1. Introduction
In 1956, the concept of artificial intelligence (AI) was introduced; however, substantial progress has been achieved in the past twelve years. In an effort to expedite the delivery of remedies with superior results, it is advantageous to evaluate thousands of medical records. AI employs computer systems that resemble machines to replicate the characteristics of human intelligence and processes. Fast learning, prediction, analysis, conclusion-making, and even self-correction are all capabilities of this technology. It has been designed to address a variety of medical issues, including speech recognition, planning, imaging, and the acquisition of a specific characteristic. To enhance the accuracy of complex problem-solving and to predict superior outcomes, AI systems offer training on a specific set of data [1].
2. The Development of Artificial Intelligence
When computer scientists first started looking into ways to make robots mimic human thought processes, the 1950s marked the beginning of the emergence of artificial intelligence. Alan Turing's Turing test is now considered a seminal place to start in the field of artificial intelligence research and development. Early artificial intelligence (AI) research was primarily symbolic, using rules and logic to reason, but progress was sluggish because of computational power constraints.
Computers began to make predictions by learning patterns in data as a result of the revival of neural networks in the 1980s. The 2010s saw the true breakthrough, though. AI has achieved significant success in the disciplines of speech recognition, image processing, and natural language processing as a result of the significant improvement in computing power and the emergence of deep learning technology [2].
The development of Al in its history can be divided into three distinct phases, as indicated by the evidence. The symbolism stage (1950-1970) was characterized by the concentration of researchers on logical reasoning, rules, and symbol processing, with the objective of enabling computers to simulate intelligent behavior through rules and a knowledge base. The resurrection of machine learning and neural networks (1970-2000): Artificial intelligence transitioned to machine learning methods that replicate biological neural networks in response to the expansion of data volume and the enhancement of computing capacity. The use of statistical machine learning techniques grew, particularly in the late 1990s. The deep learning revolution (2000-present) has resulted in significant advancements in computer vision, natural language processing, speech recognition, and other fields. This revolution is founded on technologies such as convolutional neural networks (CNN) and circular neural networks (RNN). In numerous tasks, deep learning has outperformed humans, but still requiring a significant quantity of data and processing power [3].
Nowadays, the advancement of AI is contingent upon not only the availability of powerful computational power, but also on the optimization of algorithms and the accumulation of vast amounts of data. In spite of this, there are still obstacles, including ethical concerns, data dependence, and model interpretability. However, their potential is extensive and will persist in shaping our lives.
3. Analysis
In the employment market, the influence of artificial intelligence is significant, as both opportunities and challenges arise as AI continues to develop. By optimizing operations, automating repetitive tasks, and improving decision-making processes, AI technologies are rapidly changing the landscape of industries. This transformation, however, is causing apprehension regarding economic inequality, workforce reskilling, and job displacement.
Automation is one of the biggest implications of AI on jobs. Artificial intelligence-driven machines and software are replacing jobs that involve routine duties in sectors such as manufacturing, transportation, and customer service. For instance, the transportation and delivery industries are at risk of disruption due to autonomous vehicles, while chatbots are replacing customer support positions. There is a possibility of employment losses as machines become more capable, which in turn reduces the need for human labor in specific positions [4].
Conversely, artificial intelligence is also generating new employment opportunities and positions. The need for qualified professionals with the ability to create, oversee, and maintain AI systems is expanding. Specialized skills and expertise are required for the emergence of roles in AI ethics, machine learning engineering, and data science. Furthermore, AI is increasing productivity in industries such as finance, education, and healthcare by allowing employees to concentrate on more complex, strategic, or creative tasks that are not readily automated.
To alleviate the adverse effects of AI on employment, it is imperative to implement reskilling and upskilling programs. In an AI-driven economy, workers must learn new skills to be competitive. In order to ensure that training opportunities are accessible, it is imperative that governments, businesses, and educational institutions collaborate to emphasize digital literacy, critical thinking, and problem-solving [5].
4. Opportunities and Challenges
AI's capacity to automate routine duties, which enhances efficiency across industries, is one of its most significant opportunities. In industries such as finance, healthcare, and manufacturing, AI-driven automation enables businesses to reduce human error, streamline operations, and reduce costs. For example, AI is being employed to enhance the precision of medical diagnostics, manage large-scale data analysis, and optimize supply chains. Faster, more accurate decisions benefit businesses, consumers, and society.
AI also has the potential to uncover new innovations. It drives autonomous vehicle, natural language processing, and customized medical breakthroughs. Artificial intelligence-enabled systems in the healthcare industry can evaluate large information to find trends and forecast patient outcomes, resulting in more individualized and efficient treatments. Customized learning experiences that are tailored to the unique requirements of students can be achieved through the application of AI in the field of education, potentially enhancing educational outcomes.
Additionally, AI is creating new jobs in data science, machine learning, and robotics. The increasing demand for skilled professionals in AI-related disciplines presents an opportunity for both individuals and economies to capitalize on this technological shift [6].
The opportunities that AI offers are immense; however, there are also substantial challenges. One of the biggest is job loss. As AI automates tasks that were previously performed by humans, numerous positions, particularly those that involve repetitive or manual labor, are at risk of being eliminated. Because it may be more difficult for lower-skilled individuals to transfer into new professions in an AI-driven economy, this could worsen economic inequality.
In addition, the pervasive implementation of AI raises ethical concerns. There are critical challenges that must be addressed, including the use of AI in surveillance, algorithmic bias, and data privacy. AI systems that depend on extensive datasets may unintentionally perpetuate bias if those datasets reflect historical inequalities. Technologist, policymaker, and ethicist collaboration is needed to make AI transparent, accountable, and fair [7].
Finally, cautious regulation is required due to the rapid growth of AI. Institutions and governments have to strike a balance between preserving individual liberties and upholding society norms and the necessity for innovation. Maximizing AI's benefits while reducing its possible hazards requires finding the ideal regulatory balance.
5. Response Policies
Advances in AI technology provide revolutionary possibilities for boosting daily living, increasing productivity, and resolving challenging issues. However, they also present substantial hazards, such as economic inequality, ethical dilemmas, data privacy concerns, and job displacement. Governments and communities need to take the initiative to enact laws that promote innovation while preserving ethics, equity, and the general welfare in order to solve these problems [8].
Governments have a significant influence on the laws and policies pertaining to artificial intelligence. Establishing a balanced regulatory framework that addresses the hazards connected with AI while fostering innovation in the field is one of the main duties of governments. Making sure AI systems are deployed with accountability, equity, and transparency is a major area of focus. This can be accomplished by putting in place regulations requiring algorithmic audits, impact analyses, and data governance frameworks that reduce the possibility of discriminatory practices, bias, and unethical behavior.
Governments are implementing AI policies that prioritize research and development in numerous nations. Investments in infrastructure, education, and AI research are frequently prioritized in these national AI strategies. To maintain their economic advantage in the global AI race, for instance, nations like the United States, China, and the European Union have made large financial investments in AI. In order to properly forward AI innovation, these efforts also aim to promote cooperation between government, business, and academic organizations.
Workforce development is another important aspect of the government's reaction. Governments must fund reskilling and upskilling initiatives to train workers for the occupations of the future, as AI has the potential to displace jobs in industries like manufacturing, transportation, and customer service. In order to do this, easily available training programs that provide people the digital literacy and problem-solving abilities they need to succeed in an AI-driven economy must be established. To make sure that curriculum is in line with the changing needs of the labor market, governments in particular must work with private sector organizations and educational institutions [9].
Moreover, regulatory actions that safeguard people's privacy and rights are how governments are starting to handle the ethical issues of AI. Other regions are considering data privacy rules modeled after the EU's General Data Protection Regulation. These regulations are designed to ensure that AI systems respect user privacy and prevent misuse, while also establishing explicit guidelines for data collection, use, and protection [10].
Societies, including academia, civil organizations, and the private sector, are also instrumental in the development and application of AI. Civil society groups are actively pushing for laws to address digital gap, spying, and algorithmic unfairness, among other issues. These organizations exert pressure on governments and companies to implement ethical AI practices and enhance transparency by increasing awareness of the potential negative consequences of AI.
Development of AI systems that put social advantages first is the duty of the private sector, which is leading the way in AI innovation. In an effort to guarantee that their artificial intelligence products are consistent with the principles of accountability, fairness, and non-discrimination, numerous technology organizations have implemented internal ethical guidelines and advisory boards. Nevertheless, this self-regulation frequently lacks enforceability, necessitating the implementation of external supervision mechanisms by governments.
Conversely, academic institutions are producing useful studies on the effects of AI on society as well as instruments to deal with AI-related issues. To train the next generation of AI researchers and policymakers, universities are expanding their offerings to include new interdisciplinary courses that integrate computer science, ethics, and social sciences [11].
In the end, a multi-stakeholder strategy is required to guarantee that everyone benefits from the advancement of AI. To address the technological, ethical, and societal issues posed by AI, governments, academia, civil society, and the corporate sector must work together to develop a comprehensive policy framework. By fostering responsible innovation, guaranteeing workforce readiness, and protecting human rights, societies can capitalize on the potential of AI while simultaneously mitigating its hazards.
6. Artificial Intelligence and Employment
In an effort to mitigate the employment obstacles that AI presents, governments worldwide are implementing different approaches. In order to assist people in retraining for new tasks in an AI-driven economy, many nations are investing in education and reskilling initiatives. For instance, the European Union has started a number of programs to advance AI and digital literacy. Certain governments in emerging economies are concentrating on measures that promote the growth of sectors like services and the arts that are less vulnerable to automation.
Governments, corporations, and academic institutions must work together to guarantee that people have the skills required for the labor market of the future. International organizations that promote discussion on inclusive policy creation that benefits all economies, such as the International Labour Organization, are also playing an important role [12].
Artificial Intelligence possesses the capability to transform global companies, generating novel job roles and augmenting efficiency across multiple domains. Artificial Intelligence is being utilized to improve performance and streamline processes in industries like healthcare, banking, manufacturing, and agriculture [13]. AI-driven diagnostic technologies, for instance, can help physicians diagnose patients more quickly and accurately while freeing up staff members to concentrate on patient care. AI innovations in agriculture, such as precision farming, are assisting farmers in raising agricultural yields while using fewer resources.
Data science, machine learning, AI ethics, and robotics are just a few of the industries where AI is creating a demand for new jobs. Investments in AI R&D are anticipated to result in a boom in employment creation in the technology industry for the countries involved [14]. As an example, nations such as India, China, and the US are spearheading AI innovation, which is resulting in the creation of well-paying positions in software development, engineering, and AI research. Furthermore, artificial intelligence is encouraging entrepreneurship, as firms are emerging to create AI-powered products and services for both domestic and international markets.
7. Conclusion
The potential coexistence of humanity and artificial intelligence. As long as certain requirements are satisfied, coexisting artificial intelligence (AI) and humans is not only feasible but also extremely beneficial. AI has the potential to significantly improve the quality of human life by enhancing areas such as healthcare, education, and industry. It functions as an instrument that augments human capabilities rather than supplants them. Designing and implementing AI with human well-being at the vanguard is the critical factor in achieving this positive coexistence. The ethical aspect is one of the main difficulties. AI systems should be fair, transparent, and human rights compliant in order to promote peaceful and fruitful cooperation. Preventing negative effects like prejudice, invasions of privacy, or unethical surveillance will need the establishment of governance structures that control AI development and application. Because AI automates work and may eventually make some employment obsolete, the issue of job displacement also emerged. Nonetheless, this can be mitigated by funding reskilling initiatives, which enable employees to shift into new positions that accompany technological innovation. To develop economic models that are able to accommodate these developments, governments and companies will need to work together through collaboration. Maintaining human control over AI systems is another important component. AI needs protections to keep it from making judgments that could endanger people as it becomes more independent. Building safety and accountability into AI development is essential to preserving confidence. The use of AI brings up psychological questions about what intelligence is and what it means to be human. Whether AI is used as cutting-edge instruments or as collaborators in human pursuits, society will need to determine its place in this world.
References
[1]. Okuda, T., Shiotani, S., Sakamoto, N., & Kobayashi, T. (2013). Background and current status of postmortem imaging in Japan: short history of “Autopsy imaging (Ai)”. Forensic Science International, 225(1-3), 3-8.
[2]. Khakurel, J., Penzenstadler, B., Porras, J., Knutas, A., & Zhang, W. (2018). The rise of artificial intelligence under the lens of sustainability. Technologies, 6(4), 100.
[3]. Kaul, V., Enslin, S., & Gross, S. A. (2020). History of artificial intelligence in medicine. Gastrointestinal endoscopy, 92(4), 807-812.
[4]. Judijanto, L., Asfahani, A., & Vandika, A. Y. (2022). 21st Century Economic Transformation: The Impact of Artificial Intelligence on Markets and Employment. Journal of Artificial Intelligence and Development, 1(1), 41-48.
[5]. Furman, J., & Seamans, R. (2019). AI and the Economy. Innovation policy and the economy, 19(1), 161-191.
[6]. Eager, J., Whittle, M., Smit, J., Cacciaguerra, G., & Lale-Demoz, E. (2020). Opportunities of artificial intelligence. European Parliament.
[7]. Kaplan, A., & Haenlein, M. (2020). Rulers of the world, unite! The challenges and opportunities of artificial intelligence. Business Horizons, 63(1), 37-50.
[8]. Schiff, D., Biddle, J., Borenstein, J., & Laas, K. (2020, February). What's next for AI ethics, policy, and governance? a global overview. In Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (pp. 153-158).
[9]. Radu, R. (2021). Steering the governance of artificial intelligence: national strategies in perspective. Policy and society, 40(2), 178-193.
[10]. Valle-Cruz, D., Alejandro Ruvalcaba-Gomez, E., Sandoval-Almazan, R., & Ignacio Criado, J. (2019, June). A review of artificial intelligence in government and its potential from a public policy perspective. In Proceedings of the 20th annual international conference on digital government research (pp. 91-99).
[11]. Roberts, H., Cowls, J., Hine, E., Mazzi, F., Tsamados, A., Taddeo, M., & Floridi, L. (2021). Achieving a ‘Good AI Society’: Comparing the Aims and Progress of the EU and the US. Science and engineering ethics, 27, 1-25.
[12]. Hagerty, A., & Rubinov, I. (2019). Global AI ethics: a review of the social impacts and ethical implications of artificial intelligence. arXiv preprint arXiv:1907.07892.
[13]. Miailhe, N., & Hodes, C. (2017). Making the AI revolution work for everyone. The Future.
[14]. Yu, C. (2023). AI Revolution: Reshaping Global Value Chains for the Future. Center for Open Science. https://osf. io/n6hb2/download.
Cite this article
Fan,X. (2024). Artificial Intelligence's Impact on Employment: Challenges, Potential Consumers, and Policy Responses Through Automation and Workforce Rehabilitating. Lecture Notes in Education Psychology and Public Media,73,67-72.
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The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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References
[1]. Okuda, T., Shiotani, S., Sakamoto, N., & Kobayashi, T. (2013). Background and current status of postmortem imaging in Japan: short history of “Autopsy imaging (Ai)”. Forensic Science International, 225(1-3), 3-8.
[2]. Khakurel, J., Penzenstadler, B., Porras, J., Knutas, A., & Zhang, W. (2018). The rise of artificial intelligence under the lens of sustainability. Technologies, 6(4), 100.
[3]. Kaul, V., Enslin, S., & Gross, S. A. (2020). History of artificial intelligence in medicine. Gastrointestinal endoscopy, 92(4), 807-812.
[4]. Judijanto, L., Asfahani, A., & Vandika, A. Y. (2022). 21st Century Economic Transformation: The Impact of Artificial Intelligence on Markets and Employment. Journal of Artificial Intelligence and Development, 1(1), 41-48.
[5]. Furman, J., & Seamans, R. (2019). AI and the Economy. Innovation policy and the economy, 19(1), 161-191.
[6]. Eager, J., Whittle, M., Smit, J., Cacciaguerra, G., & Lale-Demoz, E. (2020). Opportunities of artificial intelligence. European Parliament.
[7]. Kaplan, A., & Haenlein, M. (2020). Rulers of the world, unite! The challenges and opportunities of artificial intelligence. Business Horizons, 63(1), 37-50.
[8]. Schiff, D., Biddle, J., Borenstein, J., & Laas, K. (2020, February). What's next for AI ethics, policy, and governance? a global overview. In Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (pp. 153-158).
[9]. Radu, R. (2021). Steering the governance of artificial intelligence: national strategies in perspective. Policy and society, 40(2), 178-193.
[10]. Valle-Cruz, D., Alejandro Ruvalcaba-Gomez, E., Sandoval-Almazan, R., & Ignacio Criado, J. (2019, June). A review of artificial intelligence in government and its potential from a public policy perspective. In Proceedings of the 20th annual international conference on digital government research (pp. 91-99).
[11]. Roberts, H., Cowls, J., Hine, E., Mazzi, F., Tsamados, A., Taddeo, M., & Floridi, L. (2021). Achieving a ‘Good AI Society’: Comparing the Aims and Progress of the EU and the US. Science and engineering ethics, 27, 1-25.
[12]. Hagerty, A., & Rubinov, I. (2019). Global AI ethics: a review of the social impacts and ethical implications of artificial intelligence. arXiv preprint arXiv:1907.07892.
[13]. Miailhe, N., & Hodes, C. (2017). Making the AI revolution work for everyone. The Future.
[14]. Yu, C. (2023). AI Revolution: Reshaping Global Value Chains for the Future. Center for Open Science. https://osf. io/n6hb2/download.