Culturally Responsive Artificial Intelligence – Problems, Challenges and Solutions
Open accessAbstract
In the contemporary interconnected world, the concept of cultural responsibility occupies paramount importance. As the lines between nations become less distinct, it is incumbent upon individuals, communities, and institutions to assume the responsibility of safeguarding and valuing the landscape of diverse cultures that constitute our global society. This paper explores the socio-cultural and ethical challenges stemming from the implementation of AI algorithms and highlights the necessity for their culturally responsive development. It also offers recommendations on essential elements required to enhance AI systems’ adaptability to meet the demands of contemporary multicultural societies. The paper highlights the need for further multidisciplinary research to create AI models that effectively address these challenges. It also advocates the significance of AI enculturation and underlines the importance of regulatory measures to promote cultural responsibility in AI systems.
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Cultural validity builds trust by ensuring that AI systems align with the beliefs, traditions, and ways of knowing of the people and the situated contexts and lifeworlds they serve.
“Cultural validity builds trust by ensuring that AI systems align with the beliefs, traditions, and ways of knowing of the people and the situated contexts and lifeworlds they serve, further ensuring that local knowledge systems are respected and used [19, 49].”
From Designing Responsible AI with Indigenous Communities: Towards Participatory AI with ovaHimba and San People in Namibia (2026) · cites this paper as [49]
The Introduction (page unavailable) describes cultural responsiveness as listening to people’s understanding and experiences and adapting to their preferences. The Recommendations (page unavailable) also advocate incorporating sociocultural values into AI. These passages support cultural alignment, but they do not say that “cultural validity” builds trust or specifically address situated lifeworlds and the use of local knowledge systems. (LLM, conf=0.82)
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Indongo, N. N., Smith, R. C., Winschiers-Theophilus, H., Kandjengo, S., & Mbinge, U. (2026) · Proceedings of the 19th Participatory Design Conference 2026, Vol. 1: Full Papers · doi:10.1145/3796624.3796667
- Authors
- Ożegalska-Łukasik, N., & Łukasik, S.
- Affiliations
- Jagiellonian University (PL)
- AGH University of Krakow (PL)
- Venue
- Intercultural Relations
- Publisher
- Ksiegarnia Akademicka Sp. z.o.o.
- Published
- 2023-12-28
- Volume
- 7
- Issue
- 2(14)
- Pages
- 106-119
- ISSN
- 2544-2139 (ISSN-L)
- 2544-2546
- OpenAlex
- W4390976599
- Cited by
- 16
- References
- 3
- Citations by year
- 2026: 6 · 2025: 10
- FWCI
- 4.01
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- Intercultural Relations (publishedVersion, cc-by-nc-nd)
- arXiv (Cornell University) (submittedVersion, cc-by-nc-nd)
- Homo Politicus (Academy of Humanities and Economics in Lodz) (submittedVersion, cc-by-nc-nd)
- arXiv (Cornell University)
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Social Sciences › Sociology and Political Science › Innovation, Sustainability, Human-Machine Systems
- Keywords
- cultural responsibility, AI ethics, multicultural society, AI regulation, cultural diversity, algorithmic bias
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