What Can We Learn from an Anthropological Approach to Managing the Impact of AI on Society?

Introduction

Anthropology is the study of humans, their behaviours, cultures, societies, and evolutionary history.

More formally, according to Merriam-Webster Dictionary, anthropology is “the science of human beings; especially the study of human beings’ physical characteristics, their origins, environmental and social relations, and their culture.”

For the purpose of this article, we will focus on the following four branches ("subfields"):

1. cultural anthropology (or ethnology) - examines social norms, beliefs, rituals, art, and language to understand how individuals and groups create and experience their social worlds

2. social anthropology - examines patterns of behaviour in human societies and cultures.

3. linguistic anthropology - examines the role of language in social life. It studies how language shapes communication, identity, cultural practices, and power dynamics within societies.  

4. psychological anthropology - based upon the insights of Sigmund Freud who adopted 'person-centred' approaches that consider individuals' thoughts, feelings, and motivations.

Intersection of Anthropology and AI

Both disciplines, at first glance, may seem disparate. However, a closer examination reveals their significant interplay.

Anthropology provides a framework for understanding human culture, behaviours, and societies. This understanding is pivotal for developing AI systems that are not only functional but also ethically sound and socially responsible. Conversely, AI influences and modifies human behaviour and social structures.

The rapid evolution of AI technologies necessitates a deeper examination of their societal implications. This connection raises critical questions about the nature of intelligence, the role of technology in our lives, and how cultural contexts shape and are shaped by these advancements.

An Anthropological Approach to AI

Taking an anthropological approach to AI means stepping back from the purely technical lens and instead focusing on how people, communities, cultures, and institutions interact with, adapt to, and shape AI technologies.

It asks deeper questions:

• What does AI mean in different cultural and economic contexts?

• How do people’s values, beliefs, and identities influence their perceptions of AI?

• What kinds of power structures, inequalities, and social norms are being reinforced or challenged by AI?

By studying everyday human behaviour, anthropology helps us explore not only how AI is used, but why it’s used in particular ways — and what that means for people’s lives, livelihoods, and sense of purpose.

Key Learnings from an Anthropological Perspective

1. AI is not neutral — it reflects human cultures and power dynamics

Anthropologists remind us that AI systems often embed biases from the cultures they’re developed in. Understanding local contexts helps prevent technologies from amplifying existing social inequalities.

2. Trust and adoption depend on local values, not just functionality

People adopt or reject AI based on their cultural narratives, histories, and social trust — not just technical accuracy. A community that distrusts institutions may resist AI even if it works well.

3. Work and identity are deeply intertwined

AI’s impact on jobs is not just economic — it’s emotional, psychological, and social. Work gives people identity, structure, meaning, and community. An anthropological view helps us explore how to preserve these non-monetary values even as job roles evolve.

4. Change happens from the bottom up

Anthropology teaches us that grassroots adaptation often leads to more sustainable, human-centred change than top-down disruption. The more communities can shape AI on their own terms, the better the outcomes.

We will engage AIs in discussions and creative brainstorming, leveraging their unique strengths to complement and scale our abilities.

Using These Learnings to Help Ordinary People Benefit from AI

1. Design for inclusion, not just innovation

Co-create AI tools with communities rather than for them. Involve local voices in product development, policymaking, and implementation. This builds cultural relevance and practical usefulness.

2. Promote AI as a tool for empowerment, not replacement

Reframe the narrative: AI isn’t about replacing people but augmenting human capability. Upskilling programs should emphasize how AI can help people do more meaningful or higher-value work, not just automate low-skill labour.

3. Invest in human-AI collaboration, not just automation

Create jobs around AI interpretation, maintenance, ethics, training, and local adaptation — roles that blend human judgment with AI capability, especially in education, healthcare, agriculture, and language services.

4. Use storytelling to demystify AI

Anthropology values storytelling. Use stories — not just data — to explain how AI works, highlight human success stories, and address fears or misconceptions in relatable, human-centred ways.

5. Ensure cultural and linguistic localisation

AI services should speak the language and reflect the values of the communities they serve. This means investing in local data, language models, and ethical frameworks tailored to specific populations.

6. Create community-based AI learning spaces

Encourage grassroots initiatives such as AI literacy hubs, digital cooperatives, and citizen panels, where people can learn, experiment, and participate in shaping AI responsibly and creatively.

Anthropology as a Compass for Human-Centred AI

AI’s true value will not be determined by technological progress alone, but by how well it integrates into the diverse social fabrics of our world. Anthropology offers a compass to guide us through this — helping us design AI that enhances dignity, preserves identity, distributes opportunity fairly, and responds to real human needs.

If we want AI to benefit society at large, we need to go beyond code — and start listening to the people.

Epilogue

The integration of AI into everyday life is transforming human interactions significantly.

AI technologies shape communication patterns, social dynamics, and even personal intimacy. For example, AI-driven algorithms on social media platforms decide which content users see, influencing both public conversations and individual relationships.

Additionally, with AI advancing steadily, it increasingly acts as an intermediary in interpersonal interactions. Virtual assistants and chatbots, while facilitating communication, can also introduce artificial barriers. Consequently, individuals might feel disconnected or misunderstood within their relationships.

"Grasping the cultural implications of AI is vital to ensure its ethical development and purposeful integration into society."

Moreover, the proliferation of AI-based platforms has reshaped social landscapes, leading to notable changes in group interactions and power structures. Awareness of these shifts is essential for comprehending the intersection of technology and cultural behaviours.