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Open Access Publications from the University of California

Scholarly Works (8 results)

  • Article
  • Peer Reviewed
Proceedings of the Annual Meeting of the Cognitive Science Society, Volume 44 (2022)
How much information can people gain from being lied to? We propose that people can infer the truth from false messages if two preconditions are met: (1) bigger lies are more costly, and (2) speakers have known, directional deception goals. We tested this with a marble-flipping task in which a judge tried to accurately estimate the number of sampled marbles, while a sender attempted to make the judge over- or underestimate. The sender could produce larger lies about the number of marbles drawn by physically clicking marbles along a lower or higher cost function. We found that judges took into consideration both the senders' goals and costs to correct for bias introduced by senders' lies. Our paradigm allows us to show that a large amount of the variation can be explained by people correcting others' lies based on the lies that they themselves would produce.
    Cover page: Inferring truth from liesCreative Commons 'BY' version 4.0 license
    • Article
    • Peer Reviewed
    Proceedings of the Annual Meeting of the Cognitive Science Society, Volume 43 (2021)
    Do people cater their lies to their own beliefs or others' beliefs? One dominant individual-based account considers lying to be an internal tradeoff between self-interest, norms, and morals. However, recent audience-based accounts suggests that lying behavior can be better explained within a communicative framework, wherein speakers consider others' beliefs to design plausible lies---highlighting the role of theory-of-mind in strategic lying. We tease apart these accounts by examining human lying behavior in a novel asymmetric, dyadic lying game in which speakers' beliefs differ from those they ascribe to their audience. We compare participants' average reported lie (controlling for the truth) across conditions that manipulated the player's and the audience's beliefs. We find that people spontaneously tune their lies to beliefs unique to their audience, more than to their own beliefs. These results support the audience-based account of lying: estimates of how listeners will respond determine how people decide to lie.
      Cover page: Lies are crafted to the audienceCreative Commons 'BY' version 4.0 license
      • Article
      • Peer Reviewed
      UC San Diego Previously Published Works (2023)
      How do people detect lies from the content of messages, and design lies that go undetected? Lying requires strategic reasoning about how others think and respond. We propose a unified framework underlying lie design and detection, formalized as recursive social reasoning. Senders design lies by inferring the likelihood the receiver detects potential lies; receivers detect lies by inferring if and how the sender would lie. Under this framework, we can predict the rate and content of lies people produce, and which lies are detected. In Experiment 1, we show that people calibrate the extremeness of their lies and what lies they detect to beliefs about goals and the statistics of the world. In Experiment 2, we present stronger diagnostic evidence for the function of social reasoning in lying: people cater their lies to their audience, even when their audience's beliefs differ from their own. We conclude that recursive and rational social reasoning is a key cognitive process underlying how people communicate in adversarial settings. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
        • Article
        • Peer Reviewed
        Proceedings of the Annual Meeting of the Cognitive Science Society, Volume 41 (2019)
        The human ability to deceive others and detect deception haslong been tied to theory of mind. We make a stronger argu-ment: in order to be adept liars – to balance gain (i.e. maxi-mizing their own reward) and plausibility (i.e. maintaining arealistic lie) – humans calibrate their lies under the assumptionthat their partner is a rational, utility-maximizing agent. Wedevelop an adversarial recursive Bayesian model that aims toformalize the behaviors of liars and lie detectors. We comparethis model to (1) a model that does not perform theory of mindcomputations and (2) a model that has perfect knowledge ofthe opponent’s behavior. To test these models, we introduce anovel dyadic, stochastic game, allowing for quantitative mea-sures of lies and lie detection. In a second experiment, we varythe ground truth probability. We find that our rational modelsqualitatively predict human lying and lie detecting behaviorbetter than the non-rational model. Our findings suggest thathumans control for the extremeness of their lies in a mannerreflective of rational social inference. These findings provide anew paradigm and formal framework for nuanced quantitativeanalysis of the role of rationality and theory of mind in lyingand lie detecting behavior.
          Cover page: Designing good deception: Recursive theory of mind in lying and lie detection
          • Article
          Proceedings of the Annual Meeting of the Cognitive Science Society, Volume 40 (2018)
          When learning about the world, we develop mental represen-tations or concepts for things we have never seen. At the sametime, we also develop representations for things that are similarto what we have experienced. Traditionally, similarity-basedand rule-based systems have been used as distinct models tocapture conceptual representation. However, it seems implau-sible that we do not flexibly deploy both systems. Whetherboth systems can be used simultaneously to represent compo-nents of a single concept is an open empirical question. Oneexample suggesting that the use of both systems is possible isthe concept of a ZEBRA , which looks like a horse but striped.Using an artificial concept learning task, we test whether peo-ple can combine similarity and rules compositionally in orderto represent concepts. Our results suggest that people are ableto compose similarity and rules when mentally representing asingle concept.
            Cover page: Adults use gradient similarity information in compositional rules
            • Thesis
            • Peer Reviewed
            UC San Diego Electronic Theses and Dissertations (2023)

            People naturally embed themselves within communities. In doing so, people choose not only whether to cooperate with people in their social environment but how to cooperate. Here, I propose that people can produce strategic behaviors as a product of pursuing their goals while predicting how others may interact. Furthermore, individuals' socially motivated behaviors scale up to drive emergent collective behaviors. By examining these behaviors, this dissertation bridges interactions between different social hierarchies---individuals, dyads, and collectives---via recursive social cognitive mechanisms. More specifically, each chapter will address the following questions. Chapter 1 asks how parallel individuals' goals can be used to scaffold how we understand communities' behavior. Here I analyze how individual scientists' decisions, by combining network and topic space measures, coalesce to determine how integrated the cognitive science community has become in the last two decades. Chapter 2 tests how individuals deceive with lies via recursive social reasoning and strategic planning to dodge others' enforcement. Chapter 3 considers how enforcers adapt their expectations about what interpretation to take away from messages when they suspect defectors. This shift in how people interpret messages can then lead to runaway effects at the collective level, such as imprecise approximations about the truth and cooperative speakers also being induced to lie for their messages to be understood accurately. Overall, this work lays the foundation toward a unifying theory of people's and collective's behaviors arising from individualistic goals in social environments.

              Cover page: Strategic behavior in social environments
              • Article
              • Peer Reviewed
              Proceedings of the Annual Meeting of the Cognitive Science Society, Volume 45 (2023)
              Data visualizations are powerful tools for communicating quantitative information. While prior work has focused on how experts design informative graphs, little is known about the intuitions non-experts have about what makes a graph effective for communicating a specific message. In the current study, we asked participants (N=398) which of eight graphs would be most useful for answering a particular question, where all graphs were generated from the same dataset but varied in how the data were arranged. We tested the degree to which participants based their decisions on sensitivity to how easily other participants (N=542) would be able to answer that question with that graph. Our results suggest that while people were biased towards graphs that were at least minimally informative (i.e., contained the relevant variables), their decisions did not necessarily reflect sensitivity to more graded but systematic variation in actual graph comprehensibility.
                Cover page: How do communicative goals guide which data visualizations people think are effective?Creative Commons 'BY' version 4.0 license
                • Article
                • Peer Reviewed
                Proceedings of the Annual Meeting of the Cognitive Science Society, Volume 42 (2020)
                Is cognitive science interdisciplinary or multidisciplinary? Wecontribute to this debate by examining the authorship struc-ture and topic similarity of contributions to the Cognitive Sci-ence Society from 2000 to 2019. We compare findings fromCogSci to abstracts from the Vision Science Society over thesame time frame. Our analysis focuses on graph theoretic fea-tures of the co-authorship network—edge density, transitivity,and maximum subgraph size—as well as clustering within thetopic space of CogSci contributions. We also combine struc-tural and semantic information with an analysis of homophily.We validate this approach by predicting new collaborations inthis year’s CogSci proceedings. Our results suggest that cog-nitive science has become increasingly interdisciplinary in thelast 19 years. More broadly, we argue that a formal quantita-tive approach which combines structural co-authorship infor-mation and semantic topic analysis provides inroads to ques-tions about the level of interdisciplinary collaboration in thecognitive science community.
                  Cover page: Formalizing Interdisciplinary Collaboration in the CogSci CommunityCreative Commons 'BY' version 4.0 license
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