Introduction

The dawn of artificial intelligence (AI) heralds fundamental shifts in economies, societies and philosophies. And nowhere is the ethical terrain more layered than in Asia. From the aged-care robots of Japan to India’s national digital inclusion strategy, from China’s algorithmic governance systems to Southeast Asia’s startup ecosystems, Asia’s AI engagement is as varied as its cultures. Beneath the promise of efficiency and innovation also lies a deeper moral question: How can AI in Asia serve human flourishing rather than undermine it? How should technology be aligned not just with profit but with dignity, equity and collective well-being?

In Asia, the discourse on AI ethics cannot simply be an import of Western frameworks grounded in autonomy and individual rights. It must grapple with relational values, plural traditions, communal agency and developmental equity. This essay maps the ethical contours of AI across Asia, drawing upon philosophical foundations, governance frameworks, socio-economic realities, cultural dynamics and case-study of practice and challenge. It also highlights how Asia’s diversity offers both opportunities and tensions for forging responsible AI in a globalising world.

1. Beyond Western Individualism

Much of the global AI ethics discourse has been shaped by Western philosophical traditions like Kantian autonomy, liberal rights, deontological duty and consequentialist utilitarianism. In Asia, however, different value horizons dominate. For example, Confucian ethics emphasise right relationships and ritual propriety rather than abstract rights detached from communal context. Virtue ethics in an East Asian sense emphasises moral cultivation, harmony and social interconnectedness. In South and Southeast Asia, Buddhist and Hindu traditions shape moral outlooks too. Buddhism emphasises reduction of suffering and awareness of interdependence while Hindu ethical thought brings in the concept of dharma (duty/appropriate conduct) and karma (consequence of actions). These traditions emphasise relational ethics and collective responsibilities over atomised individualism.

From the Asian philosophical lens, what counts ethically is less the isolated individual decision and more the harmony of systems, the relationships between humans and technologies and the societal impacts. For example, the question is not just “can the AI system make a decision” but “how does the AI system relate to human purposes, communal values and social ecosystems?” In East Asia research, the key dimension is “harmony, propriety or a strong concept of trustworthiness” and this has to embed in AI as a value. Such a design philosophy may not hold equivalent priority in Western discourse. Thus, an Asian approach to AI ethics should support relational well-being, reinforce social trust and communal resilience.

2. Implications for AI Design & Deployment

If ethics in Asia emphasises relational value, harmony and collective agency, then design of AI needs to incorporate those dimensions. This means embedding appropriate human oversight that considers local relationships; building datasets that reflect communal diversity and risk assessments that account for social cohesion and not just individual rights. The moral status of machines also becomes modulated to become part of human‐machine ecosystems that require virtuous design and respectful relationships. In sum, the philosophical foundation for AI ethics in Asia tends towards relational ethics, communal well‐being and contextual responsibility, providing a valuable complement (not substitute) to Western frameworks.

Asia is far from monolithic. Governance of AI ethics varies widely from advanced economies with strong regulatory frameworks to developing countries balancing infrastructure gaps and regulatory urgency. Several typologies help us to understand.

1. In East Asia governments are actively shaping national AI strategies, ethics guidelines and robotics policy. Research shows that in places like South Korea, the perception of AI/robots is on a spectrum from “tool to partner”, influencing how ethics are framed.
2. In Southeast Asia and South Asia, the challenge is often one of capacity-building, infrastructure readiness and bridging the gap between business innovation and regulatory maturity. For instance, the ASEAN region has developed a Guide on AI Governance and Ethics modelling voluntary standards for companies and governments.

Thus, Asia provides a spectrum from state-led models to more market-oriented/voluntary models and each coming with its ethical consequences. A few milestone documents and frameworks are worth noting for Implementation and Awareness of Ethics in Asia.

• The UNESCO Recommendation on the Ethics of Artificial Intelligence (2021) provides global principles for human rights, dignity, diversity, ecosystem flourishing and is applicable to all 194 member states.
• The ASEAN Guide on AI Governance and Ethics offers region-specific guidance for commercial and non-military AI use in Southeast Asia. While voluntary, it is seen as a stepping stone to policy harmonisation.
• National frameworks like Japan’s “Society 5.0”, China’s “Ethical Norms for New Generation Artificial Intelligence” (2021), Singapore’s Model AI Governance Framework and India’s NITI Aayog guidelines and Digital Personal Data Protection Act are well researched and ready to implement documents.

Despite these frameworks, significant implementation gaps remain across Asia. The reasons are diverse but a summary of roadblocks is below.

• Capacity and resources: Many smaller companies and MSMEs in Southeast Asia struggle to allocate funds, hire specialised talent or build compliance mechanisms to meet ethical standards.
• Regulatory latency: Policy frameworks often lag behind fast-moving AI development. The ASEAN Guide, for example, originally targeted traditional AI applications but needed extension to Generative AI.
• Contextual relevance: Much of the global AI ethics discourse originates in Western contexts. Some Asian ethical dimensions (relationality, communal values) are underrepresented. Researchers argue for Asian values to be integrated and not merely imported.
• Enforcement and accountability: Voluntary guidelines without monitoring, audits or remediation mechanisms risk being symbolic rather than substantive.
• Equity and development dynamics: Many countries struggle to ensure that AI benefits reach marginalized groups, including rural populations, linguistic minorities and informal workers

3. The Global South Context

For many countries in Asia, especially those in the Global South, the ethics of AI are entwined with development, inclusion and structural inequality. AI holds promise of improved health diagnostics, smart agriculture and efficient public services but also risks biased datasets, exclusion of underrepresented populations, automation displacing vulnerable workers and power asymmetries in data ownership.

In Asia, datasets and models are often designed by multinational firms in the Global North; local labour (often informal) performs annotation or data-labelling, yet value accrues elsewhere. Scholars call this algorithmic or data colonialism. Ethical AI in Asia thus requires attending to who defines intelligence, who collects and owns data, and who benefits from AI systems.

Ethics in Asia cannot focus solely on “bias” in models trained on Western populations. It must also address:

• Language diversity: Asia is home to thousands of languages and many AI systems remain optimized for English or major languages, raising accessibility issues.
• Digital infrastructure: Uneven broadband, connectivity and device access mean AI deployment may exclude rural or low‐income populations.
• Skills and workforce: If AI-driven automation disproportionately displaces informal workers or young entrants without retraining, inequality deepens.
• Data sovereignty: Who controls data collected from populations? Are local communities informed and empowered?

Thus, an ethical AI agenda for Asia must emphasise equitable access, localisation, participatory governance and capacity building.

4. Cultural Dynamics

Cultural attitudes in many Asian societies differ from Western norms. Trust in government, institutions and collective decision-making tends to be higher in some Asian contexts; consequently, societal acceptance of state-led digital systems may be greater. For example, in the pandemic, certain Asian governments deployed contact-tracing apps with relatively fewer objections compared to Western publics.

AI ethics in Asia must also engage with gender norms, social hierarchy and representation. Research from East Asia identifies three challenges with robotics and AI: female objectification, the anthropomorphised tools paradox (robots as “partners”), and antisocial development (where machines reduce human relationships). In societies where gender norms and labour divisions differ from Western contexts, these issues may take unique forms: e.g., robotic caregiving in eldercare, cultural expectations of subservience or biases in datasets shaped by local tradition.

Corporations operating in Asia are increasingly adopting AI ethics codes, yet often the challenge lies in translating principles into operational practice. Large tech players have published ethics guidelines emphasising safety, fairness, transparency and human oversight. However, such charters may still lack enforcement, audits or public disclosure mechanisms. The “principles‐versus‐practice” gap remains acute.

Ethical implementation requires:

• embedding ethics into the design lifecycle of AI systems (ethics-by-design)
• performing ethical impact assessments (EIAs) relevant to local contexts
• ensuring accountability mechanisms, redress for harms and inclusive stakeholder participation

5. Academic & Research Ecosystems

Asian universities and policy institutes are starting to bridge the ethics-technology divide. For example, interdisciplinary research in Thailand emphasises the need to include social sciences, humanistic inquiry and cultural perspectives in AI governance. However, challenges remain as many AI ethics discussions are still siloed in computer science or engineering departments while humanities and local social sciences may be under-represented. Building ethical AI in Asia thus requires cross-disciplinary collaboration, localised case-studies, and ethics education that resonates with cultural and developmental realities.

While bias and fairness are universal ethics issues, their specific content in Asian contexts may differ. Under-represented populations may include linguistic minorities, rural communities, informal sector workers, caste or ethnic minorities, and migrant labourers. AI systems trained on urban, English-language, or majority-language data may exclude these groups. The ethical challenge for Asia is ensuring inclusive datasets, diverse participation in design, and equitable distribution of benefits.

AI-driven automation threatens certain categories of labour more than others: manufacturing, routine services, data annotation, gig work. In Asia, many workers are informal and lack social protections, making them more vulnerable. Ethical AI must therefore engage with socio-economic justice: How to guard against widening inequality? How to ensure transitions, reskilling, and fair labour practices? This dimension is strong in Global South contexts.

Asia faces climate and sustainability urgency. AI deployment must align with ecological goals: energy-efficient models, localised computing wherever possible and integration with sustainability frameworks. Ethical AI must account for environmental cost, resource consumption and long-term geo-social consequences. Asia, which hosts diverse environments and resource constraints, must consider ecological and sustainability ethics alongside equity. The ethics of AI should integrate questions of resource use, environmental footprint and sustainability, aligning with Asia’s developmental priorities.

Asia is emerging as both a major site of innovation and risk for generative AI, deepfake technology and cyber-fraud operations. For example, sophisticated deep-fake scams in South Asia highlight how AI can be leveraged for large-scale economic and human‐rights harm. The ethics of AI in Asia therefore must also deal with emergent risks: mis/disinformation, impersonation, automated fraud, and regulatory catch-up.

Asia faces the dilemma of aligning with global AI ethics standards while adapting to local cultural, ethical and developmental contexts. One risk is simply adopting Western frameworks without context; the other is divergent standards that hinder interoperability or global trust. The ethical imperative is to harmonise rather than polarise.

6. Case Study in Asia: Japan: Society 5.0

In Japan, the concept of “Society 5.0” aims to integrate AI, IoT and robotics into a human-centred society addressing aging, labour shortages and social well-being. In this model, ethical commitments include coexistence, welfare and quality of life improvement. Research identifies that Japanese societal narratives treat robots and AI not just as tools but as partners. At the same time, questions arise: What if human relationships are replaced by robots? How do we preserve human dignity in a hyper-automated context?

Based on the preceding analysis, we can propose key components for a coherent AI ethics agenda tailored to Asia. Ethics frameworks must reflect local traditions (relationality, harmony, collective welfare), languages, cultures and development imperatives. Ethical AI in Asia must emphasise inclusive access to data, infrastructure, talent and governance. It must ensure that benefits of AI reach rural, under-represented, linguistic and informal sectors. It must address digital divides and capacity gaps. Mechanisms might include subsidised governance support for MSMEs, open datasets in regional languages and participatory design.

7. SWOT of Asian Ethics Landscape

The Strengths & Opportunities of the Asian ecosystem are as under:

• Plural cultural ethics: Asia’s diversity of traditions offers rich ethical vocabularies (relationality, community, compassion) that can enrich global AI ethics beyond Western liberal frames.
• High adoption potential: Many Asian societies are already engaged with digital services and may more readily adopt AI systems; this offers opportunity to build responsible systems from the ground up.
• Developmental need as lever: The imperative to address issues of inclusion, inequality and growth creates a strong ethical imperative to “get AI right” in Asia, leading to innovation in governance, design and localisation.
• Regional cooperation momentum: Frameworks such as ASEAN AI Guide indicate a willingness for cross-country cooperation in ethics and governance.

Weaknesses & Risks are as under:

• Capacity and resource gaps: Especially in developing Asian economies, infrastructure, talent, regulatory maturity and funding are limited, which hampers ethical deployment.
• Power asymmetries and surveillance risks: Some Asian models prioritise state control, raising ethical risks around autonomy, accountability, and civil rights.
• Global North dominance in standards and data: If Asian actors remain passive recipients of global AI systems, then issues of data colonialism, export of bias and exclusion persist.
• Implementation gap: Many frameworks exist on paper, but fewer mechanisms for enforcement, auditing and accountability are in place.
• Rapid technology pace out-stripping governance: Generative AI, deepfakes, and new frontier models may challenge Asian regulatory systems which are still evolving.

Conclusion

Artificial intelligence offers transformative potential for Asia in healthcare, agriculture, urban services, education, and economic inclusion. But this potential is matched by ethical stakes. In Asia, the ethics of AI cannot simply mirror Western debates about privacy or individual rights: it must inhabit the terrain of relational values, communal welfare, development justice, cultural diversity, and institutional capacity. Asia’s plural traditions offer rich moral frameworks that can ground AI systems in human flourishing rather than mere efficiency.

In the end, the question is not simply what can AI do in Asia, but what should AI do in the context of human dignity, social coherence and shared futures.

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Author — Sudhir Tiku -Refugee, TEDX Speaker, Global South Advocate.Fellow AAIH & Editor AAIH Insights