RESEARCH | julian-de-freitas

Ethical Intelligence

If we are to understand what makes human intelligence unique, we need to demystify high-level thought and intuition (aka ‘common sense’). My research program focuses on the case study of what I call ethical intelligence. I study (§1) the perceptual and cognitive abilities that underlie our capacity to coordinate in social life, such as agreeing on a time and place to meet, bringing complementary fare to a potluck dinner, or dividing responsibilities on a research project, (§2) how the logic of coordination shapes public opinion about new technologies, such as whether to program certain decision rules into driverless cars, and (§3) how ethical considerations infuse everyday concepts related to well-being, such as whether we are happy, being true to ourselves, and leading meaningful lives. At a broad level, studying ethical intelligence can help us understand how to engender stable institutions in which people coordinate for the greater good, as well as how to live better lives. I approach these questions using various methods from experimental psychology and machine learning, while drawing on theoretical insights from game theory, evolutionary biology, and philosophy.

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The True Self and Moral Essentialism

Representations of and beliefs about the concept of “a self” vary across cultures, perspectives (first vs. third), and individuals. Yet my collaborators and I have found evidence suggesting that people exhibit a robust, invariant tendency to believe that deep inside every individual there is a “good true self” calling them to behave in a morally virtuous manner. We propose that this belief arises from a general cognitive tendency known as psychological essentialism.

De Freitas, J., & Cikara, M, Grossmann, I., & Schlegel, R. (2018). Moral goodness is the essence of personal identity. Trends in Cognitive Sciences, 22(9), 739–740. [Original letter by Starmans & Bloom.] **Review**
De Freitas, J., Cikara, M., Grossmann, I., & Schlegel, R. (2017). Origins of the belief in morally good true selves. Trends in Cognitive Sciences, 21(9), 634–636. **Review**
De Freitas, J., & Cikara, M. (2018). Deep down my enemy is good: Thinking about the true self reduces intergroup bias. Journal of Experimental Social Psychology, 74, 307–316 .
De Freitas, J., Sarkissian, H., Newman, G. E., Grossman, I., De Brigard, F., Luco, A., & Knobe, J. (2018). Consistent belief in a good true self in misanthropes and three interdependent cultures. Cognitive Science, 42, 134–160. [supp. materials].
De Freitas, J., Tobia, K., Newman, J. E., & Knobe, J. (2017). Normative judgments and individual essence. Cognitive Science, 1551–6709.
Newman, J. E., De Freitas, J., and Knobe, J. (2015). Beliefs about the true self explain asymmetries based on moral judgment. Cognitive Science, 39(1), 96–125.
Phillips, J., De Freitas, J., Mott, C., Gruber, J. & Knobe, J. (2017). True happiness: The role of morality in the concept of happiness. Journal of Experimental Psychology: General, 146(2),165–181.

Common Knowledge and Recursive Mentalizing

Most work in psychology has studied the representation of other's beliefs about the world, aka theory of mind. My collaborators and I have investigated how representations of knowledge -- including knowledge that others have about our own beliefs (e.g., you know X, I know that you know X), and common knowledge (you know X, I know that you know X, you know that I know that you know X, ad infinitum) -- affect diverse social phenomena such as the bystander effect and perceptions of charitability. We propose that -- rather than being represented as an explicit, multiply nested proposition -- common knowledge may be a distinctive cognitive state, corresponding to the sense that something is public or "out there".

De Freitas, J., Thomas, K. A., DeScioli, P., & Pinker, S. (2019) Common knowledge, coordination, and strategic mentalizing in human social life. Proceedings of the National Academy of Sciences. **Review**
De Freitas, J.*, Thomas, K. A.*, DeScioli, P., & Pinker, S. (2016) Recursive mentalizing and common knowledge in the bystander effect. Journal of Experimental Psychology: General, 145(5), 621–629.
De Freitas, J., DeScioli, P., Thomas, K. A., & Pinker, S. (2018). Maimonides' Ladder: States of mutual knowledge and the perception of charitability. Journal of Experimental Psychology: General.

Ethics of Autonomous Machines

How do we create complex autonomous systems that have 'ethically acceptable' behavior? The current work considers the case study of autonomous vehicles, since for the first time in history they are a truly autonomous system that is beginning to operate in populated environments. Ethics is relevant to how they should be programmed, regulated, be perceived.

De Freitas, J., Censi, A., Smith, B. W., Di Lillo, L., Anthony, S. E., & Frazzoli, E. From driverless dilemmas to more practical common-sense tests for automated vehicles. Proceedings of the National Academy of Sciences.
De Freitas, J., Anthony, S. A., Censi, A., & Alvarez, G. A. (2020). Doubting driverless dilemmas. Perspectives on Psychological Science.
De Freitas, J., & Cikara, M. (2021). Deliberately prejudiced self-driving vehicles elicit the most outrage. Cognition. [supp. materials]

Origins and Variability of Animate Attention

This work explores the idea that complex behaviors, like animate attention, can be explained by the interaction of a world model (which predicts future states of the world) and an intrinsically-motivated self model (which motivates the agent to spend time predicting parts of the world with certain features). In particular, we find that paying attention to aspects of the environment where one is continuing to learn new information (which we term progress curiosity) is a particularly powerful way to give rise to human-like behaviors like animate attention, without the need for built-in modules or hand-written rules. This work utilizes a 3D, photorealistic environment that we created for measuring artificial and human agents-- either while they wear mobile eye trackers or virtual reality goggles. We also run setups in which the displays are conveyed using real robots.

Kim, K.H. Sano, M., De Freitas, J., Haber, N., & Yamins, D. L. K. (2020). Active world model learning with progress curiosity. International Conference on Machine Learning (ICML). [ICLR workshop submission; CogSci Proceedings Submission].
Sano M., De Freitas J., Haber N., & Yamins D. L. K. (2020). Learning in social environments with curious neural agents. Proceedings of the 42nd Annual Conference of the Cognitive Science Society.

Kim, K. H., Sano, M., De Freitas, J., Yamins, D. L. K., Haber, N. Towards modeling the variability of human attention. International Conference on Learning Representations Workshop.

Models of Moral Judgment

How do people make moral judgments? The present work explores how moral judgment is influenced by perceptual and teleological factors, as well as how moral judgment affects such factors in turn.

De Freitas, J., & Alvarez, G. A. (2018). Your visual system provides all the information you need to make moral judgments about generic visual events. Cognition, 178, 133–146.
De Freitas, J.*, & Johnson, S.G.B*. (2018). Optimality bias in moral judgment. Journal of Experimental Social Psychology, 79, 149–163. [supp. materials]
De Freitas, J., DeScioli, P., Nemirow, J., Massenkoff, M., & Pinker, S. (2017). Kill or die: Moral judgment alters linguistic coding of causality. Journal of Experimental Psychology: Learning, Memory, and Cognition, 43(8), 1173–1182 [supp. materials].

Other Papers

DeScioli, P., Karpoff, R., & De Freitas, J. (2017). Ownership dilemmas: The case of finders versus landowners. Cognitive Science, 41(S3), 502–522.
De Freitas, J., Liverence, B., & Scholl, B. J. (2014). Attentional rhythm: A temporal analogue of object-based attention. Journal of Experimental Psychology: General, 143(1), 71–76.
Prinzing, M., De Freitas, J., & Fredrickson, B. L. The lay concept of a meaningful life: The role of subjective and objective factors in attributions of meaning. PsyArXiv.
De Freitas, J., Myers, N. E., & Nobre, A. C. (2016). Tracking the changing feature of a moving object. Journal of Vision, 16(3), 1–21.
Gan, C., Schwartz, J., Alter, S., Schrimpf, M., Traer, J., De Freitas, J., Bhandwaldar, A., Sano, M., Kim, K. H., Wang, E., Mrowca, D., Lingelbach, M., Curtis, A., Feigelis, K., Haber, N., Gutfreund, D., Cox, D., DiCarlo, J., McDermott, J., Tenenbaum, J., Yamins, D. L. K. ThreeDWorld: A Platform for interactive, multi-modal physical simulation. arxiv. [http://www.threedworld.org/]