Capacity of Generative AI to Interpret Human Emotions From Visual and Textual Data: Pilot Evaluation Study.

BACKGROUND: Mentalization, which is integral to human cognitive processes, pertains to the interpretation of one's own and others' mental states, including emotions, beliefs, and intentions. With the advent of artificial intelligence (AI) and the prominence of large language models in mental health applications, questions persist about their aptitude in emotional comprehension. The prior iteration of the large language model from OpenAI, ChatGPT-3.5, demonstrated an advanced capacity to interpret emotions from textual data, surpassing human benchmarks. Given the introduction of ChatGPT-4, with its enhanced visual processing capabilities, and considering Google Bard's existing visual functionalities, a rigorous assessment of their proficiency in visual mentalizing is warranted. OBJECTIVE: The aim of the research was to critically evaluate the capabilities of ChatGPT-4 and Google Bard with regard to their competence in discerning visual mentalizing indicators as contrasted with their textual-based mentalizing abilities. METHODS: The Reading the Mind in the Eyes Test developed by Baron-Cohen and colleagues was used to assess the models' proficiency in interpreting visual emotional indicators. Simultaneously, the Levels of Emotional Awareness Scale was used to evaluate the large language models' aptitude in textual mentalizing. Collating data from both tests provided a holistic view of the mentalizing capabilities of ChatGPT-4 and Bard. RESULTS: ChatGPT-4, displaying a pronounced ability in emotion recognition, secured scores of 26 and 27 in 2 distinct evaluations, significantly deviating from a random response paradigm (P<.001). These scores align with established benchmarks from the broader human demographic. Notably, ChatGPT-4 exhibited consistent responses, with no discernible biases pertaining to the sex of the model or the nature of the emotion. In contrast, Google Bard's performance aligned with random response patterns, securing scores of 10 and 12 and rendering further detailed analysis redundant. In the domain of textual analysis, both ChatGPT and Bard surpassed established benchmarks from the general population, with their performances being remarkably congruent. CONCLUSIONS: ChatGPT-4 proved its efficacy in the domain of visual mentalizing, aligning closely with human performance standards. Although both models displayed commendable acumen in textual emotion interpretation, Bard's capabilities in visual emotion interpretation necessitate further scrutiny and potential refinement. This study stresses the criticality of ethical AI development for emotional recognition, highlighting the need for inclusive data, collaboration with patients and mental health experts, and stringent governmental oversight to ensure transparency and protect patient privacy.

Social relations between students from two groups in conflict: Differences in stereotypes and perceived social distance between Jewish and Arab nursing students.

BACKGROUND: The heterogeneous nature of the nursing profession generates encounters between members of different groups. Thus, nursing education should include programs focusing on cultural sensitivity to enhance cultural competence. Due to the ongoing conflict between Arabs and Jews, Israel is an appropriate setting for examining cultural sensitivity programs. AIM: This study explores how Jewish-Israeli and Arab-Israeli nursing students studying together perceive their social relations by examining attribution of stereotypes (positive and negative) to members of the other group and willingness to engage in social interactions with individuals from the other group. SETTING: The Department of Nursing at the Max Stern Yezreel Valley College. PARTICIPANTS: 180 Jewish and Arab nursing students at two different points in their studies, beginning students and those at more advanced stages. METHODS: The students completed questionnaires examining their perceptions of the social relations between the two groups. The questionnaires measured stereotypes and perceptions of social distance regarding members of the other social group. RESULTS: More positive stereotypes and fewer negative stereotypes were found among the Jewish students than among the Arab students. Nevertheless, the Jewish students exhibited less willingness to reduce social distance. No differences were found between beginning students and advanced students with respect to stereotypes, though advanced students expressed greater willingness to reduce social distance than did beginning students. CONCLUSIONS: The findings show that perceptions of social relations are influenced by two different contexts: the students' specific context (joint studies and joint work in the future) and the broader general context of relations between the groups. The findings indicate that programs aimed at developing cultural sensitivity and improving relations in a divided society should provide differential responses for each group and should focus on willingness to cooperate and reduce social distance rather than attempting to eliminate stereotypes.