Philip Pärnamets

How the polls can be both spot on and dead wrong: using choice blindness to shift political attitudes and voter intentions.

Political candidates often believe they must focus their campaign efforts on a small number of swing voters open for ideological change. Based on the wisdom of opinion polls, this might seem like a good idea. But do most voters really hold their political attitudes so firmly that they are unreceptive to persuasion? We tested this premise during the most recent general election in Sweden, in which a left- and a right-wing coalition were locked in a close race. We asked our participants to state their voter intention, and presented them with a political survey of wedge issues between the two coalitions. Using a sleight-of-hand we then altered their replies to place them in the opposite political camp, and invited them to reason about their attitudes on the manipulated issues. Finally, we summarized their survey score, and asked for their voter intention again. The results showed that no more than 22% of the manipulated replies were detected, and that a full 92% of the participants accepted and endorsed our altered political survey score. Furthermore, the final voter intention question indicated that as many as 48% (±9.2%) were willing to consider a left-right coalition shift. This can be contrasted with the established polls tracking the Swedish election, which registered maximally 10% voters open for a swing. Our results indicate that political attitudes and partisan divisions can be far more flexible than what is assumed by the polls, and that people can reason about the factual issues of the campaign with considerable openness to change.

Biasing moral decisions by exploiting the dynamics of eye gaze

Significance Where people look generally reflects and reveals their moment-by-moment thought processes. This study introduces an experimental method whereby participants’ eye gaze is monitored and information about their gaze is used to change the timing of their decisions. Answers to difficult moral questions such as “Is murder justifiable?” can be influenced toward random alternatives based on looking patterns alone. We do this without presenting different arguments or response frames, as in other techniques of persuasion. Thus, the process of arriving at a moral decision is not only reflected in a participant’s eye gaze but can also be determined by it. Eye gaze is a window onto cognitive processing in tasks such as spatial memory, linguistic processing, and decision making. We present evidence that information derived from eye gaze can be used to change the course of individuals’ decisions, even when they are reasoning about high-level, moral issues. Previous studies have shown that when an experimenter actively controls what an individual sees the experimenter can affect simple decisions with alternatives of almost equal valence. Here we show that if an experimenter passively knows when individuals move their eyes the experimenter can change complex moral decisions. This causal effect is achieved by simply adjusting the timing of the decisions. We monitored participants’ eye movements during a two-alternative forced-choice task with moral questions. One option was randomly predetermined as a target. At the moment participants had fixated the target option for a set amount of time we terminated their deliberation and prompted them to choose between the two alternatives. Although participants were unaware of this gaze-contingent manipulation, their choices were systematically biased toward the target option. We conclude that even abstract moral cognition is partly constituted by interactions with the immediate environment and is likely supported by gaze-dependent decision processes. By tracking the interplay between individuals, their sensorimotor systems, and the environment, we can influence the outcome of a decision without directly manipulating the content of the information available to them.

Outline of a sensory-motor perspective on intrinsically moral agents

We propose that moral behaviour of artificial agents could (and should) be intrinsically grounded in their own sensory-motor experiences. Such an ability depends critically on seven types of competencies. First, intrinsic morality should be grounded in the internal values of the robot arising from its physiology and embodiment. Second, the moral principles of robots should develop through their interactions with the environment and with other agents. Third, we claim that the dynamics of moral (or social) emotions closely follows that of other non-social emotions used in valuation and decision making. Fourth, we explain how moral emotions can be learned from the observation of others. Fifth, we argue that to assess social interaction, a robot should be able to learn about and understand responsibility and causation. Sixth, we explain how mechanisms that can learn the consequences of actions are necessary for a robot to make moral decisions. Seventh, we describe how the moral evaluation mechanisms outlined can be extended to situations where a robot should understand the goals of others. Finally, we argue that these competencies lay the foundation for robots that can feel guilt, shame and pride, that have compassion and that know how to assign responsibility and blame.

False beliefs and confabulation can lead to lasting changes in political attitudes.

In times of increasing polarization and political acrimony, fueled by distrust of government and media disinformation, it is ever more important to understand the cognitive mechanisms behind political attitude change. In two experiments, we present evidence that false beliefs about one’s own prior attitudes and confabulatory reasoning can lead to lasting changes in political attitudes. In Experiment 1 (N = 140), participants stated their opinions about salient political issues, and using the Choice Blindness Paradigm we covertly altered some of their responses to indicate an opposite position. In the first condition, we asked the participants to immediately verify the manipulated responses, and in the second, we also asked them to provide underlying arguments behind their attitudes. Only half of the manipulations were corrected by the participants. To measure lasting attitude change, we asked the participants to rate the same issues again later in the experiment, as well as one week after the first session. Participants in both conditions exhibited lasting shifts in attitudes, but the effect was considerably larger in the group that confabulated supporting arguments. We fully replicated these findings in Experiment 2 (N = 232). In addition, we found that participants’ analytical skill correlated with their correction of the manipulation, whereas political involvement did not. This study contributes to the understanding of how confabulatory reasoning and self-perceptive processes can interact in lasting attitude change. It also highlights how political expressions can be both stable in the context of everyday life, yet flexible when argumentative processes are engaged.

GIRL special issue introduction

The Lund conference series on Games, Interaction, Reasoning, Learning and Semantics began in 2012. Two conferences were organized in 2012 and 2013, under the denomination of Lund Conference on Games, Interactive Rationality and Learning (GIRL@Lund), before it changed for the third, to become the Lund Conference on Games, Interaction, Reasoning, Learning and Semantics (GIRLS@Lund) in 2014, when it was also decided that the series would become bi-annual, and resume in 2016. A brief history of the conference series will illustrate its purpose and how it evolved over time, as well as serve as a first thematic introduction to the papers in this special issue. The idea of starting the conference series arose from discussions between research groups at the Department of Philosophy at the University of Lund and the Center for Formal Epistemology at Carnegie-Mellon University. The first call almost took the form of a manifesto. It insisted that the methods of formal philosophy, with their increasing reliance on simulations and empirical tests, brought the field closer to computer science, cognitive science and quantitative social sciences, and that the time was ripe for showcasing the cross-disciplinary potential inherent in this development. The first GIRL conference called for contributions in the areas of learning-theoretic models of inquiry, network-theoretic

Pupil dilation tracks the dynamics of mnemonic interference resolution

Mnemonic interference refers to the inability to retrieve a goal-relevant memory due to interference from goal-irrelevant memories. Understanding the causes of such interference and how it is overcome has been a central goal in the science of memory for more than a century. Here, we shed new light on this fundamental issue by tracking participants’ pupil response when they encode and retrieve memories in the face of competing goal-irrelevant memories. We show that pupil dilation systematically increased in accordance with interference from competing memory traces when participants retrieved previously learned information. Moreover, our results dissociate two main components in the pupillary response signal: an early component, which peaked in a time window where the pupillary waveform on average had its maximum peak, and a late component, which peaked towards the end of the retrieval task. We provide evidence that the early component is specifically modulated by the cognitive effort needed to handle interference from competing memory traces whereas the late component reflects general task engagement. This is the first demonstration that mnemonic interference resolution can be tracked online in the pupil signal and offers novel insight into the underlying dynamics.