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English Choose a language for shopping. Amazon Music Stream millions of songs. Amazon Advertising Find, attract, and engage customers. Amazon Drive Cloud storage from Amazon. Shopbop Designer Fashion Brands. The identity of a conversation partner, as a human or computer, matters. Previous work has found that the mere perceived identity of the partner as computer or human has profound effects, even when actual identity does not Fox et al. Perceived identity is critical to understand, especially from a theoretical perspective, because it gives rise to new processes, expectations of the partner, and effects that do not arise when the partner is always assumed to be human, as in previous work.
This could alter disclosure processes and outcomes in fundamental ways. For example, people often avoid disclosing to others out of a fear of negative evaluation.
Because chatbots do not think or form judgments on their own, people may feel more comfortable disclosing to a chatbot compared to a person, changing the nature of disclosure and its outcomes Lucas et al. As the conversational abilities of chatbots quickly improve Zhang et al. Extant research provides three theoretical frameworks that suggest different potential outcomes.
First, a theoretical emphasis on perceived understanding suggests that disclosure will only have a beneficial impact when the partner is believed to have sufficient emotional capacity to truly understand the discloser, which chatbots inherently cannot. We refer to this as the perceived understanding framework. Second, research on conversational agents and disclosure intimacy, in contrast, suggests that disclosure will be even more beneficial with a chatbot than a human partner, because chatbots encourage more intimate disclosure.
We refer to this as the disclosure processing framework. Third, a media equivalency approach suggests that the effects of disclosure operate in the same way for human and chatbot partners.
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We refer to this as the computers as social actors CASA framework. This occurs because feeling understood creates a sense of social belonging and acceptance, activates areas in the brain associated with connection and reward, and enhances personal goal pursuit Reis et al.
According to this model, the positive effects of feeling understood are mediated by the extent to which disclosers perceive that they are understood. In other words, disclosers need to believe the partner understands them before the positive impact of feeling understood can take place.
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In the case of a chatbot, disclosers know that a chatbot is a computer program that cannot understand them on this deeper level. They may not, then, experience the positive emotional, relational, and psychological effects of feeling understood.
On the other hand, individuals know that another person has the capability of truly understanding them in a way a chatbot cannot, especially who they are and how they experience the world. This may increase perceived understanding, resulting in more positive outcomes for disclosure with a human partner. Perceived Understanding Hypothesis: Because of increased perceived understanding, emotional, relational, and psychological effects will be greater when disclosing to a person than to a chatbot.
A perspective we call the disclosure processing framework emphasizes the advantages that non-human partners may provide compared to human partners. This framework suggests that people will disclose more to chatbots and subsequently experience more positive outcomes. Fears of negative judgment commonly prevent individuals from disclosing deeply to other people. Disclosure intimacy, however, may increase when the partner is a computerized agent rather than another person, because individuals know that computers cannot judge them Lucas et al.
Computerized agents reduce impression management and increase disclosure intimacy compared to human partners in situations in which fears of negative evaluation may be prominent e. If this occurs in all situations, and not just situations that heighten fears of judgment, people may disclose more intimately to a chatbot than they would to a person. This switch to a cognitive nature reduces the intensity and power of the negative emotion Lieberman et al. Disclosure Processing Hypothesis: Due to greater disclosure intimacy and cognitive reappraisal, emotional, relational, and psychological effects will be greater when disclosing to a chatbot than to a person.
This framework suggests that disclosure processes and outcomes will be similar, regardless of whether the partner is a person or a chatbot. A plethora of studies have found that people form perceptions of computerized agents and humans in the same way, even though people consciously know that computers are machines that do not have human personalities.
This occurs not just when the partner is actually a computer, but also when the partner is believed to be a computer von der Putten et al. Across many different types of social situations, people also behave and interact with computers in ways that are common in human-human interactions, applying social norms derived from experiences with other people to interactions with computers.
This tendency is assumed to occur because of mindlessness Langer, We mindlessly apply social scripts to those interactions, behaving in ways that are similar to how we would behave to another person, even while consciously aware that the computer is not a person. Work using fMRIs shows how deeply this tendency runs. Unlike the other two frameworks, this framework suggests that the processes that lead to disclosure benefits, such as perceived understanding, disclosure intimacy, and cognitive reappraisal, should not differ depending on the perceived identity of the conversation partner.
Rather, these processes will unfold in the same way, regardless of whether the partner is a chatbot or a person. Individuals may thus disclose to a chatbot as they do to another person, engage in cognitive reappraisal to the same degree, and feel just as understood, regardless of whether the partner is a chatbot or a person. Equivalence Hypothesis: Perceived understanding, disclosure intimacy, and cognitive reappraisal processes from disclosing to a partner will lead to equivalent emotional, relational, and psychological effects between chatbot and person partners.
In this study, we examined the effects of partner identity chatbot vs. In an experiment, participants were told they would have an online chat conversation with either a chatbot or a person.
In other words, some participants were told that they would have a conversation with a chatbot and some were told they would have a conversation with a person, but in all cases, the partner was a person. Factual disclosures contain objective information about the discloser e. The closest equivalent to our procedure is the expressive writing procedure, in which college students emotionally or factually disclose in writing and psychological outcomes are assessed Smyth, A power analysis with a significance level of.
Participants were recruited from university research participation websites and flyers posted around a university campus.
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A total of participants took part in the study This level of suspicion was lower or on par with other studies employing WoZ methods e. Before the procedure, three undergraduate research assistants, who acted as confederates in the study and interacted with participants, were trained on how to provide validating responses. Training was overseen by a clinical psychologist.
This procedure was reviewed and approved by the university Institutional Review Board.
For the study, a 2 disclosure type: emotional vs. Participants were randomly assigned to be told they would have a conversation with either another person or a chatbot. Participants were also randomly assigned to engage in an emotional conversation, in which they were asked to discuss a current problem they were facing and their deepest feelings about it, or a factual conversation, in which they were asked to describe their schedule for the day and the upcoming week in an objective way, without mentioning their feelings or emotions Birnbaum et al.
Participants then engaged in an online chat conversation for 25 minutes with a trained confederate, who was blind to whether participants thought they were talking to a chatbot or to a person, but not to whether participants were asked to engage in emotional or factual disclosure. In the emotional conversations, the confederate provided the participant with validating responses and asked questions to probe and to elicit more disclosure. In the factual conversations, the confederate responded positively and with interest e. The chat interface utilized was Chatplat, an online chat platform enabling real-time chat conversations between confederates and participants.
After the conversation ended, participants completed two questionnaires, purportedly unrelated to each other, containing our self-report measures. The chat window was embedded within an online survey tool Qualtrics , which contained all of our instructions and self-reported measures for an image of the chat window, see Supplementary Material.
Two questions from the Comforting Responses Scale Clark et al.