Culture influences reasoning. People’s choices, including conflict resolution and decision-making, are rooted in their environment and lived experiences. Therefore, creating global AI governance systems that can take culturally influenced reasoning into account is crucial for creating effective and sustainable AI systems for citizens and policy-makers and building fertile ground for AI governance.
Influences of Culture on AI ethics and governance
The societal implications of AI are a contributing factor towards raising the awareness of governments of the need to collaborate on an international framework for AI governance. There exist over 160 documents from around the world aiming to contribute towards the development of ethical principles and guidelines for AI. AI regulation around the world is fragmented with moral pluralism and cultural diversity. Therefore, to create globally compatible AI Governance, substantial and coordinated efforts are necessary.
Major issues in this subject include the mistrust among cultures and the practical challenges of coordination across locations. Looking at ‘moral decision-making’ can give us a better understanding of the implications of cultural difference issues. Psychological studies show that individuals are not strictly utilitarian in moral reasoning due to personal values and cultural standards – answers to the trolley problem being one example. By contrast, cultural products such as stories, religious texts, and folktales provide a reliable source of data for cultural modelling. These cultural products, formed over generations, provide historical memory, a moral compass, and a backbone for decision making. Therefore, considering cultures can help policy-makers understand how different groups might react to new regulations and help negotiators find common ground. Currently, there is an increasing need for global governance of AI and frameworks. The cultural differences among nations and regions present a unique set of challenges, especially when aligning core ethical principles. An examination of historical influences that inform current societal thinking may contribute to a way forward, and this has to be done while respecting diverse cultural perspectives and priorities.
Case Study: Europe & China
One example of historical-cultural differences in AI resides with China and Europe as conglomerates. They both regularly discuss the aspects of privacy, safety, fairness, robustness, and transparency; however, their viewpoints have marked differences.
European roots stemming from the Enlightenment period and various revolutions have grown into a rights-based, protecting-individuals-from-harm mentality. In Europe, based on the General Data Protection Regulation (GDPR), privacy involves the protection of an individual’s personal data from both private-commercial entities and the state. Chinese data privacy guidelines, historically influenced by the Confucian value system, have developed uniquely into a hierarchical structure of shared social responsibility and a community-based, state-run focus. According to the Chinese guidelines, data is protected from private companies and other malicious agents. But, the state has absolute control over citizens’ personal data, something that would be very difficult to incorporate in a European state. While Europe emphasises fairness and diversity by factoring in gender, ethnicity, disability, etc. and insisting upon protecting vulnerable individuals, China focuses on society as a whole by working towards reducing regional disparity and regulating individuals’ behaviour by encouraging inclusive development among their citizens. Therefore, when discussing the same concepts like privacy and safety, Europe and China essentially mean different things. While the Chinese see AI as a way of continuous improvement, some Europeans view it as a potential loss of control. For Europeans, AI development should be fair and the processes transparent. For the Chinese, AI development is to elevate society even at the expense of citizen privacy.
Overall, AI is perceived largely as a force for good in Asian cultures in general; on the other hand, there is a deep-seated fear of a dystopian technological future in Western cultures. In the future, technology and robots are envisioned as pets and companions in Chinese society while in the Western psyche, they are envisioned as tools and potentially deadly machines (as seen in films such as Terminator, The Matrix, and Black Mirror). This reveals blind spots and represents a gap in the cultural representation of AI.
Importance of Cooperation for Sustainable – Global AI Development
A globally interconnected landscape for AI is likely to emerge. To make it a sustainable landscape, it has to be built on mutual trust and inclusive development. Moreover, cross-cultural cooperation in AI has proven to be somewhat effective due to the requirement of diversity for an effective AI system. For example, diversity in data helps create a better AI system for a wider range of consumers and help to counter localised biases. Cooperation doesn’t necessarily require standardisation and uniformity.
Sometimes it is possible to agree on practical issues despite disagreements on abstract values and principles. For this, academia has a key role in building mutual understanding and clarifying where different forms of the agreement will be necessary and possible.  We will have to consider that every nation has different developmental concepts, priorities, and strengths. Therefore, it is critical and cost-efficient to learn from each other. European countries, based on GDPR, have laid a solid foundation for AI ethics and governance. The US and UK have an advantage with regards to being the original innovators in the fundamental theories of AI which has helped in creating more matured AI ecosystems. Japan has been hugely successful in developing a balanced relationship between humans and AI development. And China has been emerging as the leading centre of AI development and manufacturing. Cooperation is essential if we are to deliver and reap the benefits of AI globally. Most of the documents and guidelines from different nations adhere to, or reference the United Nations Sustainable Development goals, which reveals a distinct commonality for international standardisation and time will show whether these actors are willing to respect these principles or if it is an effort more towards international relations. This creates a hybrid approach for AI – incorporating different cultural views and the thread of human commonality working towards improving sustainability, poverty, inequality, health and well-being, environment, etc., to lay a fertile ground for governance.
International cooperation while respecting diversity across cultures and countries is required for sustainable global AI development. As exemplified by the Chinese-European differences and similarities, modern overlap and historical diversions require delicate consideration. Hence, more avenues are necessary to discuss these challenges and increase cross-cultural AI cooperation among nations. Mutual trust-building exercises and cross-cultural development will create a rich atmosphere to promote collaboration and cooperation to create governance that serves all of humanity.