CoALA: Multi-layered framework for developing and harnessing collective expertise

The wisdom of the collective is increasingly being regarded as a force that can be harnessed for creative problem solving. Collective expertise has been demonstrated to solve problems that have challenged experts for years. However, current platforms are limited to simple models of task distribution and collaboration. There is little technology support for crowdsourcing complex, collaborative, time-critical problems. The issue of training such large, distributed teams also remains a challenge. This proposal seeks to advance the state of the art with a platform to develop and harness multiple layers of collective expertise for collaborative problem solving. This multilayered approach makes it possible to tap into the skills of a large crowd, while simultaneously providing increased levels of trust and expertise through a layer of community sourcing. This enables a high degree of flexibility in finding the right mix of skills for each problem. The platform addresses the challenges of optimal task allocations, schedule and budget management, and efficient performance assessment. Furthermore, the platform supports an apprentice-based training model where the crowdsourcing mechanism is leveraged to provide personalized learning experiences. Phase I will result in a detailed system design and the development of a proof-of-concept prototype to demonstrate feasibility.