft, and Google.

Legally, the question of diplomatic immunity came into sharper focus: how to ensure the the legal obligation of tech companies to protect the immunity of data and documents stored by international organisations.

By providing the service of “digital embassies” with data stored in Luxembourg on servers run by private companies in accordance with international diplomatic law that the nation’s authorities enforce, Luxembourg identified a business opportunity for such an ambiguous situation around data and diplomatic immunity. Estonia and the ICRC (International Committee of the Red Cross) thus established ‘digital embasies’ in Luxembourg.

Protecting UN data will receive new relevance as tech companies rush to get more data to train their AI foundational models.

Shift to online meetings

The second main digital shift at the UN in recent years happened during the COVID pandemic, when meetings moved from UN buildings to online platforms. Again, the question of legal protections was raised.

For physical meetings the UN owns and manages the facilities used for physical meetings in New York, Geneva, Vienna, Nairobi, and other locations. Through international conventions and headquarters agreements, these UN sites provide the necessary security and immunity. Ultimately, the UN venues ensure data protection, confidentiality, and other locational guarantees so all Member States can meet on a secure and impartial footing. 

But the involvement of privately-owned platforms, such as Zoom and Microsoft Team, raised concerns about the status of online diplomatic venues, analogous to traditional ones. In some cases, certain member states could not access such platforms due to sanction regimes. As any restriction in accessing online meetings threatens UN impartiality, the UN secretariat was obliged to work on streaming bypasses for countries that could not use certain commercial platforms.  

As the world of diplomacy returned to physical meetings, there has been less urgency in defining the legal status of online diplomatic meetings.

Yet, this issue remains to be settled before future crises emerge. One solution was to develop a UN online meeting platform as a “public good” contribution from companies, countries and citizens worldwide. This open-source platform was envisaged as a means of inclusive and effective diplomatic meetings and overall global governance.   

Why is AI different from previous technological innovations at the UN?

Unlike previous technologies, from typewriters to Zoom meetings, AI can actively frame arguments and outcomes in UN policy debates and negotiations. As ‘off-the-shelf’ AI proprietary systems carry the bias of data and the algorithm on which it is developed and come with transparency limitations and challenges, a reliance on proprietary AI will open inevitable questions about the impartiality of such systems. Ensuring impartiality would require transparency and explainability of the full AI cycle from the data on which foundational models are based to assigning ‘weights’ to various segments of AI systems.

We, the peoples, the first line of the UN Charter, should guide the development of artificial intelligence (AI) at the UN. Contributions of countries, companies, and communities worldwide to AI@UN could bolster the high potential of AI to support the UN’s missions of upholding global peace, advancing development, and protecting human rights.

An inclusive approach to AI development is key for upholding the principle of impartiality, a pillar of the UN. 

The AI@UN has two main goals:

• support policy discussions on the sustainable AI transformation of the UN ecosystem; and
• inspire the contributions of AI models and agents by member states and other actors.

As a starting point, we would like to propose the following guiding principles for the development and deployment of AI models, modules, and agents at the UN: 

1. Open Source: Abiding by the open-source community’s principles, traditions, and practices. Openness and transparency should apply to all phases and aspects of the AI life-cycle, including curating data and knowledge for AI systems, selecting parameters and assigning weights to develop foundational models, vector databases, knowledge graphs, and other segments of AI systems. 

2. Modular: Developing self-contained modules according to shared standards and parameters. AI@UN should start with AI agents and modules for core UN activities and operations.

3. Public Good: ‘Walking the talk’ of public good by using AI to codify UN knowledge as a public good to be used by countries, communities, and citizens worldwide. By doing so, the UN would inspire the AI-enabled codification of various knowledge sources, including ancient texts and oral culture, as the common heritage of humankind.   

4. Inclusive: Enabling member states, companies, and academia to contribute, by their capacities and resources, to the technical, knowledge, and usability aspects of AI@UN. A modular approach to AI@UN would require a wide range of knowledge contributions beyond technical ones.  

5. Multilingual: Representing a wide range of linguistic and cultural traditions. The special focus will be on harvesting the knowledge and wisdom available in oral traditions not available in the written corpus of books and publications.

6. Diverse: Ensuring inputs from a wide range of professional, generational, cultural, and religious perspectives. While AI@UN should aim to identify convergences between different views and approaches, diversities should not be suppressed by the ‘least common denominator’ approach inferred in AI. Diversity should be built in through the transparent traceability of sources behind AI-generated outputs. 

7. Accessible: Adhering to the highest standards for accessibility, in particular for people with disabilities. AI@UN must increase the participation of people with disabilities in UN activities, from meetings to practical projects. Simple solutions and low-bandwidth demand should make the system affordable for all. 

8. Interoperable: Addressing a problem of organisational silos in managing knowledge and data within the UN system. Interoperability should be facilitated by knowledge ontologies and taxonomies, data curation, and shared technical standards.

9. Professionale: Following the highest industry and ethical standards of planning, coding, and deploying software applications. This will be achieved by testing, evaluating, and submitting AI solutions to a peer-review process. The main focus will be maximising the reliable development of AI solutions to directly impact human lives and well-being. 

10. Explainable: Tracing every AI-generated artefact, such as a report or analysis, to sources used by AI inference, including texts, images and sound recording. Explainability and traceability would ensure transparency and impartiality of AI@UN systems.

11. Protecting Data and Knowledge: Achieving the highest level in protecting data, knowledge and other inputs into AI systems. Explainability and traceability will be critical for protecting data and knowledge used by the AI@UN system.  

12. Secure: Guaranting the highest possible level of security and reliability of AI@UN. Open source, red-teaming, and other approaches will ensure that the systems are protected by having as many ‘eyes’ as possible to test and evaluate AI code and algorithms. AI communities will be encouraged to contribute to red-teaming and other tests of the AI@UN system.

13. Sustainable: Realisation of SDGs and Agenda 2030 through three main approaches: firstly, ensuring that SDGs receive higher weights in developing AI models and tools; secondly, the AI systems themselves should be sustainable through, for example, sharing the code, building resources, and providing proper documentations and development trails; thirdly, AI solutions should be developed and deployed with environmental sustainability in mind.

14. Capacity: By developing an AI system, the UN should develop its own and wider AI capacities. Capacity development should be: a) holistic, involving the UN Secretariat, representatives of Member States, and other communities involved in UN activities; and b) comprehensive, covering a wide range of AI capacities from a basic understanding of AI to high-end technical skills. 

15. Future-Proofing: Planning and deploying systems dealing with future technological trends. Experience and expertise gathered around AI@UN should be used to deal with other emerging technologies, such as augmented/virtual reality and quantum computing. 

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The call to action is clear: by leveraging the transformative power of AI, the UN can turn an ongoing challenge into a watershed moment for global governance. The UN’s commitment to innovation and adaptability will test its resilience and underscore its enduring relevance and leadership in charting the course of human progress.

Opportunities in crisis

AI transformation will inevitably trigger tensions due to its impact on deeper layers of the way the UN functions. Likely opposition based on human fear and attachments to the status quo should be openly addressed and reframed around opportunities that AI transformation will open on individual and institutional levels.  

AI transition offers numerous opportunities:

First, AI can help small and developing countries to participate in more informed and impactful ways in the work of the UN. AI can compensate for their small diplomatic missions and services, which must follow the same diplomatic dynamic as big systems. AI will reduce current AI asymmetry.

Second, AI can help the UN Secretariat to refocus time and resources and spend less time on traditional paperwork, like preparing reports, to allow more work on the ground in Member States where their help is critical.

Next steps

Embarking on this journey towards integrating AI into the UN’s operations is not merely a step but a leap into the future—one that demands boldness, a cooperative spirit, and an unwavering dedication to the ideals that have anchored the UN since its inception.

The potential for AI to bolster the UN’s mission in upholding global peace, advancing development, and championing human rights is immense.

In fact, the need to adopt an open-source AI framework exceeds the need for technological innovation. The UN will be able to evolve, take the lead, and remain relevant in a rapidly changing global landscape by adopting an open approach to AI.

By leveraging the transformative power of AI, the UN can turn a looming challenge into a watershed moment, ensuring the organisation’s relevance and leadership in charting the course of human progress for all.