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Resist manipulation

Ability to resist manipulation that would decrease trustworthiness, legitimacy or unfairly influence the outcome.

Maturity:
Medium
Importance:
Extreme
Opportunity:
High
Neglectedness:
High
Transnational:
Low

How this is performed now...

  • Process organizers Process organizers anticipate vulnerabilities in processes and do their best to mitigate risk with countermeasures.
  • Citizens' assembly organizers Citizens' assemblies organizers design processes with an understanding of where manipulation is possible and more likely, and develop mitigating strategies, such as by reinforcing the epistemic capabilities of participants before interacting with new information, developing selection algorithms with manipulation resistance, and establishing governance protocols for impartiality of key actors.

Related Resources

Research

Strategy-proofness and Arrow's conditions: Existence and correspondence theorems for voting procedures and social welfare functions

Satterthwaite's landmark 1975 work on strategy-proofness and Arrow's conditions, investigating the relationship between preventing strategic manipulation in voting procedures and satisfying Arrow's impossibility conditions. This foundational work in mechanism design theory demonstrates existence ...
Research

Adversarial testing for Generative AI

Google's guide defining adversarial testing as systematically evaluating ML models against malicious or inadvertently harmful input, covering explicit queries (containing policy-violating language) and implicit queries (seeming harmless but involving sensitive topics). The four-stage workflow inv...
Research

Strategic Classification

Hardt et al. (2015) address classifier manipulation by strategic actors, modeling the problem as a sequential game between classifier designers and individuals seeking favorable classification who may alter attributes to game the system. For natural cost function classes, they developed computati...
Research

The Social Cost of Strategic Classification

Examines how actors modify behavior when being evaluated by algorithms. Builds on a 2015 paper by Hardt and related to a 2020 paper by the same authors
Research

Strategic Classification is Causal Modeling in Disguise

Miller, Milli, and Hardt (2020) reveal a fundamental connection between strategic classification and causal inference, distinguishing between gaming (circumventing the system) and genuine improvement. Their central argument is that designing classifiers that incentivize improvement must inevitabl...
Research

Fair algorithms for selecting citizens’ assemblies

Sortition algorithms have been designed to select participants according to quotas, balancing representativeness, fairness and manipulation resistance (Flanigan, 2021; Baharav, 2024).

Related goals and research questions