• Skip to main content
  • Skip to primary sidebar
AAAI

AAAI

Association for the Advancement of Artificial Intelligence

    • AAAI

      AAAI

      Association for the Advancement of Artificial Intelligence

  • About AAAIAbout AAAI
    • AAAI Officers and Committees
    • AAAI Staff
    • Bylaws of AAAI
    • AAAI Awards
      • Fellows Program
      • Classic Paper Award
      • Dissertation Award
      • Distinguished Service Award
      • Allen Newell Award
      • Outstanding Paper Award
      • Award for Artificial Intelligence for the Benefit of Humanity
      • Feigenbaum Prize
      • Patrick Henry Winston Outstanding Educator Award
      • Engelmore Award
      • AAAI ISEF Awards
      • Senior Member Status
      • Conference Awards
    • AAAI Resources
    • AAAI Mailing Lists
    • Past AAAI Presidential Addresses
    • Presidential Panel on Long-Term AI Futures
    • Past AAAI Policy Reports
      • A Report to ARPA on Twenty-First Century Intelligent Systems
      • The Role of Intelligent Systems in the National Information Infrastructure
    • AAAI Logos
    • News
  • aaai-icon_ethics-diversity-line-yellowEthics & Diversity
  • Conference talk bubbleConferences & Symposia
    • AAAI Conference
    • AIES AAAI/ACM
    • AIIDE
    • IAAI
    • ICWSM
    • HCOMP
    • Spring Symposia
    • Summer Symposia
    • Fall Symposia
    • Code of Conduct for Conferences and Events
  • PublicationsPublications
    • AAAI Press
    • AI Magazine
    • Conference Proceedings
    • AAAI Publication Policies & Guidelines
    • Request to Reproduce Copyrighted Materials
  • aaai-icon_ai-magazine-line-yellowAI Magazine
    • Issues and Articles
    • Author Guidelines
    • Editorial Focus
  • MembershipMembership
    • Member Login
    • Developing Country List
    • AAAI Chapter Program

  • Career CenterCareer Center
  • aaai-icon_ai-topics-line-yellowAITopics
  • aaai-icon_contact-line-yellowContact

Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 35 / No. 6: AAAI-21 Technical Tracks 6

Incentivizing Truthfulness Through Audits in Strategic Classification

February 1, 2023

Download PDF

Authors

Andrew Estornell

Washington University in St Louis


Sanmay Das

George Mason University


Yevgeniy Vorobeychik

Washington University in St. Louis


DOI:

10.1609/aaai.v35i6.16674


Abstract:

In many societal resource allocation domains, machine learning methods are increasingly used to either score or rank agents in order to decide which ones should receive either resources (e.g., homeless services) or scrutiny (e.g., child welfare investigations) from social services agencies. An agency's scoring function typically operates on a feature vector that contains a combination of self-reported features and information available to the agency about individuals or households. This can create incentives for agents to misrepresent their self-reported features in order to receive resources or avoid scrutiny, but agencies may be able to selectively audit agents to verify the veracity of their reports. We study the problem of optimal auditing of agents in such settings. When decisions are made using a threshold on an agent's score, the optimal audit policy has a surprisingly simple structure, uniformly auditing all agents who could benefit from lying. While this policy can, in general be hard to compute because of the difficulty of identifying the set of agents who could benefit from lying given a complete set of reported types, we also present sufficient conditions under which it is tractable. We show that the scarce resource setting is more difficult, and exhibit an approximately optimal audit policy in this case. In addition, we show that in either setting verifying whether it is possible to incentivize exact truthfulness is hard even to approximate. However, we also exhibit sufficient conditions for solving this problem optimally, and for obtaining good approximations.

Topics: AAAI

Primary Sidebar

HOW TO CITE:

Andrew Estornell||Sanmay Das||Yevgeniy Vorobeychik Incentivizing Truthfulness Through Audits in Strategic Classification Proceedings of the AAAI Conference on Artificial Intelligence (2021) 5347-5354.

Andrew Estornell||Sanmay Das||Yevgeniy Vorobeychik Incentivizing Truthfulness Through Audits in Strategic Classification AAAI 2021, 5347-5354.

Andrew Estornell||Sanmay Das||Yevgeniy Vorobeychik (2021). Incentivizing Truthfulness Through Audits in Strategic Classification. Proceedings of the AAAI Conference on Artificial Intelligence, 5347-5354.

Andrew Estornell||Sanmay Das||Yevgeniy Vorobeychik. Incentivizing Truthfulness Through Audits in Strategic Classification. Proceedings of the AAAI Conference on Artificial Intelligence 2021 p.5347-5354.

Andrew Estornell||Sanmay Das||Yevgeniy Vorobeychik. 2021. Incentivizing Truthfulness Through Audits in Strategic Classification. "Proceedings of the AAAI Conference on Artificial Intelligence". 5347-5354.

Andrew Estornell||Sanmay Das||Yevgeniy Vorobeychik. (2021) "Incentivizing Truthfulness Through Audits in Strategic Classification", Proceedings of the AAAI Conference on Artificial Intelligence, p.5347-5354

Andrew Estornell||Sanmay Das||Yevgeniy Vorobeychik, "Incentivizing Truthfulness Through Audits in Strategic Classification", AAAI, p.5347-5354, 2021.

Andrew Estornell||Sanmay Das||Yevgeniy Vorobeychik. "Incentivizing Truthfulness Through Audits in Strategic Classification". Proceedings of the AAAI Conference on Artificial Intelligence, 2021, p.5347-5354.

Andrew Estornell||Sanmay Das||Yevgeniy Vorobeychik. "Incentivizing Truthfulness Through Audits in Strategic Classification". Proceedings of the AAAI Conference on Artificial Intelligence, (2021): 5347-5354.

Andrew Estornell||Sanmay Das||Yevgeniy Vorobeychik. Incentivizing Truthfulness Through Audits in Strategic Classification. AAAI[Internet]. 2021[cited 2023]; 5347-5354.


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

We use cookies on our website to give you the most relevant experience by remembering your preferences and repeat visits. By clicking “Accept All”, you consent to the use of ALL the cookies. However, you may visit "Cookie Settings" to provide a controlled consent.
Cookie SettingsAccept All
Manage consent

Privacy Overview

This website uses cookies to improve your experience while you navigate through the website. Out of these, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may affect your browsing experience.
Necessary
Always Enabled
Necessary cookies are absolutely essential for the website to function properly. These cookies ensure basic functionalities and security features of the website, anonymously.
CookieDurationDescription
cookielawinfo-checkbox-analytics11 monthsThis cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Analytics".
cookielawinfo-checkbox-functional11 monthsThe cookie is set by GDPR cookie consent to record the user consent for the cookies in the category "Functional".
cookielawinfo-checkbox-necessary11 monthsThis cookie is set by GDPR Cookie Consent plugin. The cookies is used to store the user consent for the cookies in the category "Necessary".
cookielawinfo-checkbox-others11 monthsThis cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Other.
cookielawinfo-checkbox-performance11 monthsThis cookie is set by GDPR Cookie Consent plugin. The cookie is used to store the user consent for the cookies in the category "Performance".
viewed_cookie_policy11 monthsThe cookie is set by the GDPR Cookie Consent plugin and is used to store whether or not user has consented to the use of cookies. It does not store any personal data.
Functional
Functional cookies help to perform certain functionalities like sharing the content of the website on social media platforms, collect feedbacks, and other third-party features.
Performance
Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors.
Analytics
Analytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics the number of visitors, bounce rate, traffic source, etc.
Advertisement
Advertisement cookies are used to provide visitors with relevant ads and marketing campaigns. These cookies track visitors across websites and collect information to provide customized ads.
Others
Other uncategorized cookies are those that are being analyzed and have not been classified into a category as yet.
SAVE & ACCEPT