Artificial intelligence (AI) has penetrated nearly every aspect of our digital lives, from personalized recommendations on ecommerce platforms to complex systems for healthcare and finance. While AI might seem universal, cultural perspectives have great influence on its adoption. Western cultures often regard AI as a tool to enhance productivity, despite accompanying fears of job replacements and ethical concerns. In contrast, many Eastern cultures view AI as an extension of human collaboration rather than competition. These cultural perceptions shape not only how people integrate AI into their daily lives and how much they trust AI, but also how humans design AI.
This column explores how different cultures perceive AI, its limitations in understanding cultural nuances, and how design can enable AI to better reflect this diversity.
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How People Perceive AI Across Different Cultures
Cultural differences influence how people interact with technology and shape their perceptions of AI. In Western societies, people view AI as a tool that can boost efficiency and enable them to maintain control. They prefer to manage AI systems directly, reflecting the individualism of Western cultures, in which individuals shape their environments rather than adapt to them.
Western technology giants such as Microsoft and Google are integrating AI into their productivity tools. As Figure 1 shows, Microsoft Copilot helps users draft email messages, summarize documents, automate scheduling, and optimize workflows. While these tools reduce manual labor and enhance individuals’ efficiency, they still let users maintain a high level of control.
Figure 1—Microsoft Copilot supports an AI assistant in Word
In contrast, Eastern cultures often embrace AI as a natural extension of human life, emphasizing harmony rather than control. Instead of viewing AI solely as a tool, people in these cultures are more inclined to engage with AI as a collaborator or companion that enhances their experience. This mindset aligns with an interdependent view of the self, in which the individual and the environment are deeply connected. Recent research also suggests that East Asians are more likely to anthropomorphize technology and actually view chatbots as a form of life within the natural world because of the influence of the animistic nature of Eastern religions. This perspective helps explain why social companion robots are especially popular in Asia, as Figure 2 shows.
Figure 2—Ropet AI provides companions for Asian females
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AI’s Limitations in Cultural Understanding
AI systems, particularly large language models (LLMs), struggle to understand and represent cultural nuances accurately. A recent study found that GPT-4o often aligns with the cultural values of English-speaking and Protestant European countries, especially regarding self-expression, gender equality, and environmental concerns.
In an experiment, researchers tested ChatGPT by assigning personas from various countries, including the US, India, Finland, Austria, Canada, Germany, Nigeria, and the UAE. Despite their giving the AI additional cultural background information before answering, the AI still produced inaccurate portrayals, with India being the least well represented. This suggests that AI models likely have biases due to the training data on which they rely. This can lead to distorted cultural representations.
Such biases pose a serious threat to fair and ethical AI applications. If AI algorithms have biased cultural interpretations, the use of AI-powered tools in decision-making processes could potentially reinforce existing inequalities. For example, bias in the algorithms of hiring tools could influence candidate evaluations and even exclude top candidates, as Figure 3 illustrates.
Figure 3—Biased cultural interpretations in AI hiring tools
Unlike humans, AI lacks lived experiences and emotional intelligence, causing difficulties in grasping cultural nuances. While AI is a powerful tool across various domains, it is essential to acknowledge its limitations in cultural interpretation and ensure that human oversight guides the applications of AI in sensitive areas.
How Culture-Driven Design Can Address Cultural Bias in AI
Because AI is evolving rapidly, addressing its cultural biases has become increasingly important. One effective, culture-driven design approach tailors AI experiences to cultural norms and the behaviors of target users.
Following up on my earlier discussion of GPT-4o’s cultural alignment, cultural prompting has emerged as a key strategy for mitigating bias. This technique instructs the model to respond from a specific country’s perspective. Studies indicate that this method can reduce bias in 71% to 81% of tested countries, making AI more adaptable and culturally aware.
In addition to cultural prompting, this approach also incorporates the following principles:
data representation and bias mitigation—AI should use diverse, representative datasets and employ bias-detection tools such as IBM AI Fairness 360 to correct cultural biases.
adaptive AI behavior—Implementing cultural prompting and customizing AI responses’ tone and etiquette on the basis of cultural norms enhances adaptability.
ethical and regulatory compliance—AI must align with global ethical standards such as EU AI Act and UNESCO’s AI Ethics Framework and maintain human oversight of culturally sensitive decisions.
localized UX design—User interfaces, visuals, and interactions should reflect cultural expectations while respecting customs, taboos, and communication styles.
continuous learning and human feedback—Using ethnographic AI research and real-time user feedback helps refine AI’s cultural understanding over time.
These principles are based on well-established frameworks such as Hofstede’s Cultural Dimensions Theory and Human-Centered AI. By integrating these frameworks, AI systems can become more adaptable and culturally aware. One example of such a platform is Diversio, which focuses on diversity, equity, and inclusion, as Figure 4 shows. Diversio helps businesses identify and mitigate bias in hiring and workplace culture by using AI to analyze diversity metrics and provide insights that promote inclusivity.
Figure 4—Diversio’s AI-driven insights promote diversity and inclusion
The Evolving Intersection of Culture and AI
While the influence of cultural differences such as individualism and collectivism on digital software is well known, there is still much to discover about how cultural dimensions shape people’s perceptions of and responses to AI. Within this technological revolution, fostering AI with a human-centered and culturally aware mindset is a crucial skill. By prioritizing inclusivity and cultural adaptability, we can build AI systems that empower users, enhancing human capabilities rather than replacing them.
Jo is a product designer who has experience in various markets. She has worked in countries such as Taiwan, China, the Netherlands, and the United Kingdom. Jo has a keen interest in exploring how different cultures intersect and influence the software user interface (UI), user experience, and product strategy. Over the years, Jo has gained valuable insights from these diverse cultures and their transitions. As a result, she aims to share these insights with a broader audience that is interested in the cultural aspects of digital product design. Read More
