Technological advancements in modern society have both positive and negative implications in various aspects. Most of the problems experienced daily can be solved by technology. Innovations are becoming a tool for measuring progress and good life. Data plays a crucial role in establishing power relations via the collection capability of machines that generate knowledge. Data is perceived as information collected and spread via professional and public communication systems in the media industry. Media technologies such as smartphones integrate diverse broadcast, storage, and data-sharing roles. This advancement converts daily experiences into information that can be assessed, shared or used for political mileage. Technological advancement has enhanced surveillance in different sectors. Drones and other devices have been adopted to survey areas of concern and gather the data needed for particular tasks (Gates, 2017, pp. 187). Exploring the impact of AI on the future of work offers valuable insights into a transformative and influential aspect of our society. This essay will mainly explore AI’s present and future impact on the job market.
The Current State of Technology
Technological advancement is currently replacing human beings in various sectors. Surveillance is one of the areas that have benefited from artificial intelligence. It aims to oversee the activities undertaken in a specific place to determine whether the set rules are followed and identify those participants deviating from the limits. Human resource is no longer required to achieve the monitoring. Video cameras, smartphone apps, drones, sensors, microphones, biometrics and satellites have fitted well in surveillance (Gates, 2017, pp. 187). Once mounted in places of interest, they capture all the moments and transmit the data to the appropriate office. Surveillance is majorly associated with major state activities and security departments. It provides regular updates about the state of affairs in different regions of a country. In the section of security, surveillance tends to spy on any terror activities likely to be planned to target a specific place. Once the information is collected, the security personnel takes suitable measures to counter the plans.
Figure 1: AI in Surveillance
Technology and science play a critical role in controlling different perceptions of nature. It reveals the superiority of science over nature and its application in making life simpler. Advancement in technology is considered progress in society since accomplishing tasks is made more accessible. Currently, programmed machines are enabled with face recognition systems, distance learning, robotics, surveillance gadgets and media (Slack, n.d., pp. 192). The invention of new technologies attempts to make the world better by focusing on economic, political and environmental ideologies. However, people have attached much value to technology and ignore that some problems need machine learning collaboration and change in some aspects. For instance, technology cannot solve the problem of global warming singlehandedly. People need to shift from the use of fossil fuels to clean energy. Artificial intelligence would play a very minimal role in improving environmental degradation.
Data systemization in sociology, information and natural sciences initially required humans to analyze. Currently, computational machines can perform the task of evaluating and analyzing data without the need for human intervention (Gregg & Nafus, 2017, pp. 55). Analysis performed by a computerized machine is more accurate as opposed to human analysis. However, technological advancement is only partially advantageous. Since most of the tasks previously performed by humans are computerized, different organizations use machine learning and lay off the employees in charge.
Figure 2: AI in data analytics
Impact of AI on the Future of Work
Artificial intelligence is growing rapidly and can change how people accomplish tasks, learn and apply technology. AI can perform tasks that humans had earlier done. It would play a crucial role in problem-solving, decision-making and language processing. As AI and machine learning continue to evolve, different workplaces are adopting the system to perform repetitive tasks and assist in decision-making (Wang & Siau, 2019, pp.61). The implication is that going into the future, the size of the workforce will shrink, and joblessness will become common. Applying AI in the workplace would lead to enhanced efficiency and increased productivity. The level of accuracy will be highly improved, and the chances of errors occurring become limited.
Challenges Associated with Artificial Intelligence
Understanding and addressing the challenges of AI is crucial. Arguments against the widespread adoption of AI are that it will likely cause job losses, earning inequalities and drainage of human skills (Ernst et al., 2019, pp.4). Data scarcity is one of the major shortcomings of the system. AI relies on trained data to give reliable output. Getting massive amounts of data is challenging and needs human expertise for labelling. The system will generate fake results if the data is not fed well. Artificial Intelligence is prone to limited implementation. An AI system can only be programmed to perform a single task. The system cannot multitask. Creating an AI system with human features has been a great challenge.
Artificial Intelligence is prone to data insecurity. In most cases, the data fed into the system is sensitive and should remain confidential. This system will likely breach and steal private data (Nishant et al., 2020). The transparency of algorithms is another challenge in dealing with artificial intelligence. Machine learning uses algorithms that need to be simplified to be understood by many people. Only experts can understand the output and analyze the trend in the output generated. Explaining the factors leading to predictions made by machines may take work. The system is prone to bias as it depends on the data provided. If the person feeding the information is prejudiced, the output will be biased.
Opportunities for Artificial Intelligence
There are several opportunities associated with Artificial Intelligence. It can lead to the production of new services and products in machinery, tourism, fashion, healthcare and farming. The system can assist in boosting sales, improving machine maintenance, enhancing the quality of production, improving client service and saving energy. When used in public services, AI can lead to reduced costs and provide new chances in education, public transport, waste management and enhance product sustainability. The system strengthens democracy by scrutinizing data and minimizing the chances of misinformation (Ernst et al., 2019, pp.25). The information generated is of high quality and supports diversity. AI is expected to be applied in curbing crimes by the justice sector.
Policy Considerations for Artificial Intelligence
Policy considerations have been formulated to ensure that AI systems are reliable and human-centred. These considerations deal with fairness and ethics, and respect for human democracy aspects. Human privacy should be considered in public policy considerations, and the disadvantages of shifting the current biases from the analogue to the digital era. The issue of gender and racial factors should be given priority in policy considerations (Vollmer et al., 2020). The urge to progress towards a robust, transparent, secure and safe AI system with clearly outlined mechanisms for their output is also underlined. Policies that encourage transparent Artificial Intelligence systems include the ones that encourage responsible programs and establish a virtual ecosystem which does not compromise data privacy. Such systems should support small enterprises to thrive in the market, support competition and enhance smooth transition as employees move from one job to another.
The study of the implications of artificial intelligence on the future of the job market is critical on local, national and global levels because it affects labour, employment procedures and worldwide deliberations on personnel transformation. Employees likely affected are those involved in repetitive tasks that can be easily automated. The implication is that as employers adopt AI, there should also be an alternative for displaced employees.
Ernst, E., Merola, R., & Samaan, D. (2019). Economics of artificial intelligence: Implications for the future of work. IZA Journal of Labor Policy, 9(1). https://sciendo.com/article/10.2478/izajolp-2019-0004
Gates, K. (2017). Surveillance.
Gregg, M., & Nafus, D. (2017). Data.
Nishant, R., Kennedy, M., & Corbett, J. (2020). Artificial intelligence for sustainability: Challenges, opportunities, and a research agenda. International Journal of Information Management, 53, 102104.
Slack, J. D. (n.d.). Technology.
Vollmer, S., Mateen, B. A., Bohner, G., Király, F. J., Ghani, R., Jonsson, P., … & Hemingway, H. (2020). Machine learning and artificial intelligence research for patient benefit: 20 critical questions on transparency, replicability, ethics, and effectiveness. bmj, 368. https://www.bmj.com/content/bmj/368/bmj.l6927.full.pdf
Wang, W., & Siau, K. (2019). Artificial intelligence, machine learning, automation, robotics, future of work and humanity: A review and research agenda. Journal of Database Management (JDM), 30(1), 61-79. https://www.researchgate.net/profile/Keng-Siau-2/publication/333423274_Artificial_Intelligence_Machine_Learning_Automation_Robotics_Future_of_Work_and_Future_of_Humanity_A_Review_and_Research_Agenda/links/5cf48f4b92851c4dd0240f42/Artificial-Intelligence-Machine-Learning-Automation-Robotics-Future-of-Work-and-Future-of-Humanity-A-Review-and-Research-Agenda.pdf