Lack of employment opportunities contributes to the persistence of poverty throughout the world. At the same time, crowdsourced human computation can potentially provide work to large numbers of people, without imposing specialized skill requirements. In this study we investigate the feasibility of connecting people in rural areas to human computation employment with a pilot-scale project, and assess the way they use the income they receive to determine if this is an effective poverty-alleviation strategy. We find that workers in a rural Kenyan village are able to complete several example task types; using a simplified human computation platform called PulaCloud, they completed approximately 100,000 image classification tasks for a bioinformatics research project. The income they received was significantly more than that available from limited local employment options, and they spent it almost exclusively on basic needs, educational expenses, and productive investments, strongly suggesting that this can be an effective tool in the fight against poverty. We emphasize that this is not an aid-based approach to economic development; rather, workers are engaged as producers in the global knowledge economy and are paid for making contributions to scientific research.