This research paper explores the effects of data variance on the quality of Artificial Intelligence image generation models and the impact on a viewer's perception of the generated images. The study examines how the quality and accuracy of the images produced by these models are influenced by factors such as size, labeling, and format of the training data. The findings suggest that reducing the training dataset size can lead to a decrease in image coherence, indicating that AI models get worse as the training dataset gets smaller. Moreover, the study makes surprising discoveries regarding AI image generation models that are trained on highly varied datasets. In addition, the study involves a survey in which people were asked to rate the subjective realism of the generated images on a scale ranging from 1 to 5 as well as sorting the images into their respective classes. The findings of this study emphasize the importance of considering dataset variance and size as a critical aspect of improving image generation models as well as the implications of using AI technology in the future.

This research investigates the attitude of students towards chatbots and their potential usage in finding career resources. Survey data from two sources were analyzed using descriptive statistics and correlation analysis. The first survey found that students had a neutral attitude towards chatbots, but chatbot understanding was a key factor in increasing their usage. The survey data suggested that chatbots could provide quick and convenient access to information and personalized recommendations, but their effectiveness for career resource searches may be limited. The second survey found that students who were more satisfied with the quality of resources from the career office were more likely to use chatbots. However, students who felt more prepared to explore their career options were less likely to use chatbots. These results suggest that the W. P. Carey Career Office could benefit from offering more and better resources to prepare students for exploring their career options and could explore the use of chatbots to enhance the quality of their resources and increase student satisfaction. Further research is needed to confirm these suggestions and explore other possible factors that may affect the use of chatbots and the satisfaction with career office resources.

The recent popularity of ChatGPT has brought into question the future of many lines of work, among them, psychotherapy. This thesis aims to determine whether or not AI chatbots should be used by undergraduates with depression as a form of mental healthcare. Because of barriers to care such as understaffed campus counseling centers, stigma, and issues of accessibility, AI chatbots could perhaps bridge the gap between this demographic and receiving help. This research includes findings from studies, meta-analyses, reports, and Reddit posts from threads documenting people’s experiences using ChatGPT as a therapist. Based on these findings, only mental health AI chatbots specifically can be considered appropriate for psychotherapeutic purposes. Certain chatbots that are designed purposefully to discuss mental health with users can provide support to undergraduates with mild to moderate symptoms of depression. AI chatbots that promise companionship should never be used as a form of mental healthcare. ChatGPT should generally be avoided as a form of mental healthcare, except to perhaps ask for referrals to resources. Non mental health-focused chatbots should be trained to respond with referrals to mental health resources and emergency services when they detect inputs related to mental health, and suicidality especially. In the future, AI chatbots could be used to notify mental health professionals of reported symptom changes in their patients, as well as pattern detectors to help individuals with depression understand fluctuations in their symptoms. AI more broadly could also be used to enhance therapist training.

With an increase in Artificial Intelligence applications in the world of technology, its usage has extended as far as the world of business, with small, medium, and large firms offering both products and services for consumer and business use. Through its historical development, and the devolvement of frameworks, algorithms, and basic toolkits, the application of AI in business was able to flourish. The development of multiple tools such as smart stethoscopes and conversational assistants throughout multiple industries has created a complex commercial enterprise of Artificial Intelligence for the specific genre of business and its applications today are bound to have major effects on the AI applications of tomorrow.