There are several web platforms that people use to interact and exchange ideas, such as social networks like Facebook, Twitter, and Google+; Q&A sites like Quora and Yahoo! Answers; and myriad independent fora. However, there is a scarcity of platforms that facilitate discussion of complex subjects where people with divergent views can easily rationalize their points of view using a shared knowledge base, and leverage it towards shared objectives, e.g. to arrive at a mutually acceptable compromise. In this paper, as a first step, we present Widescope, a novel collaborative web platform for catalyzing shared understanding of the US Federal and State budget debates in order to help users reach data-driven consensus about the complex issues involved. It aggregates disparate sources of financial data from different budgets (i.e. from past, present, and proposed) and presents a unified interface using interactive visualizations. It leverages distributed collaboration to encourage exploration of ideas and debate. Users can propose budgets ab-initio, support existing proposals, compare between different budgets, and collaborate with others in real time. We hypothesize that such a platform can be useful in bringing people's thoughts and opinions closer. Toward this, we present preliminary evidence from a simple pilot experiment, using triadic voting (which we also formally analyze to show that is better than hot-or-not voting), that 5 out of 6 groups of users with divergent views (conservatives vs liberals) come to a consensus while aiming to halve the deficit using Widescope. We believe that tools like Widescope could have a positive impact on other complex, data-driven social issues.
翻译:人们使用一些网络平台进行互动和交流思想,例如Facebook、Twitter、Google+等社交网络;Quora和Yahoo等网站;答案;以及各种各样的独立论坛。然而,缺乏便于讨论复杂议题的平台,在这些议题上,持有不同观点的人可以使用共享的知识库来方便地理顺其观点,并以此为共同目标,例如,达成相互接受的妥协。在本文中,作为第一步,我们展示了一个宽广的、创新的协作网络平台,以激发对美国联邦和州预算辩论的共同理解,帮助用户就所涉复杂问题达成数据驱动的共识。它汇集了不同预算(例如过去、现在和拟议的)中不同的财务数据来源,利用互动的可视化来提供一个统一的界面。它利用各种协作来鼓励探索思想和辩论。用户可以提出预算 ab-niciotio,支持现有提案,在不同的预算之间进行比较,并与其他人在现实时间里合作。我们假设这样一个热的平台能够有助于使用户就所涉复杂问题达成数据驱动力共识,而我们则使用简单的三变的实验性观点来更接近于我们。