Protecting Privacy in Indian Schools: Regulating AI-based Technologies' Design, Development and Deployment

Education is one of the priority areas for the Indian government, where Artificial Intelligence (AI) technologies are touted to bring digital transformation. Several Indian states have also started deploying facial recognition-enabled CCTV cameras, emotion recognition technologies, fingerprint scanners, and Radio frequency identification tags in their schools to provide personalised recommendations, ensure student security, and predict the drop-out rate of students but also provide 360-degree information of a student. Further, Integrating Aadhaar (digital identity card that works on biometric data) across AI technologies and learning and management systems (LMS) renders schools a ‘panopticon’. Certain technologies or systems like Aadhaar, CCTV cameras, GPS Systems, RFID tags, and learning management systems are used primarily for continuous data collection, storage, and retention purposes. Though they cannot be termed AI technologies per se, they are fundamental for designing and developing AI systems like facial, fingerprint, and emotion recognition technologies. The large amount of student data collected speedily through the former technologies is used to create an algorithm for the latter-stated AI systems. Once algorithms are processed using machine learning (ML) techniques, they learn correlations between multiple datasets predicting each student’s identity, decisions, grades, learning growth, tendency to drop out, and other behavioural characteristics. Such autonomous and repetitive collection, processing, storage, and retention of student data without effective data protection legislation endangers student privacy. The algorithmic predictions by AI technologies are an avatar of the data fed into the system. An AI technology is as good as the person collecting the data, processing it for a relevant and valuable output, and regularly evaluating the inputs going inside an AI model. An AI model can produce inaccurate predictions if the person overlooks any relevant data. However, the state, school administrations and parents’ belief in AI technologies as a panacea to student security and educational development overlooks the context in which ‘data practices’ are conducted. A right to privacy in an AI age is inextricably connected to data practices where data gets ‘cooked’. Thus, data protection legislation operating without understanding and regulating such data practices will remain ineffective in safeguarding privacy. The thesis undergoes interdisciplinary research that enables a better understanding of the interplay of data practices of AI technologies with social practices of an Indian school, which the present Indian data protection legislation overlooks, endangering students’ privacy from designing and developing to deploying stages of an AI model. The thesis recommends the Indian legislature frame better legislation equipped for the AI/ML age and the Indian judiciary on evaluating the legality and reasonability of designing, developing, and deploying such technologies in schools

An Integrated Theoretical Model of Information Systems Success/Technology Adoption for Systems Used by Employees in the 4 And 5-Star Full-Service Hotel Sector in the UK

This study aspires to combine several components of extant theoretical frameworks of Information Systems (IS) evaluation and develop a new mechanism/model, the Integrated IS Success/Technology Adoption Model, which can be applied in the context of the 4 and 5-star UK hotel industry. It is hoped that this new model can reliably measure the IS Success and technology adoption of the technological innovations used by hotel employees. Current research tends to concentrate on general emerging IS trends such as Information Communication Technologies (ICTs), including mobile and virtual reality applications. Even though there is abundant research on Information Systems used by hotel customers, the numbers of available published material seem to diminish when it comes to IS evaluation from the viewpoint of hotel employees. To complicate matters even further, most hotel employee-related studies originate from the USA or Southeast Asia. Aiming to combat this distinct shortage in academic papers, the present thesis recognises the evident research gap and seeks to fill it by presenting a study that is pertinent to the realities of hotel employees working in 4 and 5-star fullservice hotels in the UK. A major difference between a customer/guest use of IS and an employee use is that the former does not have to use a hotel’s systems; however, this is not the same with employees, for whom daily system use is compulsory as part of their jobs. Therefore, different metrics apply for each subset. iii The secondary research makes every effort to showcase a comprehensive account of IS evaluation approaches, starting from general strategies and frameworks to the breakdown of specialised IS success and technology adoption models and their dimensions. The primary research incorporates 28 (two sets of 14) interviews with hotel department managers in order to corroborate existing or identify new IS evaluation dimensions and subthemes. The interview analysis produces two previously unexploited by the literature themes that have a major impact on System Quality, one of the central dimensions of IS Success. The key contribution of the current study is the Integrated IS Success/Technology Adoption Model, developed through corroborating the interview findings with the literature review outcomes. The Model is based on two prominent IS evaluation models, the IS Success Model (DeLone and McLean, 1992) and the Technology Acceptance Model (Davis, 1989). The originality of the Model springs from the fusion of these two frameworks, but also from the modifications added. For example, the proposed model features Social Norms, a dimension that permeates the Theory of Actioned Reason (Fishbein and Ajzen, 1975). Other additions include the use of IT training, senior management support, and facilitating conditions as external variables. Future research efforts could perhaps concentrate on testing and validating the proposed research model by use of quantitative methods in the form of a research questionnaire that would obtain the opinions of hotel line employees about the systems they work with on a daily basis