Better public policy through natural language information access

  • Authors:
  • Boris Katz;Roger Hurwitz;Jimmy J. Lin;Ozlem Uzuner

  • Affiliations:
  • MIT Artificial Intelligence Laboratory, Cambridge, MA;MIT Artificial Intelligence Laboratory, Cambridge, MA;MIT Artificial Intelligence Laboratory, Cambridge, MA;MIT Artificial Intelligence Laboratory, Cambridge, MA

  • Venue:
  • dg.o '03 Proceedings of the 2003 annual national conference on Digital government research
  • Year:
  • 2003

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Abstract

Federal agencies implement laws passed by the Congress by creating rules and regulations that can be applied in practice. During this process, staffs at the various agencies may review past and current regulations and receive comments from stakeholders and the public regarding the proposed regulations.Putting rulemaking online can increase the public's awareness of the proposed rules and its participation in the process. It can also facilitate staff work. A key factor in realizing these benefits will be the availability of simple, intuitive, and timely access to the empowering legislation, the proposed rules and information regarding them. We propose to provide such access through an information architecture that allows members of the public as well as staff and stakeholders to obtain the texts and information they desire by using everyday language. Over the past decade, we have developed the START and Omnibase systems for natural language question answering and have applied them in a variety of domains. We plan to use these systems and our experience to support online rule making.We note that besides providing information access, these systems can function more proactively, by soliciting feedback from targeted parties or by sending out notifications and information in response to standing queries submitted by the users.