Kevin O'Neill

People more frequently select norm-violating factors, relative to norm- conforming ones, as the cause of some outcome. Until recently, this abnormal-selection effect has been studied using retrospective vignette-based paradigms. We use a novel set of video stimuli to investigate this effect for prospective causal judgments—i.e., judgments about the cause of some future outcome. Four experiments show that people more frequently select norm- violating factors, relative to norm-conforming ones, as the cause of some future outcome. We show that the abnormal-selection effects are not primarily explained by the perception of agency (Experiment 4). We discuss these results in relation to recent efforts to model causal judgment.

This article examines methodological and ethical issues of ethnographic research through the lens of Emmanuel Levinas's philosophy. Levinas is relevant to a critical analysis of ethnographic methods because his philosophy turns on the problematic relationship between self and other, among other important problems that define and guide contemporary anthropological research, including questions of responsibility, justice, and solidarity. This article utilizes Levinas's philosophy to outline a phenomenology of the “doing” of fieldwork, emphasizing the contingency of face-to-face encounters over controlled research design. This account provides a basis for going beyond the polarized opposition between objective and subjective ethnographic approaches. Levinas allows for an ethically informed ethnography premised upon an acknowledgement of risk and uncertainity over researcher control or reflexivity. Providing a handful of concrete examples, the article argues that critical self-reflection about the fundamental face-to-face dimension of fieldwork is central to ethnography's ethical possibilities.

Abstract:This visual essay invites renewed reflection on the iconography of the people. In the spring of 2020, Guatemala's President Alejandro Giammattei prohibited citizens from leaving their homes to help contain the spread of the novel coronavirus known as Covid-19. Doing little to manage the spread of the virus, these curfew events gave new aesthetic and political meaning to a familiar visual genre: photographs of empty streets. For more than a century, and especially in the summer of 2020, images of crowds and mass protests have provided both governments on the one hand, and protesting multitudes on the other with an aesthetic representation of the people. But this interest in collective assemblies has tended to engage only one side of the equation. To fully appreciate the visual power of the people, it is also necessary to understand those images from which people are strikingly absent.

A well-ingrained and recommended engineering practice in safety-critical software systems is to separate safety concerns from other aspects of the system. Along these lines, there have been calls for operating systems that implement ethical controls in an ethical layer separate from, and not amenable to tampering by, developers and modules in higher-level intelligence or cognition layers. There have been no implementations that demonstrate such a marshalling of ethical principles into an ethical layer. To address this, we present three different tracks for implementing such systems, and offer a prototype implementation of the third track. We end by addressing objections to our approach.

How do people evaluate causal relationships? Do they just consider what actually happened, or do they also consider what could have counterfactually happened? Using eye tracking and Gaussian process modeling, we investigated how people mentally simulated past events to judge what caused the outcomes to occur. Participants played a virtual ball‐shooting game and then—while looking at a blank screen—mentally simulated (a) what actually happened, (b) what counterfactually could have happened, or (c) what caused the outcome to happen. Our findings showed that participants moved their eyes in patterns consistent with the actual or counterfactual events that they mentally simulated. When simulating what caused the outcome to occur, participants moved their eyes consistent with simulations of counterfactual possibilities. These results favor counterfactual theories of causal reasoning, demonstrate how eye movements can reflect simulation during this reasoning and provide a novel approach for investigating retrospective causal reasoning and counterfactual thinking.