The future of hospitality jobs

This article reviews the literature on artificial intelligence (AI)-driven technology and looks at its effects on the future of hospitality jobs, and the skills needed for the future. The purpose of this article is to understand and describe how developments in AI-driven robotics and automation will shape the future of hospitality jobs, the skills in demand, and their impact on the design of education and training. Various input parameters are significant in understanding the future of hospitality jobs. For an optimised understanding, literature has been critically reviewed and investigated from different angles, namely academics, technological advancements, developments in the industry, and governments and policymakers. The literature reveals that AI-driven technology is developing at a very high speed and shows its extensive application in tourism and hospitality  management and other related industries. Many of today’s jobs will be lost to AI, automation and robotics, and new jobs with new skill-set requirements will emerge. Education establishments will have to adopt a new futureproof educational system or risk becoming obsolete. This review article will be beneficial for industry and education. The article reveals the detailed literature review on jobs that are at high risk of disappearing and offers an insight into what future jobs might be and what skills and competences will be required. Keywords: artificial intelligence, employment, skills, hospitality, human resources, training and educatio

A return to Teacherbot:Rethinking the development of educational technology at the University of Edinburgh

In the market discourses of technological disruption, higher education institutions have routinely been positioned in deficit models and of anachronistic approaches to teaching at odds with the types of educational futures being presented by commercial organisations. Predominantly, automation technologies in the form of artificial intelligence are being promoted as the future of teaching. In this paper, on the other hand, we explore the prospects for using non-artificial intelligence automated agents in teaching and its impact on the teacher function at the University of Edinburgh. Through engagement with teachers, staff and students at the university, this research has identified use cases for bots, in what spaces they would be situated, and how they would supplement the teacher function. This paper argues that a community-driven approach combined with a sociomaterial conceptualisation can generate a shift from market discourses and to collaborative development of educational technologies

ANALYZING THE IMPACT OF AUTOMATION ON EMPLOYMENT IN DIFFERENT US REGIONS: A DATA-DRIVEN APPROACH

Automation is transforming the US workforce with the increasing prevalence of technologies like robotics, artificial intelligence, and machine learning. As a result, it is essential to understand how this shift will impact the labor market and prepare for its effects. This culminating experience project aimed to examine the influence of computerization on jobs in the United States and answer the following research questions: Q1. What factors affect how likely different jobs will be automated? Q2. What are the possible effects of automation on the US workforce across states and industries? Q3. What are the meaningful predictors of the likelihood of automation for certain jobs or groups? Q4. How can governments and businesses best prepare for the effects of automation on the workforce? Q5. What are the most effective ways to reduce the negative effects of automation on workers and communities? The findings are as follows: Q1: Jobs that do not require higher education are more likely to be automated. Additionally, income and automation are negatively related. The study concludes that job occupations with higher education are less likely to be automated. In contrast, jobs in lower-skilled industries, such as manufacturing and retail, are more vulnerable to automation. Q2: As automation technology advances, it will create new jobs in emerging fields and lead to job losses in certain industries. The effects of automation on employment reductions will vary across states and industries, with certain ones being more susceptible than others. Q3: Income and education are significant factors that impact the likelihood of automation. Jobs that pay lower wages and do not require higher education are more likely to be automated. Q4: State governments and businesses should invest in (1) learning and guidance programs to benefit workers and obtain additional expertise and knowledge to prepare them for the changing job market. (2) Promoting innovation and entrepreneurship is another recommendation to create new job opportunities in emerging fields like robotics, AI, and data analysis. Implementing policies that support workers affected by automation, such as unemployment insurance or retraining programs, can also provide a protection net for workers who have dropped their occupations due to computerization. (3) Lastly, understanding the specific industries and job types that are most vulnerable to displacement is a key recommendation. Q5: Effective ways to reduce the negative effects of automation on workers and communities include (1) providing financial and educational support for affected workers, (2) creating policies that incentivize businesses to invest in training and reskilling programs, and (3) fostering a culture of innovation and creativity that encourages the development of new technologies and industries. Possible areas of further study related to the research questions addressed in this paper include exploring the impact of automation on different demographic groups (Research Question 3), investigating the potential implications of automation on the future of work (Research Questions 2 and 5), and examining the role of public policies in addressing the challenges posed by automation (Research Questions 4 and 5). In conclusion, automation has the potential to transform the US workforce and bring both benefits and challenges. The findings suggest that education and income are significant factors that impact the likelihood of automation. The effects of automation on employment reductions will vary across states and industries. State governments and businesses should prepare for the effects of automation by investing in learning and guidance programs, promoting innovation and entrepreneurship, and implementing policies that support workers affected by automation. Understanding the specific industries and job types that are most vulnerable to displacement is also crucial for mitigating the negative effects of automation

Audit and AI: Can Artificial Intelligence Restore Public Trust?

Due to the fallout from a series of corporate fraud scandals in the late 2000s, the auditing world has lost much of the public trust that is very important to the profession. Much of the value of an audit opinion is determined by the trust the public places in the auditors behind the opinion. Without trust in the auditors, the audit opinion has very little value. The recent increase in the usage of artificial intelligence (AI) in many industries presents a solution to the problem of auditors. Increased usage of AI in the audit process has the potential to better meet public demand for an audit as well as restore public trust

AI, Robotics, and the Future of Jobs

This report is the latest in a sustained effort throughout 2014 by the Pew Research Center's Internet Project to mark the 25th anniversary of the creation of the World Wide Web by Sir Tim Berners-Lee (The Web at 25).The report covers experts' views about advances in artificial intelligence (AI) and robotics, and their impact on jobs and employment

Active learning based laboratory towards engineering education 4.0

Universities have a relevant and essential key role to ensure knowledge and development of competencies in the current fourth industrial revolution called Industry 4.0. The Industry 4.0 promotes a set of digital technologies to allow the convergence between the information technology and the operation technology towards smarter factories. Under such new framework, multiple initiatives are being carried out worldwide as response of such evolution, particularly, from the engineering education point of view. In this regard, this paper introduces the initiative that is being carried out at the Technical University of Catalonia, Spain, called Industry 4.0 Technologies Laboratory, I4Tech Lab. The I4Tech laboratory represents a technological environment for the academic, research and industrial promotion of related technologies. First, in this work, some of the main aspects considered in the definition of the so called engineering education 4.0 are discussed. Next, the proposed laboratory architecture, objectives as well as considered technologies are explained. Finally, the basis of the proposed academic method supported by an active learning approach is presented.Postprint (published version

Artificial intelligence: opportunities and implications for the future of decision making

Artificial intelligence has arrived. In the online world it is already a part of everyday life, sitting invisibly behind a wide range of search engines and online commerce sites. It offers huge potential to enable more efficient and effective business and government but the use of artificial intelligence brings with it important questions about governance, accountability and ethics. Realising the full potential of artificial intelligence and avoiding possible adverse consequences requires societies to find satisfactory answers to these questions. This report sets out some possible approaches, and describes some of the ways government is already engaging with these issues

Automation Potential and Artificial Intelligence

This Fact Sheet highlights the automation potential in the Mountain West states (Nevada, Utah, Arizona, New Mexico, and Colorado) and its metropolitan statistical areas using the findings of Automation and Artificial Intelligence: How machines are affecting people and places, a report by the Brookings Institution