Saudi Cultural Missions Theses & Dissertations
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Item Restricted An investigation of AI in talent management in luxury hospitality in the UK (United Kingdom)(Saudi Digital Library, 2023-09-29) Alshalah, Zahra; Marinakou, EvangeliaAn investigation has been conducted into the implementation of artificial intelligence in the luxury hospitality sector of the United Kingdom. Digitalization is influencing the business operations of the hospitality sector from a variety of perspectives, including talent management. Managing talent is critical to the success of business operations in the luxury tourism sector, since it is a fundamental component of providing a better level of service to customers. There is no doubt that the hospitality industry is one of the largest in the United Kingdom. Hoteliers have been assisted greatly by artificial intelligence in managing their talent in recent years. Yet most human resources managers in luxury hotels in the United Kingdom are unaware of the existence of this technology, which is the reason for their slow growth. The purpose of this specified dissertation paper is to provide an in-depth analysis and discussion regarding the various challenges that various HR managers are undergoing while implementing AI technology within the hospitality industry in the UK. As well as the variety of approaches through which these challenges can be mitigated, this article discusses various ways through which all of these challenges can be mitigated. Artificial intelligence has been found to be able to facilitate the recruitment process. By doing so, Human Resources professionals have been able to reduce their workload. Additionally, it is used to train employees, make cognitive decisions, and select resumes for employment.97 0Item Restricted To What Extent Were US Intelligence Failures at Pearl Harbor and the Vietnam War a Result of Cultural Bias in Intelligence Analysis ?(Saudi Digital Library, 2022-09-05) AlSaud, Faisal; Wagner, StevenPearl Harbor and many aspects of the Vietnam War have been widely acknowledged as being riddled with intelligence failures on behalf of the US intelligence and military community. Yet, the role of cultural bias in these events has been underestimated. This study uses primary and secondary sources to argue that in both cases, the intelligence community miscalculated the enemy’s intentions and failed to provide an accurate cultural assessment of the situation, which led to poor strategic decisions. Cultural superiority, arrogance, Orientalism, mirror-imaging, and other characteristics of the intelligence community culture played a significant role in this intelligence miscalculation. Moreover, the dissertation reveals that no major changes have been made to eliminate or at least minimize pervasive cultural bias in the American intelligence agencies, despite gradual recognition of its role within the intelligence community.18 0Item Restricted How Does Bias Affect Users of Artificial Intelligence Systems?(2023) Bubakr, Hebah Abdullah; Baber,ChrisIn large companies, artificial intelligence (AI) is being used to optimise workflow and ensure efficiency. An assumption is that the AI system should remain unaffected by bias or prejudices to contribute to providing fairer results. For example, in the recruitment process, AI ensures that each applicant is judged by the exact criteria in the job description. Our results suggest otherwise; therefore, we wondered whether the problem of bias extends from the training data (which, replicates existing inequalities in organisations) to the design of the AI systems themselves. These learning systems are dependent on knowledge elicited from human experts. However, if the systems are trained to perform and think in the same way as a human, most of the tools would use unacceptable criteria because people consider many personal parameters that a machine should not use. The question remains whether the potential impact of bias is considered in the design of an AI system. In this thesis, several experiments are conducted to study unconscious bias in the application of AI with the aid of two qualitative frameworks and two quantitative questionnaires. We first explore the unconscious bias in user interface designs, then examine programmers’ understanding of bias when creating a purposely biased machine using medical databases. A third study addresses the effect of AI recommendations on decision-making, and finally, we explore whether user acceptance is dependent on the type of AI recommendation, testing various suggestions. This project raises awareness of how the developers of AI and machine learning might have a narrow perspective of ‘bias’ as a statistical problem rather than a social or ethical problem. This limitation is not because they are unaware of these wider concerns but because the requirements relating to the management of data and the implementation of algorithms might restrict their focus to technical challenges. Consequently, bias outcomes can be produced unconsciously because developers are simply not attending to these broader concerns. Creating accurate and effective models is important but so is ensuring that all races, ethnicities and socioeconomic levels are adequately represented in the data model (O’Neil, 2016).24 0