Mata, AndréFerreira, Mário Augusto de Carvalho BotoFiedler, KlausMendonça, Cristina2020-04-152020-04-152020-01http://hdl.handle.net/10451/42847The area of judgment and decision-making became very influential under the heuristics-andbiases research program by revealing that the prevailing economic theories lacked realism: The human being is not, as these theories had assumed, perfectly rational. Instead, people frequently rely on simplified, mostly automatic and unconscious strategies (i.e., heuristics) that enable the human mind, with its limitations, to provide acceptable judgments and decisions, but that can also lead to systematic errors (i.e., biases) under certain conditions. Yet, the judgment and decision-making research itself still neglects essential aspects of reality that can have an important influence on the way people judge and make decisions. Among these aspects is the fact that, as people live in societies, they receive information from, and transmit it to, other people. The main hypothesis explored in the current dissertation is that this social dynamic will lead to a social amplification of bias: As information travels from one person to the next, the message will aggregate individual biases leading to messages that are progressively more biased the further they travel from their source. In four experimental chapters, the social amplification of bias hypothesis was tested using the serial reproduction paradigm. In this paradigm, communication chains are formed using the responses of one participant (e.g., the recall of a text) as the stimuli to be presented to the next participant, thus recreating the social dynamic of receiving and transmitting information in the laboratory. These studies supported the social amplification of bias hypothesis, and did so covering different judgment and decision-making domains (risk perception, illusory correlations, denominator neglect, and cognitive reflection), using different types of response formats (frequency estimates, forced recognition, free recall), andincluding samples from Europe and the US, online and in the lab. The dissertation ends by discussing implications, future research, and potential modelling and debiasing techniques.engSerial reproductionsocial amplificationjudgment and decision-makingheuristics and biasesdoctoral thesis101497687