Abstract: In the rapidly evolving landscape of international development and humanitarian aid, knowledge democratisation plays a pivotal role. The ability to share and access information across borders and organisations is essential for achieving sustainable impact. However, as we embrace artificial intelligence (AI) to facilitate knowledge exchange, we must also address privacy concerns. This blog post explores the intricate relationship between knowledge democratisation, AI, and user privacy within the context of global development efforts. We propose policy changes that balance innovation with the protection of individual rights in an increasingly data-centric world.
The importance of power dynamics in knowledge democratisation
Understanding who holds power and whose knowledge counts iscritical to navigating knowledge democratisation. Historically, policy and decision-makers have considered privileged data from Western sources andoverlooked local knowledge. As Kofi Annan, former UN Secretary-General, famously stated: "Information does not belong to one ideology or another; knowledge is not the privilege of one creed or conviction. If information and knowledge are central to democracy, they are the conditions for development. It is that simple… It is our duty and our responsibility to see that gift bestowed on all the world’s people, so that all may live lives of knowledge and understanding."
AI-driven tools can democratise knowledge by providing equitable access to information and personalised learning experiences, empowering individuals from diverse backgrounds to gain the skills and insight sthey need to succeed. These tools break down traditional barriers, making high-quality resources available to a wider audience and offers new opportunities to challenge existing power dynamics. Yet, we must balance this potential with the protection of individual rights and respect for cultural contexts (Beduschi, 2022).
Privacy risks in the global context
Scale and cross-border data flows
AI’s hunger for vast data transcends national boundaries, involving diverse stakeholders in international development efforts. Cross-border data flows raise jurisdictional and sovereignty concerns ,impacting privacy rights.
In large-scale humanitarian efforts, data from various countries is often pooled to create comprehensive AI models that can predictneeds and allocate resources efficiently. For instance, data from differentrefugee camps around the world might be aggregated to improve response strategies. Although this practice can lead to conflicts between different national privacy laws, posing significant challenges in protecting individual data.
Humanitarian data ethics and ethical considerations in crisisdata collection
In crisis situations such as natural disasters or conflicts, rapid data collection is crucial for effective response. AI-driven systems can analyse this data to identify the most affected areas and allocate resources swiftly. However, the urgency of data collection must be balanced with the needto respect the dignity and privacy of affected populations. Ensuring ethical guidelines are followed, even in high-pressure situations, is essential to prevent the misuse of sensitive information and maintain the trust and dignity of those impacted (Fournier-Tombs, Albrecht, & Brubaker, 2024).
Data sharing and collaboration
International development relies on cooperation and collaboration. AI platforms facilitate knowledge exchange, but data sharing must be transparent and consensual. Striking the right balance between open collaboration and privacy protection is essential (Smith, Jones, & Patel, 2020).
For example, when multiple NGOs work together on a project, they need to share data to avoid duplicating efforts and to create more comprehensive solutions. AI platforms can streamline this process by integrating and analysing data from various sources, providing a unified view that enhances coordination and decision-making. This could look like a centralisedAI-driven dashboard that aggregates data where we can easily spot gaps, successes, challenges and opportunities efficiently with a friendly user interface.
It Is essential that all parties Involved are aware of and consent to how their data will be used. This can be achieved through clear communication and robust systems of consent. These measures are necessary to maintain trust and cooperation among stakeholders, ensuring that data sharing is ethical and effective.
Policy recommendations for privacy protection
Informed consent and ethical AI
Strengthen informed consent processes to ensure that users, especially vulnerable populations, understand how their data contributes to AI models. How? By embedding ethical AI principles into development practices, emphasising privacy and human rights.
Enhancing informed consent
In many cases, individuals providing data may not fully understand how it will be used by AI systems. Simplifying consent forms and ensuring they are available in local languages can help bridge this gap. Additionally, using visual aids or interactive tools can enhance comprehension and make the consent process more engaging and effective.
Proposed policy for global data governance
Developing international norms for data sharing in humanitarian contexts and addressing legal gaps by harmonising privacy regulations across countries.
Creating international data governance frameworks
International bodies like the United Nations could lead efforts to create standardised data governance frameworks that apply across borders. Such frameworks would ensure that data sharing in humanitarian contexts adheres to agreed-upon privacy standards, reducing the risk of data misuse and enhancing collaboration between countries and organisations.
Human-centric AI design
Prioritise user agency. Allow individuals to control their data sharing preferences. Design AI systems that respect cultural norms and local privacy expectations.
User-controlled data sharing
Providing users with tools to easily manage their datasharing preferences can empower them and build trust. For instance, AI platforms could include user dashboards where individuals can see what data has been collected, how it is being used, and opt in or out of data sharing as they see fit.
In harnessing AI for global development, we cannot compromise privacy rights. Policymakers, practitioners, and technologists must collaborate to create a data-centric world that respects individual dignity, fosters knowledge democratisation, and safeguards privacy. AI systems like Propel represent more than technical solutions; they embody a shift towards embedding a culture of knowledge-sharing and ethical data use at the heart of development work.
Let’s work together to create a future where data not only informs but transforms global impact.
References:
Beduschi, A. (2022). Harnessing the potential of artificial intelligence for humanitarian action: Opportunities and risks
Fournier-Tombs, E., Albrecht, E., & Brubaker, R. (2024).Disinformation and Peacebuilding in Sub-Saharan Africa: UNU-CPR
Smith, A., Jones, P., & Patel, R. (2020). Digital Platforms and Knowledge Management in International Development
United Nations Secretary-General Kofi Annan (1997)