The ability of communicative robots to express emotions in various ways is critical for human-robot interaction. People communicate with each other using language and nonverbal cues such as gestures and facial expressions to convey their emotions and infer others’ emotions (Barrett, 1993; Lange et al., 2022). By expressing emotions in the same manner as humans, the signals and intentions sent by robots can be intuitively understood by humans, without these having to undergo special training for interaction with robots. Thus, it is essential for robots to express emotions to facilitate human-robot interactions (Cañamero and Fredslund, 2001; Eyssel et al., 2010; Kim and Kwon, 2010; Złotowski et al., 2015; Tsiourti et al., 2019). Furthermore, it has been argued that emotions have a social function (van Kleef and Côté, 2022). the social functionof emotions refers to the influence of emotional expressions on the thoughts, feelings, and behaviours of others, which has been widely confirmed in the emotional expressions of robots (Melo et al., 2023). For example, it has been demonstrated that when robots express emotions through language, gestures, and facial expressions, they increase their ratings of intelligence, sociability (Garrell et al., 2017), humanlikeness, likeability, and closeness (Eyseel et al., 2010). In addition, field research in supermarkets has shown that children are interested in robots that exhibit emotional expressions and engage with them themselves (Motoda, 2019). In short, the social function of emotions has many advantages, as it works not only between people but also between people and robots (Melo et al., 2023). Additionally, many studies have shown that emotional expressions by robots can change peoples’ attitudes towards them and influence their emotions and behaviours (e.g., Garrell et al., 2017; Motoda, 2019). Moreover, Cañamero and Fredslund. (2001) argued that more emotional expressions are required for richer human-robot interactions. In addition, robots should be able to express diverse and complex emotions that are similar to those of humans.

In September 2021, a robot that sheds tears like a human was developed at a University in Japan. The robot has tear sacs in its eyes, moistens its eyes, and sheds tears naturally (Yoon, 2021). Associate Professor Sejima, the robot developer, hopes to create an atmosphere that allows people to cry easily in the presence of crying robots. The robot is intended for tele-counselling and activities that aim to relieve stress by crying (Yoon, 2021).

However, it is unclear whether the tears shed by robots are recognised as emotional expressions. The behaviour of shedding tears in response to emotional arousal is unique to humans (Vingerhoets, 2013). In studies on non-human subjects, the tears of animals and avatar faces have been found to convey sadness (Gračanin et al., 2021; Picó and Gadea, 2021). However, to the best of our knowledge, no studies have examined people’s perceptions of tears shed by robots. In other words, it is not clear whether the social functions of emotions that arise from people shedding tears work in the same manner when robots shed tears. Therefore, even if a robot is equipped with the ability to shed tears, it is unclear whether it will have the expected effects such as emotional communication and interaction. Hence, it is essential to clarify this issue when designing future robots. As a result, the present study aimed to determine whether robot tears also exhibit the typical signalling functions of human tears using methods employed in previous studies conducted on human tears. In the next section, the typical emotional and social signalling functions of human tears are reviewed. Finally, the overview and hypotheses of the present study are presented.

Human tears function as a signal that conveys sadness. Provine et al. (2009) and Zeifman and Brown (2011) showed that removing tears from a picture of a tearful person reduced the intensity ratings of sadness. Conversely, adding tears to a sad expression accelerates the rate at which it is perceived as sad, indicating that tears facilitate the perception of sadness (Balsters et al., 2013). Ito et al. (2019) demonstrated that when tears were added to neutral, sad, angry, fearful, and disgusted facial expressions, the rated intensity of sadness was higher for all expressions and the rating pattern of facial expressions approached that of sadness. They concluded that tears are convey sadness.

Additionally, tears can function as a social signal to elicit support intentions from others. Several studies examined the effect of tears on eliciting support intentions using pictures of tearful people or digitally manipulated pictures of tears. The results have consistently shown enhanced support intentions for tearful individuals compared to those who are not tearful (Hendriks and Vingerhoets, 2006; Vingerhoets et al., 2016; Stadel et al., 2019). The effect of tears on eliciting support intentions from others was proposed by Zickfeld et al. (2021) as a social support hypothesis. They demonstrated that tears elicit support intention from others; however, the magnitude of the effect of tears varies depending on certain variables such as the event of crying, relationship with the person, and gender. Recently, the process by which tears elicit support intentions has become increasingly apparent. Vingerhoets et al. (2016) and Zickfeld et al. (2021) demonstrated that tears represent feelings of helplessness and warmth. Observers feel connected to a tearful individual, which leads to supporting intentions towards the latter.

This study investigated whether tears shed by robots have both emotional and social signalling functions, using methods similar to those employed in previous studies conducted on human tears. Specifically, we used pictures of robots as visual stimuli and measured self-reported responses. These responses provide the first clue to people’s feelings and behaviours in real-life situations. In other words, we aimed to determine whether the responses to a robot’s tears were similar to those to human tears. Study 1 investigated whether robot tears serve as emotional signals that convey sadness. Study 2 investigated whether robot tears served as a social signal that elicits support intentions. The process underlying the effect of human tears on support intentions has been identified in existing literature; therefore, Study 2 also examined whether robots and humans were similar in this process.

Because people tend to anthropomorphise robots and exhibit social reactions, robot tears may elicit reactions similar to those of as human tears. Systematic experiments by Reeves and Nass. (1996) have shown that people behave socially and politely towards flattering inorganic objects, such as computers. This theory, which argues that people tend to assign human characteristics to media, is called media equation theory (Reeves and Nass, 1996). Furthermore, this phenomenon occurs unconsciously and automatically (Reeves and Nass, 1996), and has been confirmed in people’s reactions to robots (e.g., Rosenthal-von der Pütten et al., 2013; Suzuki et al., 2015). This phenomenon suggests that people tend to perceive inorganic objects anthropomorphically. Consequently, we predicted that people’s reactions to robot tears would be similar to their reactions to human tears. Specifically, we predicted that people would attribute a robot’s tears to feelings of sadness, thereby increasing the rating of sadness intensity. Furthermore, it was predicted that people would evaluate a robot shedding tears as warm and helpless, similar to a tearful person, and would feel more connected to the robot, thereby resulting in increased support intention.

The participants viewed pictures of robots with and without tears and rated the intensity of the emotion experienced by the robot in the picture. In previous studies of human tears, the type of emotion for which ratings were asked varied from study to study, with some asking participants to respond to sadness only (Provine et al., 2009; Balsters et al., 2013), to negative emotions only (Ito et al., 2019), and to Ekman’s (1999) basic six emotions (Gračanin et al., 2021). It is also a customary and common practice in numerous facial expression recognition studies to measure Ekman’s (1999) six basic emotions (happiness, sadness, anger, disgust, fear, and surprise; e.g., Miwa et al., 2003; Ge et al., 2008; Kishi et al., 2012; Bennett and Šabanović, 2014). This study is the first to examine the impact of robot tears on emotional ratings. To determine the impact of more emotions, we asked the participants to rate the six basic emotions proposed by Ekman. (1999). Previous studies have shown that tears enhance sadness (e.g., Provine et al., 2009; Ito et al., 2019). Thus, we predicted that robots with tears would have higher ratings of sadness intensity than those without tears (Hypothesis 1). Conversely, the effect of tears on emotions other than sadness depends on the facial expressions before tears are applied. For example, applying tears to an angry facial expression results in a stronger evaluation of the anger emotion conveyed by the expression (Gračanin et al., 2021). However, because the robots used in this study were incapable of changing their facial expressions or clearly conveying an expression of a particular emotion, no explicit hypotheses were formulated for emotions other than sadness.

Study 1 revealed that tears enhance the rated intensity of sadness in robots. Study 2 aimed to investigate whether robot tears serve as a social signal to elicit support intentions using different scenarios. We also examined whether the effect of tears on eliciting support intentions was mediated by perceptions of warmth, helplessness, and connectedness, as in humans. Because many previous studies have shown that tears have a strong effect on eliciting support intentions (e.g., Vingerhoets et al., 2016; Stadel et al., 2019; Zickfeld et al., 2021), it was hypothesised that support intentions would be higher for robots with tears than for robots without tears (Hypothesis 2). Furthermore, the tear-eliciting support intention effect is mediated by increased perceptions of warmth, helplessness, and connectedness of the tearful individual (Vingerhoets et al., 2016; Zickfeld et al., 2021). We also hypothesised that the effect of tears on eliciting support intentions would be mediated by the perceptions of warmth, helplessness, and connectedness (Hypothesis 3).

The present study aimed to investigate whether tears shed by robots have an emotional signalling function for conveying sadness and a social signalling function for eliciting support intentions, using methods similar to those of previous studies conducted on human tears. Study 1 examined whether robot tears served as an emotional signal to convey sadness, and demonstrated that robots with tears conveyed enhanced sadness. Study 2 examined whether robot tears serve as a social signal to elicit support intentions and found that robot tears also elicit support intentions. Moreover, the process by which robot tears elicit support intentions was found to be similar to that of humans.

The results of the present study suggest that tears may have facilitated the anthropomorphisation of the robot. The results of the two experiments conducted in the present study replicated those of previous studies using human pictures. This demonstrated, for the first time, that tears in robots may function as emotional and social signals in the same manner as in humans. As inorganic objects, robots have no emotions or will and do not shed tears spontaneously. However, because people tend to anthropomorphise inorganic robots (Reeves and Nass, 1996), it is presumed that they perceive emotions and sociality in the tears of the robots. In addition to this flexibility in human cognition, it is possible that the object itself, the tears, may have been a catalyst for people to find emotional and social qualities in the robot and may have promoted anthropomorphising and perception of the robot with human-like characteristics. Riek et al. (2009) examined whether people showed empathy towards robots by displaying videos of robots being abused. The results showed that there were differences in the degree of empathy depending on the appearance of the abused robot, with higher empathy shown for a human-like robot (android) than for a robot with a mechanical appearance (cleaning robot Roomba). Thus, the personhood of a robot influences people’s social responses to it. Moreover, the perception of a robot’s personhood has been argued to increase acceptance, liking, familiarity and trust towards the robot and facilitate social interactions with people (Eyssel et al., 2010; Fink, 2012). Because shedding tears is a unique human expression of emotions (Vingerhoets, 2013), it can be inferred that tears are symbolic elements of personhood. Therefore, the addition of tears to a robot, which is an inorganic object, may have promoted people’s tendency to perceive inorganic objects as anthropomorphic and the robot as an infinitely human-like entity.

Furthermore, shedding tears is a meaningful way for robots to express their emotions. The results of this study suggest that robot tears increase the intensity of sadness and that shedding tears can function as an emotionally expressive behaviour of sadness in robots. In addition to sadness, tears are accompanied by diverse emotions such as happiness and anger (Vingerhoets, 2013). Although Study 1 did not provide contextual information, it may be possible to express emotions other than sadness through tears, depending on the context in which the tears are shed. Consequently, equipping robots with tear-shedding behaviour is expected to broaden their range of emotional expressions and make human-robot interactions more sophisticated and richer. Moreover, the perception of sad facial expressions differs between young and older adults, with older adults being less sensitive to the perception of sad facial expressions compared to young adults (Phillips and Allen, 2004; MacPherson et al., 2006). However, no differences were found between older and young adults in their assessment of grief in response to the emotional expression of shedding tears, indicating that tears are a universal emotional signal that conveys grief across all ages (Grainger et al., 2019). Therefore, the provision of a tear function as a way of expressing sadness in robots may be beneficial, as it facilitates the transmission of sadness regardless of the age of the person interacting with the robot.

This study demonstrates for the first time that the social functioning of emotions can occur when robots shed tears. It has been shown that when robots express emotions through facial expressions and gestures, they exhibit the same social functions as humans (Melo et al., 2023). The present study supports the results of previous studies and shows that this applies to the previously untested emotional expression of shedding tears, thereby contributing to new knowledge in this area. Specifically, Study 2 showed that robot tears elicited support intentions and influenced human behaviours. The behaviour of shedding tears attracts the attention of others and elicits approach responses (Hendriks et al., 2008; Vingerhoets, 2013). Moreover, it can be applied for the treatment of autism through human-robot interactions (e.g., Scassellati et al., 2012; Taheri et al., 2018) and as “robot being cared for” to fulfil the self-esteem and self-affirmation of older adults (Kanoh, 2014). In other words, equipping robots with the ability to shed tears may contribute to further developments in fields where robots are actively utilised.

Finally, the limitations and future perspectives of this study are discussed. First, the baseline of stimuli used in this study was not uniform. For example, some robots missed certain facial parts (mouth and nose) or appeared to smile. In humans, tears have been shown to enhance the evaluation of sadness and support intentions, regardless of facial expressions prior to the imposition of tears (e.g., Provine et al., 2009; Zeifman and Brown, 2011; Ito et al., 2019). However, the magnitude of the effect of tears varies across facial expressions (e.g., Ito et al., 2019). Therefore, future work is needed to control the facial expressions and parts of the robot and examine the effect of tears. In addition, the number of robot types used in the experiments was small. Although four different types of robots were used in this study, many different types of communicative robots have been developed with varying appearances, ranging from those modelled on animals, such as dogs and seals, to those that look more like humans (Weiss et al., 2009; Zecca et al., 2009; Eyssel et al., 2010; Pandey and Gelin, 2018). Consequently, it is unclear whether the results presented in this study can be generalised to all robots. Second, contextual information was limited. Specifically, Study 1 did not include any contextual information. This is a necessary procedure for identifying the emotions signified by tears. Contextual information is a very important factor in determining the emotion indicated by the emotional expression, especially tears, which can be associated with a range of emotions (Vingerhoets, 2013; Zickfeld et al., 2020). Future studies should set contextual information and determine whether a robot’s tears can also intensify the evaluation of other emotional expressions such as joy, emotion, and anger. Third, the present study dealt only with subjective assessments. Our aim was to identify the signalling function of robot tears using an approach similar to that of previous studies conducted on human tears. Thus, we asked the participants to respond to the support intention of a subjective evaluation of the pictures of the robot. This method is important because it provides the first clues to actual human reactions to the robot. Conversely, previous studies examining the social function of emotions have shown that compared to non-expressed emotions, robots made concessions in negotiation games to opponents who showed emotional expressions (Sinaceur et al., 2015), donated more money (Takagi and Terada, 2021), and made suggestions with high amounts of money in ultimatum games (Terada and Takeuchi, 2017), showing that emotional expressions can influence the behaviour of others. In the present study, support intentions increased for robots that shed tears. However, it is not clear whether this leads to actual support behaviour. Future hypothesis testing using behavioural indicators is required.

The tears in robots may have signalling effects similar to those in humans. Robot tears have enhanced the rated intensity of sadness. They also indicated warmth and helplessness. The observers felt a sense of closeness to the tear-shedding robot, which led to support intentions. The results suggest that robot tears, like human tears, have both an emotional signalling function for conveying sadness and a social signalling effect that elicits support intentions. This is the first study to demonstrate the previously unidentified emotional and social signalling functions of robot tears and to determine the potential for new tear-specific interactions between humans and robots.