6 citations · 7 across the 6 of their papers we have counts for
7 papers
Making Generative AI Workable at Work: Accountability, Localization, and Representation in Kenyan and Nigerian Small Businesses
Najeeb Gambo Abdulhamid, Stephanie Nyairo, Liz Ankrah +1
Generative AI is widely framed as democratizing skilled work by lowering the barrier to producing professional output. Drawing on 21 semi-structured interviews with 27 workers acro…
Toward Cultural Alignment: Human-Centered Evaluation of Multimodal AI Stories Across Five African Communities
Millicent Ochieng, Felermino D. M. A. Ali, Elizabeth A. Ankrah +8
In this paper, we examine how well AI-generated multimodal stories align with the lived practices, relationships, language, values, and visual expectations of the communities they…
Reasoning Beyond Labels: Measuring LLM Sentiment in Low-Resource, Culturally Nuanced Contexts
Millicent Ochieng, Anja Thieme, Ignatius Ezeani +5
Sentiment analysis in low-resource, culturally nuanced contexts challenges conventional NLP approaches that assume fixed labels and universal affective expressions. We present a di…
Dukawalla: Voice Interfaces for Small Businesses in Africa
Elizabeth Ankrah, Stephanie Nyairo, Mercy Muchai +4
Small and medium sized businesses often struggle with data driven decision making do to a lack of advanced analytics tools, especially in African countries where they make up a maj…
AI and the Future of Work in Africa White Paper
Jacki O'Neill, Vukosi Marivate, Barbara Glover +71
This white paper is the output of a multidisciplinary workshop in Nairobi (Nov 2023). Led by a cross-organisational team including Microsoft Research, NEPAD, Lelapa AI, and Univers…
Beyond Metrics: Evaluating LLMs' Effectiveness in Culturally Nuanced, Low-Resource Real-World Scenarios
Millicent Ochieng, Varun Gumma, Sunayana Sitaram +5
The deployment of Large Language Models (LLMs) in real-world applications presents both opportunities and challenges, particularly in multilingual and code-mixed communication sett…
Towards Measuring and Modeling "Culture" in LLMs: A Survey
Muhammad Farid Adilazuarda, Sagnik Mukherjee, Pradhyumna Lavania +5
We present a survey of more than 90 recent papers that aim to study cultural representation and inclusion in large language models (LLMs). We observe that none of the studies expli…