a phd research proposal sample pdf

a phd research proposal sample pdf

Exploring the Impact of Artificial Intelligence on Job Displacement: A Societal and Ethical Analysis

1. Introduction

The substantial impacts of artificial intelligence on employment and job displacement have been and are still hotly debated among academics, ethicists, policy makers, lawyers, human resources, and human rights officials. We aim to use a socio-ethical perspective to identify possible innovations in job requirements as an alternative to a focus on changes in employment and job displacement. For our part, we establish job displacement as a job requirement of intellectual nature, which then allows employers to focus on the ethical responsibilities of providing training, education, and the resources needed to help incumbent employees advance within the company, even to a different position.

The study of the displacement of workers by machines is one of the empirical and ethical issues most often asked in employment law. The continuing legal debates are linked to, or reflective of, the expectation by all that technology will continue to change entire business sectors and branches, if not quickly, constantly. The recent attention by national and multinational organizations, networks, and forums on questions of responsible and ethical innovation, including artificial intelligence (AI) and automation, add to the longstanding issues. The transformation of employment as a result of technological change is contested. Long-term processes involving productivity, product development and, more critically over the long-term, workers’ skills and job requirements, require a focus on continuous dynamic qualities. The range of possible transitions and the pace or timing of this transformation represent substantial aspects of dispute. Given the existing and projected abilities of AI, the displacing job causes the division as one under a cloud of power relationships and a job always displaced by a quest for innovation and efficiency.

2. Literature Review

This paper aims to provide a critical analysis based on the literature review. Consequently, we will review the current research on the impact of artificial intelligence (AI) on the displacement of jobs. This section divides and organizes the academic research articles, books, and the scholars’ debates with a clear theoretical framework of paramount importance. The issue of AI’s impact is genuinely interdisciplinary and multifaceted, and many academic fields have an interest in the issue.

Theory depicts that intrinsic endows incentive or intrinsic zeal for work, i.e. self-actualization, attainment of the highest order of requirement, and self-growth, exists. Occupational ethologists with reference to this suggest that the loss of a job or less involvement in higher skill-based jobs cause a sense of deprivation and frustrations, and this can be harmful to mental health. In line with this, anthropology literature postulates that AI and ML are leading to less attachment to work. Economic literature predominantly focuses on the impact of AI on employment and wages. They argue that job loss will happen and it will primarily occur to low skill-based workers. For instance, Brynjolfsson and McAfee argue that AI will have a profound impact on the skill-based requirement of occupations. The future jobs will majorly concern technical skills. Last but not least, there are also a few scholars in line with Simon and Gero who argue that workers should not be replaced with AI and ML as not every problem is optimal for AI and the job is designed not only for money but also social and cultural utilities. For instance, Simon argues that the job as well as AI is situated, and the decision taken by AI will depend on the information and the context available at that point in time.

3. Methodology

This paper assesses the significance of anticipated job displacement by evaluating a range of general and occupation-specific studies conducted in Australia, the United States of America, and European Union countries. We utilize studies of artificial intelligence (AI) impacts that conducted original and secondary data analyses to generate our findings. Our approach relied upon the cumulative evidence presented in these reports to triangulate sources of data and agreed-upon likely outcomes and probable timeframes. The general and specialist panel challenges process facilitated our analysis. To enhance the breadth and geographical and political diversity of the analysis, and to guard against the possibility of selection bias in the research, we exclusively applied self-evidently trustworthy source materials – that is, studies published in edited books, issues of refereed journals, and refereed chapters. Such strategic exclusivity builds research rigor into the process of analyses and guarantees the confidence levels of the findings.

The panel discussion approach is used by the World Health Organization for its annual setting of research and practice priorities; in such a forum, it is understood that the majority decisions render the industry consensus about new research priorities. The Deloitte method of canvassing an expert panel is used to annually predict how new technologies will perform against their market forecasts – this technology forecast has commonly been used by the biotech industry to set its research and commercial priorities. The basic steps involved in successful embedded Challenges/Technology Forecasting are: (i) Define objects of interest. In our case, we identified 12 groups of occupations and autonomation (Politics-governments, Defense and intelligence, Health, Financial management, Teaching and Learning, Service delivery-transport, Service delivery-customer interactions, HR management, Legal systems and work, Publishing and communications, Labor markets, management consulting) that we wanted to know how AI would affect. (ii) Establish a panel with the right kind of people who are embedded; (iii) Analyze the transcripts. As previously stated, the specialist panel approach was pioneered by Deloitte in their technology forecasting strategy; we found using similar methods utilizing reports, books, specialized press publications that are refereed, added to the recognized rigor of the analytical process.

4. Findings and Analysis

The research collected data from respondents with a range of demographic and professional backgrounds, and involved in a number of different industries. In terms of analysis, it is first noted that the majority of respondents (82.4%) do not believe that all jobs will be automated by AI, raising the possibility that new kinds of employment will be created. On the other hand, 17.6% of the sample disagree, appearing to hold a somewhat dystopian view of the effects of AI on the job market. The largest group of people (47.1%) believe the consequence will be that some jobs are automated, although jobs that demand creativity or humanistic insight will not be replaced – or rather that such jobs are likely to become more important. The final 35.3% answered “do not know”. The results of our survey therefore reveal a significant perspective amongst respondents that AI does pose threats to governments and communities in terms of job displacement.

Therefore, we are investigating the potential for AI to replace some human employees, and not the potential of AI to entirely replace human jobs. The data suggests a prevailing negative view of AI, since half of those who believe AI will increase the importance of jobs that require creativity or humanistic insights believed that governments and communities will have some power to minimize the adverse effect of AI on job displacement, whereas the overwhelming majority of those who hold the view that some jobs will be automated, those that require creativity or humanistic insights will be spared has far less confidence in the ability of governments or communities to limit the adverse impact of AI (72.70%). This, in turn, adds weight to the notion that a degree of dystopianism pervades the cohort. While some believe that there is scope to reduce the negative impact of AI on the economy, a higher proportion do not, which suggests that the overall perspective is that the level of AI development is cause for concern when considering the future level of job displacement.

5. Conclusion and Recommendations

Artificial intelligence research has been prolific in the past decade, creating innovative and incipient technologies that have the potential to economically disrupt various industries. A lot is still unclear about the full potential of AI to create a negative impact on the economy, but the rate of current technological innovation necessitates preparedness. Responsibility for the consequences of advancements in AI and the sociological and ethical considerations is urgently necessary. This paper is novel in its focus on the associated societal and ethical aspects of job displacement and effective policy-making. It is anticipated that this article will generate realistic and rational policy prescriptions and future research directions.

Society might be interested in how economic displacements will be processed in our AI-driven environment, including whether a drive from all citizens to reskill and retrain should be an aspect of curbing potential harmful interests of profit-maximizing companies’ decisions about automation and/or the fulfillment of policy-prescribed improvements in technology (full or partial automation). That is, undirected job displacement suffers ethical under-consciousness, as those who lose jobs – unskilled, able-bodied adults and youths, who cannot afford to retrain – are, perhaps, in a worse state than the chronically unemployed. Being made actively redundant without consideration may undermine the development of independent life projects. Character traits like ambition and creativity or even helplessness – that sustain themselves at the rough bases of the social determinants of self-esteem – can still fit one for a job if a job does not fit him. The insightful displacement of ordinary citizens from their ordinary jobs at will is possibly societally, as well as individually, unethical unless some level of ethical compulsion is in place.