I recently read an interesting piece from Harvard Business Review titled "Find the AI Approach That Fits the Problem You're Trying to Solve " The essence of the article resonates deeply with my own beliefs, particularly around the notion that effective problem-solving begins with asking the right questions. Statements such as "without the right questions, you'll be starting your journey in the wrong place" and "Start with the problem, not the technology" echo a seemingly obvious yet profoundly complex reality.
This concept, while straightforward, is far from simplistic. In the realm of international development, organizations are confronted with a labyrinth of challenges, far beyond the scope of a singular issue. It's not just about identifying a problem and pairing it with a technological solution. There lies a critical, yet often overlooked step: prioritization.
Consider the diverse array of organizations striving to address global development issues. The challenge isn't merely in selecting a single problem but in discerning which lever to pull for maximal impact. Should technology then be primarily leveraged to navigate these strategic decisions, allocating resources more effectively?
While funding agencies may gravitate towards these macro questions, implementing organizations face more pragmatic concerns. Their focus often shifts towards securing necessary funding, leveraging technology to streamline grant seeking and proposal writing processes. This delineation underscores a fundamental principle: the application of technology, particularly AI, must be tailored not just to the problem at hand, but to the scale and scope of the organization's mission and resources.
Funding agencies are not going to fund implementers to improve their proposal development mechanisms, but they could and will fund efforts to leverage technology (including AI) to address global challenges. To what extent will that funding go to macro questions around levers for maximum impact?
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