Collective identity and experience: an AI order for the common good
Self‑Explaining AI democratizes governance, challenges dominance, fosters global cooperation.
In 2040, Self-Explaining AI is significantly shaping global AI development and its governance. These systems surpass Explainable AI in that their decision-making processes are not only transparent in themselves, but also communicated in a comprehensible, contextualised and individualised way. This facilitates low-threshold participation by the population in political, economic and technological decision-making.
Self-Explaining AI translates highly complex contexts into easy-to-understand, interactive formats. It adapts its explanations to the knowledge and interests of the users. This not only enables citizens to be better informed, but also to actively participate in political and regulatory processes – be it through automated consultation procedures or digital voting. Government agencies use AI to efficiently analyse feedback from the population. And thanks to AI, political institutions can make more transparent and comprehensible decisions. This not only strengthens trust in technology and governance but also changes the political dynamic: access to knowledge, including on political and regulatory processes, is now open to a broader social base.
Self-Explaining AI was published in 2035 as an open source project by an alliance of research institutions, tech companies and civil society organisations from India, Brazil and South Africa. This changed the global balance of power. It gave smaller nations and emerging players access to powerful AI tools, while established technology corporations from the US and China, which had previously benefited from proprietary systems, saw their supremacy jeopardised.
The conflicting interests of countries in favour of open systems and those that rely on proprietary technologies gave rise to political tensions. These conflicts, as well as public pressure from global civil society for greater transparency and participation, culminated in a reform of international AI governance. With the creation of the Global AI Governance Forum (GAIGF), a new UN multi-stakeholder forum now coordinates global AI governance in 2040 and continues to coordinate existing frameworks such as the GDC. Governments, technology companies, the scientific and academic community and civil society are all equally represented in GAIGF. Developed from existing international cooperation and standardisation processes, GAIGF aims to coordinate the various concerns and interests in a more inclusive and transparent way. However, harmonising regional differences and members’ divergent economic interests remains a challenge. The EU is pushing for strict minimum ethical standards, while China and Russia are committed to technological pragmatism. At the same time, the big technology corporations are trying to mitigate new transparency requirements for their proprietary AI systems in order to protect their business model.
For the first time, civil society too is now fully involved in setting global technical standards. Thanks to the ability of Self-Explaining AI to simulate and explain the impacts of technical standards and regulations, these can now be understood and evaluated even by non-specialists. Online citizen participation processes enable civil society to play a role in shaping developments, with technology companies being encouraged to act more transparently and with a greater focus on the common good. Many AI applications are becoming public goods through a combination of government funding, pressure from civil society and the prevalence of open-source solutions.
In 2040, the UN is setting out its vision for globally just AI governance, in which all AI applications developed for the common good are recognised as public goods. With support from the UN Permanent Forum on Indigenous Issues (UNPFII), AI is gradually integrating indigenous knowledge systems and culturally specific values. This traditional knowledge surrounding collaborative and sustainable governance of public goods will in future guide the work of the UN. In parallel, we are seeing the emergence of technology cooperatives – collaborative platforms based on democratic principles that promote responsible access to AI resources and knowledge to support social justice and sustainable development. This new interplay between commercial and community-based structures is shaping the AI landscape in many regions of the world, albeit in varying forms.
In the UN system, wealthy countries have committed to granting poorer member states access to AI infrastructures through subsidies or ‘infrastructure-as-a-service’ models. This enables processing power and data to be used efficiently, but also creates new dependencies in the Global South. However, many emerging economies are able to use this access to establish themselves as key players in AI development and create new AI ecosystems. As a result, income differences between countries are shrinking and AI investments globally are being distributed more equitably. This is leading to a comprehensive shift in economic dynamics and to more stable societies.
Global digital infrastructure presents a hybrid picture in 2040. Self-Explaining AI has democratised the technological knowledge required to build and maintain data infrastructures. Whereas major technology corporations continue to operate centralised data centres, less tech-savvy local communities are also able to develop and manage their own data processing capacity. A similar pattern can be seen in the energy supply, where municipal energy cooperatives use Self-Explanatory AI to manage local renewable energies efficiently, whereas technology corporations rely on centralised, industrial energy solutions. The AI-supported optimisation of resource exploration and resource management also promotes the sustainable use of raw materials. The use of highly efficient AI algorithms and low-resource programming languages also helps to reduce energy consumption. These developments are taking on increasing significance as climate tipping points approach.
Self-Explaining AI is also being used to support governments, NGOs and international organisations in developing de-escalating measures in complex international conflicts. AI-supported systems are increasingly taking on tasks in virtual diplomacy and preventive conflict resolution. Although offensive military AI applications are outlawed internationally, their use is still permitted in areas such as cyber defence, logistics and crisis management.
The EU has also introduced a Technology Generation Contract, which gives citizens the chance to vote on the fundamental principles of AI use every five years. Some regions are experimenting with similar models, while others are looking towards more controlled participation formats. The different approaches to technology governance continue to reflect ongoing regional differences.
Alongside the diverse and innovative applications of Self-Explaining AI, new risks are also emerging as states with authoritarian tendencies attempt to manipulate Self-Explaining AI. Instead of leveraging the potential of AI for public participation, they specifically use AI-supported disinformation to influence public opinion and secure geopolitical interests. These strategies over AI use undermine the integrity of democratic processes and strengthen authoritarian power structures.
WILD CARD: AI as a legal representative of natural resources
In 2040, international bodies are trialling the use of AI to represent natural resources such as rivers, forests and ecosystems as legal entities. The purpose of AI-controlled ‘legal representatives’ is to independently promote the interests and protection of resources and influence policy-making and legal decision-making. The aim of the experiment is to give natural entities an independent legal voice with a view to improving the way the requirements of environmental protection and climate action are addressed. The introduction of these AI legal representatives triggers intense debate about the role of technology in legislation and the administration of justice. While environmentalists celebrate the concept as revolutionary progress for nature conservation, critics see the danger of a technocratic distortion of political decisions.