Data Flows and Colonial Regimes in Africa: A Critical Analysis of the Colonial Futurities Embedded in AI Recommendation Algorithms Angella Ndaka, University of Witwatersrand, Johannesburg, South Africa Fátima Ávila - Acosta, Berlin Graduate School of Social Sciences at Humboldt University, Berlin, Germany Harnred Mbula, Centre for Epistemic Justice, Nairobi, Kenya Christine Amera, Centre for Epistemic Justice, Nairobi Kenya Sandra Tiyani Chauke University of Pretoria, South Africa Eucabeth Majiwa Jomo Kenyatta University of Agriculture and Technology, Nairobi, Kenya Abstract In the last few years, Africa has experienced growth in a thriving ecosystem of Artificial Intelligence (AI) technologies and systems, developed and promoted by both local and global technology players. While the sociotechnical imaginaries about these syst ems promote AI as critical to achiev ing Africa's sustainable development agenda, some of them have subtly permeated society, recreating new values, cultures, practices, and histories that threaten to marginalize minority groups in the region. Africa predominantly frames AI as an imaginary solution to address complex social challenges; however, the narrative subtly ignores deeper power - related concerns, including data governance, embedded algorithmic colonialism, and the exploitation that propag ates new digital colonial sites. However, the development of current AI ethics in Africa is in its infancy and predominantly framed through lenses of Western perspective, with the social and ethical impacts of the AI innovations and application on African epistemologies and worldviews not prioritized. To ensure that people on the African continent leverage the benefits of AI, these social and ethical impacts o f AI need to be critically and explicitly considered and addressed. This chapter will therefore seek to frame the elemental and invisible problems of AI and big data in the African context by examining digital sites and infrastructure through the lens of power and interests. It will present reflections on how these sites are using AI recommendation algorithms to recreate new digital societies in the region, how they have the potential to propagate algorithmic colonialism and negative gender norms, and what this means for the regional sustainable development agenda. The chapter proposes adopting business models that embrace response - ability and consider the existence of alternative socio - material worlds of AI. These reflections will mainly come from ongoing discussions with Kenyan social media users in this author's user space talks, which take place every month. Keywords: Artificial Intelligence; algorithmic colonialism; Data; response - ability; digital sites Section 1: Introduction The growing global interest, combined with rising investments in AI skilling and infrastructure development, is a key driver of the expanding landscape of AI technologies and systems across Africa.

It feels like everything is slowly but surely being affected by the rise of artificial intelligence (AI). And like every other disruptive technology before it, AI is having both positive and negative outcomes for society. One of these negative outcomes is the very specific, yet very real cultural harm posed to Australia's Indigenous populations. The National Indigenous Times reports Adobe has come under fire for hosting AI-generated stock images that claim to depict "Indigenous Australians", but don't resemble Aboriginal and Torres Strait Islander peoples. Some of the figures in these generated images also have random body markings that are culturally meaningless.

The global AI surge demands crowdworkers from diverse languages and cultures. They are pivotal in labeling data for enabling global AI systems. Despite global significance, research has primarily focused on understanding the perspectives and experiences of US and India crowdworkers, leaving a notable gap. To bridge this, we conducted a survey with 100 crowdworkers across 16 Latin American and Caribbean countries. We discovered that these workers exhibited pride and respect for their digital labor, with strong support and admiration from their families. Notably, crowd work was also seen as a stepping stone to financial and professional independence. Surprisingly, despite wanting more connection, these workers also felt isolated from peers and doubtful of others' labor quality. They resisted collaboration and gender-based tools, valuing gender-neutrality. Our work advances HCI understanding of Latin American and Caribbean crowdwork, offering insights for digital resistance tools for the region.

Data are essential in developing healthcare artificial intelligence (AI) systems. However, patient data collection, access, and use raise ethical concerns, including informed consent, data bias, data protection and privacy, data ownership, and benefit sharing. Various ethical frameworks have been proposed to ensure the ethical use of healthcare data and AI, however, these frameworks often align with Western cultural values, social norms, and institutional contexts emphasizing individual autonomy and well-being. Ethical guidelines must reflect political and cultural settings to account for cultural diversity, inclusivity, and historical factors such as colonialism. It focuses on the contrast between individualistic and communitarian approaches to data ethics. The proposed framework could inform stakeholders, including AI developers, healthcare providers, the public, and policy-makers about healthcare data ethical usage in AI in Africa. Keywords: data ethics, artificial intelligence, ubuntu philosophy, ethical framework, global health Introduction Healthcare systems are the pillar of public health and well-being, providing essential services to communities worldwide. However, only between one-third and one-half of the world's population had access to essential health services in 2017 (World Health Organization 2020), especially in the Global South.

With growing application of machine learning (ML) technologies in healthcare, there have been calls for developing techniques to understand and mitigate biases these systems may exhibit. Fair-ness considerations in the development of ML-based solutions for health have particular implications for Africa, which already faces inequitable power imbalances between the Global North and South.This paper seeks to explore fairness for global health, with Africa as a case study. We conduct a scoping review to propose axes of disparities for fairness consideration in the African context and delineate where they may come into play in different ML-enabled medical modalities. We then conduct qualitative research studies with 672 general population study participants and 28 experts inML, health, and policy focused on Africa to obtain corroborative evidence on the proposed axes of disparities. Our analysis focuses on colonialism as the attribute of interest and examines the interplay between artificial intelligence (AI), health, and colonialism. Among the pre-identified attributes, we found that colonial history, country of origin, and national income level were specific axes of disparities that participants believed would cause an AI system to be biased.However, there was also divergence of opinion between experts and general population participants. Whereas experts generally expressed a shared view about the relevance of colonial history for the development and implementation of AI technologies in Africa, the majority of the general population participants surveyed did not think there was a direct link between AI and colonialism. Based on these findings, we provide practical recommendations for developing fairness-aware ML solutions for health in Africa.

Prior work has explicated the coloniality of artificial intelligence (AI) development and deployment. One process that that work has not engaged with much is alignment: the tuning of large language model (LLM) behavior to be in line with desired values based on fine-grained human feedback. In addition to other practices, colonialism has a history of altering the beliefs and values of colonized peoples; this history is recapitulated in current LLM alignment practices. We suggest that AI alignment be decolonialized using three proposals: (a) changing the base moral philosophy from Western philosophy to dharma, (b) permitting traditions of argument and pluralism in alignment technologies, and (c) expanding the epistemology of values beyond instructions or commandments given in natural language.

A House Democrat is warning artificial intelligence could become a tool of "digital colonialism" if the U.S. doesn't take steps to work with Western Hemisphere nations to create AI systems that reflect diversity and inclusion. Rep. Adriano Espaillat, D-N.Y., proposed a resolution during the August break that says the U.S. must champion a "regional" AI strategy that includes Western Hemisphere nations as this new technology is developed. "United States-led investments in the development of AI in the Western Hemisphere would promote the inclusion and representation of underserved populations in the global development and deployment of AI technologies, ensuring that no individual country dominates AI but rather collaborative developments in the Western Hemisphere," his resolution asserted. WHAT IS ARTIFICIAL INTELLIGENCE (AI)? Rep Adriano Espaillat, D-N.Y., is calling on the U.S. to work closely with Western nations as it develops artificial intelligence systems and guidelines.

OpenAI said Tuesday that it has released an AI "classifier" for identifying AI-authored text written by AI like its own ChatGPT. The problem? ChatGPT is pretty good at evading OpenAI's new tool. ChatGPT has absolutely overwhelmed academia, where students are using it as a virtual assistant of sorts in a variety of tasks. Unfortunately, some students are crossing the line and using it to create content that they are passing off as original--cheating, in other words. The trouble is trying to determine which answers were written by a human, and which by an AI.

The vast list of artificial intelligence applications continually increases as researchers, technologists, and scientists try to leverage computing power to gain competitive edges over the more slowly adopting set. Today I want to traipse across the American business and tech landscape and present a few of the new and hopefully intriguing upgrades of these mostly familiar devices and services being brought into the 21st century via AI. First a quick overview of the concept of AI and where it's come from over the past years and decades. Earlier writings comingled two phrases to identify the technology: artificial intelligence, which has become the well-known marketable way to talk about the tech, and "computational intelligence," which might be useful amongst a group of AI--err, CI?--subject matter experts, but doesn't carry the cachet of its more widely accepted phrase. For anyone who uses either phrase, it's generally understood to refer to some sort of machine-based intelligence.

My husband and I love to eat and to learn about history. So shortly after we married, we chose to honeymoon along the southern coast of Spain. The region, historically ruled by Greeks, Romans, Muslims, and Christians in turn, is famed for its stunning architecture and rich fusion of cuisines. Little did I know how much this personal trip would intersect with my reporting. Over the last few years, an increasing number of scholars have argued that the impact of AI is repeating the patterns of colonial history.