AI's Intelligence Problem
I've spent a good portion of my career exploring systemic challenges. One consistent thread I've observed is the danger of applying one-size-fits-all solutions to diverse realities.
This danger has never felt more urgent than with AI solutions being copy-pasted into African contexts.
For too long, the dominant paradigm, especially in Western cultures, has narrowly defined intelligence primarily through abstract reasoning and logical deduction, often traced back to concepts like IQ testing.
But intelligence is far richer, more multifaceted, than what a standardized test or a language model can capture. "Intelligence" isn't merely about individual cognitive prowess. It often encompasses:
Emotional Intelligence: The ability to understand and manage one's own emotions and those of others, fostering empathy and strong relationships.
Social Intelligence: The skill to navigate complex social situations, build consensus, and contribute to community harmony.
Practical Intelligence: AKA "street smarts" or common sense. This involves solving real-world problems through adaptation and experience, not just theoretical knowledge.
Collective or Community-Oriented Intelligence: Where an individual's wisdom is measured by their contribution to the collective good and the well-being of their community.
This means AI solutions, however well-intentioned, often fail to resonate or even make sense in many contexts.
The Data Desert
This fundamental flaw is compounded by a massive practical problem: the "data desert." AI models are ravenous beasts, demanding vast quantities of data to learn and perform. The overwhelming majority of this data, however, originates from wealthy Western communities, reflecting its languages, behaviors, economic structures, and social norms.
What does this mean for other cultures? It means a critical absence of robust, representative datasets. It means we miss the nuances of local languages and dialects, unique economic activities, context-specific health data, cultural behaviors and social interactions.
What if…
AI was more comprehensively intelligent?
Emotional Intelligence: What if an AI, trained on culturally nuanced emotional expressions and communication patterns, could serve as a personalized mentor for individuals navigating job interviews or difficult workplace situations? Imagine an AI companion that helps a young African entrepreneur practice pitching their business idea to a Western investor, providing feedback not just on content, but also on subtle cues like tone of voice, body language, and culturally appropriate assertiveness. This boosts their confidence and improves their chances of securing funding. This AI would understand the emotional landscape of the interaction.
Social Intelligence: What if an AI could analyze community networks and identify individuals who, through their social connections and trust within the community, could act as effective bridges for economic opportunities? For instance, an AI could map informal credit networks in a village, recognizing key individuals who facilitate lending and repayment based on social capital rather than formal financial history. This AI could then help connect aspiring small business owners with these trusted individuals, facilitating access to capital and fostering localized economic growth, all while respecting existing social structures.
Practical Intelligence: What if an AI could learn from the "street smarts" of local populations to develop more effective and context-specific economic programs? Consider an AI that observes and analyzes how street vendors in a bustling market dynamically adjust their pricing, inventory, and sales strategies based on real-time factors like weather, foot traffic, and supply chain fluctuations. This AI could then provide actionable, real-time insights and recommendations to other vendors, helping them optimize their operations and increase their income, bypassing the need for abstract, theoretical business models that may not apply to their unique environment.
Collective or Community-Oriented Intelligence: What if an AI could facilitate the aggregation and application of community wisdom to address shared economic challenges and create collective wealth? Picture an AI platform that enables a fishing town to pool their collective knowledge about optimal fishing grounds, sustainable practices, and market demand. The AI could analyze this shared data, identify patterns, and propose strategies for collective resource management, improved fishing techniques, or even direct sales to larger markets, leading to increased income and enhanced well-being for the entire community.
To get any of this done, we first have to acknowledge that AI has an intelligence problem.