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Improving Access to Justice with Legal Chatbots

Author

Listed:
  • Marc Queudot

    (PK-4935, 201 Avenue du President-Kennedy, Université du Québec à Montréal UQAM, Montreal, QC H2X 3Y7, Canada
    600 Rue De la Gauchetière Ouest, National Bank of Canada, Montréal, QC H3B 4L2, Canada)

  • Éric Charton

    (600 Rue De la Gauchetière Ouest, National Bank of Canada, Montréal, QC H3B 4L2, Canada)

  • Marie-Jean Meurs

    (PK-4935, 201 Avenue du President-Kennedy, Université du Québec à Montréal UQAM, Montreal, QC H2X 3Y7, Canada)

Abstract

On average, one in three Canadians will be affected by a legal problem over a three-year period. Unfortunately, whether it is legal representation or legal advice, the very high cost of these services excludes disadvantaged and most vulnerable people, forcing them to represent themselves. For these people, accessing legal information is therefore critical. In this work, we attempt to tackle this problem by embedding legal data in a conversational interface. We introduce two dialog systems (chatbots) created to provide legal information. The first one, based on data from the Government of Canada, deals with immigration issues, while the second one informs bank employees about legal issues related to their job tasks. Both chatbots rely on various representations and classification algorithms, from mature techniques to novel advances in the field. The chatbot dedicated to immigration issues is shared with the research community as an open resource project.

Suggested Citation

  • Marc Queudot & Éric Charton & Marie-Jean Meurs, 2020. "Improving Access to Justice with Legal Chatbots," Stats, MDPI, vol. 3(3), pages 1-20, September.
    • Handle: RePEc:gam:jstats:v:3:y:2020:i:3:p:23-375:d:409101
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    References listed on IDEAS

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    1. Monya Baker, 2016. "1,500 scientists lift the lid on reproducibility," Nature, Nature, vol. 533(7604), pages 452-454, May.
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    Cited by:

    1. Ahmed Izzidien, 2023. "Using the interest theory of rights and Hohfeldian taxonomy to address a gap in machine learning methods for legal document analysis," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-15, December.

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