Artificial Intelligence (AI), which is also popularly known as machine intelligence is a form of intelligence that is primarily demonstrated with the help of computing machines. This form of intelligence is deeply contrasted with natural level of intelligence that are displayed mostly by humans. The use of AI provides a way of designing special algorithms that would enhance the working of a computer, a software or a controlled robot in order to work just in the same manner as humans (Russell and Norvig 2016).
The functionalities of AI is mostly accomplished by studying the nature of the thinking of humans. AI based methods also help in deciding the factors in which humans would be able to think, decide about several factors, learn specific tasks and try to solve a particular form of problem. The outcomes of the study would be able to decide for a computer to develop intelligent form of specially designed algorithms and systems (Ghayvat et al. 2015).
The extensive use of AI functionality within the sector of jobs has impacted the world in several ways. There are various noticeable concerns in regards to the upcoming impact of AI technology based on the workforce and employment.
The key terms that were used for various search within my strategy of search are automation, neural network, deep learning algorithms, assembly-line and self-driven vehicles. I have also made use of Google search, Google books, which have helped me to understand the topic of my search strategy and thus focus on the importance of the topic. The underlying databases that were used are Google Scholar. These databases were used for searching index articles on specific topics based on my research.
The cases of automation or the use of AI within the job sectors have made a major impact for the benefits within the organization. This impact of AI within the sector of jobs have made a major impact within the jobs. The rising concern of AI has decreased the number of people who used to perform some specific tasks. Robots are replacing humans as some bots are able to perform the critically acknowledged tasks (Chui, Manyika and Miremadi 2015). This process is making the progress of jobs in an easier manner.
The use of inclusion and exclusion criteria have also helped me to choose the current topic of discussion. These criteria mainly focus on the previous records based on the topic and previous researches that had been made on the topic. Both of these criteria helped me in gathering data based on appropriateness of the subject. The articles are mainly gathered based on the various form of reviews and experiences of people who have experienced the impact of automation within their workplace. This has helped me to extract a significant relevance to the topic of my research.
The extensive use of AI has dramatically helped in improving the world of jobs. There are several business or job sectors, which have decided to utilize the AI based technology within their workplace in order to increase the efficiency within their area, increase growth of revenue, reduce the costs of operation and also improve the experience of customers (Arntz, Gregory and Zierahn 2016).
With the deployment of the right form of AI technology within any industry or business, it has been found that the organization would be able to gain certain benefits:
The underlying fear that are faced by businesses, organizations and employees is that the impact of automation within the job sector would take away the jobs of the employees. This might happen as most of the critical jobs, which are mainly performed by people in the recent times would be taken over by computer operated bots. However, various professionals based within this field have understood the potential and opportunities for organizations to upgrade the workforce and thus transform the experience of the users (Noble 2017).
Embracing the new form of AI technology is a crucial factor. Implementation of the technology within manufacturing industries would transform the sector. Although it is a time-consuming process that would make use of much valuable resources. The underlying technology is not only able to provide reliable and consistent form of outcomes but it also has the potential to evolve with the integration of AI and big data within agile machines (Demirkan and Delen 2013).
With the increasing factor of productivity within organisations, it could be confirmed that more amount of money and time could be invested for engagement within the workforce. This would in turn help in developing a strong culture within the company. The high rate of retention of workers within the organisation is possible as these employees would have more time for learning innovative ideas and concepts. They would also be able to counter the long unproductive work hours by enhancing their skills and knowledge by learning the new technologies that would be implemented within the workplace (Jones and Sallis 2013).
Different innovative trends would include a flexible working environment or reduced hours of office. The rise and the impact of AI would be able to make the employee happier, much more relaxed and ultimately create a productive workplace experience. This would provide much more significant benefits within every aspect of the business.
There are several tasks within some organizations, which are monotonous in nature. These kinds of tasks could be transformed with the help of automated machines. The automation of such kind of tasks would make some kind of tasks to be obsolete. There are some kinds of activities and tasks, which are in relation with the classification of documents, retrieval and discovery of information, operations of call centre/customer care and modification of internal contents (Smith and Anderson 2014). These kind of tasks would be much more based upon the automation technology and thus would reduce the work of humans. This same kind of roles of automation would also be in relation with the support and operation along the production lines within factories. In these kind of workplaces, humans are majorly being replaced by smart-bots. These bots would be able to navigate the space in a sage manner, detect and move objects and also be able to perform different complex operations based on assembling of products, tools or parts. Implementation of AI within the organization would also be effective within handling of extensive form of complex activities (Malysheva et al. 2016). These activities would require the processing of streams of data, accumulated signals and multiple signals in real time scenario.
Transportation is one of the sector, which is in a high mode of transformation. The use of fully autonomous cars would be a scene of reality in the future. These cars would be safer, much effective and efficient. There are some professional drivers who would see the demand of their skills to drop in a rapid manner (Rossetti et al. 2013).
The electronic commerce sector would also experience a substantial transformation. The fulfilment sectors would be automated fully. In these centres, it could be witnessed that the AI controlled bots would be able to collect products, execute the orders placed by customers, and decide the locations of sending orders to customers based on the help of autonomous cars or drones. There would also be a massive shrink on the prime importance of salespersons and the extensive networks of physical stores. Based on the perspective of future scenarios, it could be acknowledged that customer based AI agents would be able to negotiate with retailer based AI agents and thus would discuss different tactics, objectives and strategies.
There are some traditional professions that are primarily based upon strong human relationships. Legal professions is one such example that would impacted significantly. The AI agents would be able to handle different form of support services such as extraction of knowledge, classification and handling of documents that are based within the legal context (Prendinger and Ishizuka 2013).
The context of automation within the insurance and financial services would also require a major amount of processing of data and other forms of content handling mechanisms. These sectors would also be benefited with the implementation of AI. The AI could also play a major role in the process of elimination of bureaucracy, which would help in improving design and performance based on social programmes and also improvement of citizenship services (Barrett et al. 2015).
The impact of automation or AI has also contributed to extreme level of shifts within the employment sector. There are many sectors beyond the reach of manufacturing that are now being impacted in the recent times. Some of the popular examples of the reach of automation within some sectors include kiosks. In these places, smart devices such as tablets are majorly used for the purpose of placing orders and paying within restaurants (David 2015). Robots are used extensively for the processing of packages within warehouses and self-driven vehicles.
With the advancement of deep learning algorithms and AI, it has been seen that the recent softwares would be able to detect the different patterns of data. This would enable the allowance of judgemental decisions and non-routine tasks to be performed in an automated fashion. The combination of advances within machine learning and mobile based robotics could also be able to permit the manual tasks to be performed in an automated manner (Mnih et al. 2015). The traditional based tasks, which would be performed only by humans are now being replaced with bots who are able to control the workflow.
What would be the impact of emerging AI technologies on public policy and employment in the future?
Conclusion
Based on the discussion from the above report, it could be concluded that the impact of AI within the transformation of the job sector has their advantages as well as disadvantages. Though the implementation of AI within the workplace would help in increasing the level of productivity, enhance the efficiency within the workplace and reduce the costs of operation, it would also leave a major impact on the replacement of jobs that were traditionally performed by humans. The use of AI would also might play a major role of support to humans and would thus empower them to increase their level of performance. As various organizations would implement AI based systems, there would be an increased need for employing highly skilled professionals who would hold the responsibility for overseeing, managing and coordinate the training systems of complex AI systems. This would help in ensuring the integrity, objectivity, security factors and maintain a proper use of the computing systems. With some form of assumptions based on the disruption of technological unemployment due to AI revolution, it could also be concluded that the new age of AI would also bring creativity, well-being and prosperity. This would also lead towards flexible and premium service offerings.
Based on the drawn conclusions, it could be recommended that with the empowerment of AI within organizations, it would be help in handling critical and complex situations. With the impact of AI on jobs of employees, it could be recommended that different societies would need to adapt according to the newer form of technological landscape (Makridakis 2017). They should also need to adapt towards flexible approaches and also be able to inherit of learning newer technologies, collaborate with companies and discover newer methods of innovation. New forms of strategy should be developed that would be able to focus on education, rethink about the working within the current companies, markets and employment sectors. These companies who would be inheriting AI based solutions should be able to redesign the social based mechanisms in order to cover the new range of situations and scenarios based on the job sectors (Holtgrewe 2014).
References
Arntz, M., Gregory, T. and Zierahn, U., 2016. The risk of automation for jobs in OECD countries.
Barrett, M., Davidson, E., Prabhu, J. and Vargo, S.L., 2015. Service innovation in the digital age: key contributions and future directions. MIS quarterly, 39(1), pp.135-154.
Chui, M., Manyika, J. and Miremadi, M., 2015. Four fundamentals of workplace automation. McKinsey Quarterly, 29(3), pp.1-9.
David, H., 2015. Why are there still so many jobs? The history and future of workplace automation. Journal of Economic Perspectives, 29(3), pp.3-30.
Demirkan, H. and Delen, D., 2013. Leveraging the capabilities of service-oriented decision support systems: Putting analytics and big data in cloud. Decision Support Systems, 55(1), pp.412-421.
Ghayvat, H., Liu, J., Mukhopadhyay, S.C. and Gui, X., 2015. Wellness sensor networks: A proposal and implementation for smart home for assisted living. IEEE Sensors Journal, 15(12), pp.7341-7348.
Holtgrewe, U., 2014. New new technologies: the future and the present of work in information and communication technology. New technology, work and employment, 29(1), pp.9-24.
Jones, G. and Sallis, E., 2013. Knowledge management in education: Enhancing learning & education. Routledge.
Makridakis, S., 2017. The forthcoming Artificial Intelligence (AI) revolution: Its impact on society and firms. Futures, 90, pp.46-60.
Malysheva, T.V., Shinkevich, A.I., Kharisova, G.M., Nuretdinova, Y.V., Khasyanov, O.R., Nuretdinov, I.G., Zaitseva, N.A. and Kudryavtseva, S.S., 2016. The sustainable development of competitive enterprises through the implementation of innovative development strategy. International Journal of Economics and Financial Issues, 6(1), pp.185-191.
Mnih, V., Kavukcuoglu, K., Silver, D., Rusu, A.A., Veness, J., Bellemare, M.G., Graves, A., Riedmiller, M., Fidjeland, A.K., Ostrovski, G. and Petersen, S., 2015. Human-level control through deep reinforcement learning. Nature, 518(7540), p.529.
Noble, D., 2017. Forces of production: A social history of industrial automation. Routledge.
Prendinger, H. and Ishizuka, M. eds., 2013. Life-like characters: tools, affective functions, and applications. Springer Science & Business Media.
Rossetti, R.J., Almeida, J.E., Kokkinogenis, Z. and Gonçalves, J., 2013. Playing transportation seriously: Applications of serious games to artificial transportation systems. IEEE Intelligent Systems, (4), pp.107-112.
Russell, S.J. and Norvig, P., 2016. Artificial intelligence: a modern approach. Malaysia; Pearson Education Limited,.
Smith, A. and Anderson, J., 2014. AI, Robotics, and the Future of Jobs. Pew Research Center, 6.
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