EAGER: Programming the Crowd

EAGER：对人群进行编程

• 批准号: 1144520
• 负责人: Emery Berger
• 金额: $ 15万
• 依托单位: University of Massachusetts Amherst
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-01-01 至 2015-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1144520&HistoricalAwards=false
• 关键词: EAGER; Programming; Crowd

People can perform with ease many tasks that remain difficult or impossible for computers, including vision, motion planning, and natural language understanding. New "crowdsourcing" platforms like Amazon's Mechanical Turk make it easier than ever to harness human computational power by streamlining job posting, tracking, and payment for workers. However, the lack of automation means that crowdsourcing currently does not scale up. Low quality results must be filtered out, but checking human computations can be difficult. Economic incentives and anonymity expose crowdsourcing to fraud. Deciding how much to pay workers for particular tasks and how many workers to hire remains an art.This project introduces crowdprogramming, an approach that fully integrates human and digital computation. In crowdprogramming, humans are modeled as function calls in a standard programming language. This approach lets programmers focus on programming logic, while the crowdprogramming runtime system manages the critical tradeoffs between cost, time, and data quality. Crowdprogramming will dramatically lower the barriers to harnessing human computational power. It will enable a rich new class of applications that divide labor between digital and human computations, where computers and humans do the work each does best. It will enable complex orchestration of human computations, automatically control quality to maintain high accuracy and avoid fraud, and schedule tasks and adjust payments to maximize speed while staying within budget. By streamlining the incorporation of human labor into computation, crowdprogramming has the potential to add an entirely new job sector to the economy.

人类可以轻松地完成许多对计算机来说仍然困难或不可能完成的任务，包括视觉、运动规划和自然语言理解。亚马逊（Amazon）的Mechanical Turk等新型“众包”平台通过简化招聘、跟踪和员工薪酬，使利用人类的计算能力变得比以往任何时候都更容易。然而，缺乏自动化意味着众包目前还没有扩大规模。低质量的结果必须过滤掉，但检查人工计算可能很困难。经济激励和匿名性使众包容易受到欺诈。决定为特定任务支付多少工资以及雇佣多少工人仍然是一门艺术。这个项目引入了大众编程，这是一种将人类和数字计算完全结合在一起的方法。在众包编程中，人类被建模为标准编程语言中的函数调用。这种方法让程序员专注于编程逻辑，而众包编程运行时系统管理成本、时间和数据质量之间的关键权衡。大众编程将大大降低利用人类计算能力的障碍。它将催生一种丰富的新型应用程序，在数字计算和人工计算之间进行分工，在这种情况下，计算机和人类各做各擅长的工作。它将实现复杂的人工计算编排，自动控制质量以保持高精度并避免欺诈，并安排任务和调整付款以最大限度地提高速度，同时保持在预算范围内。通过简化人类劳动与计算的结合，众包编程有可能为经济增加一个全新的就业领域。