Published Paper Details:

Assessing AI uses in institutions of higher learning has triggered this study, where the researcher seeks to establish what faculty feel and think about technologies concerning performance evaluation systems based on artificial intelligence. The study also focuses on how these experiences are influenced by demographic characteristics such as age, gender, education level, and teaching experience in a diverse sample from Coimbatore District. Altogether, the responses were largely positive, and the AI works as it is recognized for providing reasonable and unbiased comments that can benefit career development and correlate the work satisfaction. However, there are some lose ends with regards to lack of human intervention, a potential for algorithmic bias, lack of accountability. Concern with job and promotion opportunities and work-life imbalance also brings focus on segments that crave change. The present work mentions the strong connections between the experiences of faculty and demographic factors and concludes that there ought to be different approaches to AI implementation. To ensure that the system is effective and fair the research offers information on potential development which includes: a dual approach where the AI works under the supervision of managers and coaches while at the same time finding ways of maintaining work-life equilibrium.