This article proposes five ideas that the design of data governance policies for the trustworthy use of artificial intelligence (AI) in Africa should consider. The first is for African states to assess their domestic strategic priorities, strengths, and weaknesses. The second is a human-centric approach to data governance, which involves data processing practices that protect the security of personal data and the privacy of data subjects; ensure that personal data are processed in a fair, lawful, and accountable manner; minimize the harmful effect of personal data misuse or abuse on data subjects and other victims; and promote a beneficial, trusted use of personal data. The third is for the data policy to be in alignment with supranational rights-respecting AI standards like the African Charter on Human and Peoples Rights, the AU Convention on Cybersecurity, and Personal Data Protection. The fourth is for states to be critical about the extent to which AI systems can be relied on in certain public sectors or departments. The fifth and final proposition is for the need to prioritize the use of representative and interoperable data and ensure a transparent procurement process for AI systems from abroad where no local options exist.
Category: Research Topic: Tech & Society (STS)
Research Topic: Tech & Society (STS)
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OECD Gender Equality in Technology Governance
Director Mackenzie represented the Aula Fellowship and the AI context in conversations at this global conference for equity. We stand together, or we fall.
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Beyond the algorithm: Empowering ai practitioners through liberal education
As AI technology continues to transform society, there is a growing need for engineers and technologists to develop interdisciplinary skills to address complex, society-wide problems. However, there is a gap in understanding how to effectively design and deliver inter-disciplinary education programs for AI-related training. This paper addresses this gap by reporting on a successful summer school program that brought together specialists from around the world to engage in deliberations on responsible AI, as part of a Summer School in Responsible AI led by Mila – Quebec Artificial Intelligence Institute. Through deep dive auto-ethnographic reflections from five individuals, who were either organizers or participants, augmented with end-of-program feedback, we provide a rich description of the program’s planning, activities, and impact. Specifically, our study draws from engineering education research, bridging the gap between research and practice to answer three research questions related to the program: (1) How did the program design enable a more effective understanding of interdisciplinary problem-sets? (2) How did participants experience the interdisciplinary work of the program? (3) Did the program affect participants’ impact on interdisciplinary problem-sets after the program? Our findings highlight the benefits of interdisciplinary, holistic, and hands-on approaches to AI education and provide insights for fellow engineering education researchers on how to design effective programs in this field.
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Decoding the Diversity: A Review of the Indic AI Research Landscape
This review paper provides a comprehensive overview of large language model (LLM) research directions within Indic languages. Indic languages are those spoken in the Indian subcontinent, including India, Pakistan, Bangladesh, Sri Lanka, Nepal, and Bhutan, among others. These languages have a rich cultural and linguistic heritage and are spoken by over 1.5 billion people worldwide. With the tremendous market potential and growing demand for natural language processing (NLP) based applications in diverse languages, generative applications for Indic languages pose unique challenges and opportunities for research. Our paper deep dives into the recent advancements in Indic generative modeling, contributing with a taxonomy of research directions, tabulating 84 recent publications. Research directions surveyed in this paper include LLM development, fine-tuning existing LLMs, development of corpora, benchmarking and evaluation, as well as publications around specific techniques, tools, and applications. We found that researchers across the publications emphasize the challenges associated with limited data availability, lack of standardization, and the peculiar linguistic complexities of Indic languages. This work aims to serve as a valuable resource for researchers and practitioners working in the field of NLP, particularly those focused on Indic languages, and contributes to the development of more accurate and efficient LLM applications for these languages.
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How Issav Asimov Predicted/Influenced the Present AI Scenario
This paper investigates Isaac Asimov’s impact on modern artificial intelligence (AI) and robotics, focusing on how his visionary narratives and Three Laws of Robotics resonate with current technological practices and ethical debates. Analyzing specific predictions from Asimov’s works that have materialized in today’s AI applications, we draw parallels between his fictional insights and real-world technologies from leading tech firms. The study further considers the social implications of AI, including issues of human displacement and trust. We also discuss the progress and challenges in formulating global ethical standards for AI, reflecting on national and international efforts. The analysis highlights Asimov’s lasting influence and the ongoing importance of ethical deliberation in the AI field.
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Unveiling AI Concerns for Sub-Saharan Africa and its Vulnerable Groups
In Sub-Saharan Africa (SSA), artificial intelligence is still in its early stages of adoption. To ensure that the already existing class imbalance in SSA communities does not hinder the realization of the Sustainable Development Goals, such as data security, safety, and equitable access to AI technologies, acceptable reliability measures must be put in place (as policies). This paper identifies some of the vulnerabilities in AI and adds a voice to the risks and ethical concerns surrounding the use of AI and its impact on SSA and its vulnerable groups. Our systematic literature review of related research between January 2014 and June 2024 shows the current state of AI adoption in SSA and the socio-political challenges that impact its development, revealing key concerns in data Governance, safety privacy, educational and skill gaps, socioeconomic impacts, and stakeholder influence on AI adoption in SSA. We propose a framework for designing data governance policies for the inclusive use of AI in SSA.
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Public Consultation: AI & Copyright, Canada
This white paper is a response to Industry Canada’s public call for expert consultation on AI and Copyright. The consultation had specific questions, which are reproduced with our
answers, below. -
Several presentations, including “Taking the Lead in SWE: An Asian Perspective.”
Dr. Bhaduri will be presenting at the Society of Women Engineers, with whom she is a Senator. Several events are online for interested persons. Dr. Bhaduri is an accomplished technologist and educator, as well as being excellent speaker and is appreciated for her wit, her precision, and her kindness.