Impact of AI on Employment – Positive and Negative Aspects

The implications of Artificial Intelligence on employment would be described in this section, using One search, as it has already transform the world of work. In the assessment task 1 and 2, it has been discussed about the Information Technology use in the designing and coding of the website. Based on it most of the jobs that are seen are at the risk of automatization with the advancement of AI (Brynjolfsson, Rock & Syverson, 2017). In the decades that are coming, only narrow range of tasks will be taken by the robots. For the new industrial revolution, a broad economic policy response would be prepared. Virtual learning techniques have helped machines to perform physical and cognitive tasks in a wide range. The work that they do is expected to increase the efficiency and accuracy (Nilashi et al., 2015). The AI systems advance through increased computational power, big data and machine learning. The benefits for the use of machine are clear for the human work and employment. If the performance of the machine goes beyond the levels of human then a question arise in mind is that whether the humans’ jobs are at risk due to the implication of machine which may reduce the employment (Frey & Osborne, 2017).

The implications of AI would affect the employment in both negative and positive way. If it is considered negatively then it would display the workers from the tasks that they were performing previously (West, 2015). On the other hand, if it is considered positively then it would present the increased demand for the labour for other industries or jobs which arises due to automation. If it is checked back into the previous industrial revolutions during the 19^th century then it can be seen that the amount of coarse cloth a single weaver produce in an hour increases by factor of 50. However, when checked through the amount of labour required per yard for the cloth was 98 per cent (Russell, Dewey & Tegmark, 2015). As a result, cloth has become cheaper and increases its demand. Thus, it creates more jobs for long run.

There was another case study in which introduction to automobiles led to decline in jobs that are related to horse. With the emergence of new industries has resulted in positive impact on employment (Chui, Manyika & Miremadi, 2015). The automobile industry grew fast and increases the availability of jobs in the sector. With the increase in the number of vehicles, different sectors have created different jobs. Thus, the cases that are analysed in the past suggest that the displacement effect has dominated. However, during the longer run markets and society were fully adapted to automation shocks. The effect of productivity could lead to a positive impact on the employment. With the most recent technological developments large volumes of legal documents are introduced which reduces the cost however increases its demand.  

Types of AI Technologies

Artificial Intelligence (AI) has got a consistent progress which help in improving their capabilities for business, medicine and automotive (Wisskirchen et al., 2017). The major industries and organization has predicted that machine could do or perform any work that a human can perform. The field of AI could be grown dramatically. The basic technologies comprise the AI implication includes:

Boolean Search: Boolean Search are algorithms that allow the user to combine the keywords along with the operators which include AND, OR and NOT to produce a more relevant results. Thus, the result that was produces would limit the search for those documents that contains two keywords (Raza & Khosravi, 2015). 

Machine Learning: Machine Learning is part of data analysis method that could automate the analytical building model. Algorithms are used from the data that are learning iteratively. A cloud based AI product generally provides the Application Program Interfaces (APIs) were all forms of data are understood that could reveal the business-critical insights which could harness the power of cognitive computing. There are various products of APIs that are organized to build a cognitive search and a content analytics engines. A meaningful insight is built for the applications that have an unstructured text. The user can use iPhone in Amazon Alexa were an order could be place for a toilet paper. Making an inquiry for customer service or paying bill through phone will bring them in contact with each other by designing a computer algorithm that would address the need. Machine seems to have surpassed the performance of the human. The AI technology impacts the work of human beings.

Natural Language Search (NLS): The NLS comprises of algorithms that could perform the search by identifying the content to match the topic that the user describe in a plain language. As NLS is an AI based technology, it can understand the things that are written in the document, web page, tables, and databases similar to humans.

Natural Language Processing (NLP): The NLP comprises of the algorithms that has allow the computer to understand and process the human languages. NLP is the component of the Artificial Intelligence and it is in the computer program that enables the system to understand the human language that is spoken.

In assessment 1 and 2, I have discussed about the designing and had reviewed for every case from various articles. The articles that were reviewed for this report helped to take immediate actions. Though AI would not display the job categories but would make easier the job for the future as there are more tasks that are automated to improve the productivity or safety. AI is not a future technology for organizing the data or makes the live of human easier or uncovers the trends. The enterprise has got a positive impact from AI (Acemoglu & Restrepo, 2018). I found one thing to be very clear about this technology is that a lot of disruption would be going on in the coming 5 to 10 years where each technology have got their own way of working. When the data set were evaluated about the task that would be better done by AI and human respectively. I found that for the web development each skill set has been evaluated to determine the tasks that could be done better and were performed better by the humans. There are plenty of jobs that could be done by AI much better than the humans. However, humans have still excelled plenty of tasks over AI.

Case Studies

There are instances were robots can help alleviate the employees without making them losing their tasks through menial, tedious, time-consuming or tasks that are physically-strenuous. In most of the scenario it is scene that robots had built a collaboration of working together. The value of AI is so much that it can bring a huge difference in the enterprise were there has been provide a set of input to map with the set of output (Holtgrewe, 2014). There are tasks that require strength and efforts. In such case automating one skill would not replace other workers. Workers have achieved more upward growth and the workers were having opportunities were they could work on a more complex tasks. I have now learned that with this research I can make a clear idea about the writing skills that are enhance with the ability to read, analyse the power to write and have to search for common themes. During the research, the articles were very much helpful as it has the ability to learn and approaches were made to encourage the commonalities. 

References

Acemoglu, D., &Restrepo, P. (2018). Artificial Intelligence, Automation and Work (No. w24196). National Bureau of Economic Research.

Brynjolfsson, E., Rock, D., &Syverson, C. (2017). Artificial intelligence and the modern productivity paradox: A clash of expectations and statistics. In Economics of Artificial Intelligence. University of Chicago Press.

Chui, M., Manyika, J., &Miremadi, M. (2015). Four fundamentals of workplace automation. McKinsey Quarterly, 29(3), 1-9.

Frey, C. B., & Osborne, M. A. (2017). The future of employment: how susceptible are jobs to computerisation?. Technological forecasting and social change, 114, 254-280.

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), 9-24.

Nilashi, M., Ibrahim, O., Mirabi, V. R., Ebrahimi, L., &Zare, M. (2015). The role of Security, Design and Content factors on customer trust in mobile commerce. Journal of Retailing and Consumer Services, 26, 57-69.

Raza, M. Q., &Khosravi, A. (2015). A review on artificial intelligence based load demand forecasting techniques for smart grid and buildings. Renewable and Sustainable Energy Reviews, 50, 1352-1372.

Russell, S., Dewey, D., &Tegmark, M. (2015). Research priorities for robust and beneficial artificial intelligence. Ai Magazine, 36(4), 105-114.

West, D. M. (2015). What happens if robots take the jobs? The impact of emerging technologies on employment and public policy. Centre for Technology Innovation at Brookings, Washington DC.

Wisskirchen, G., Biacabe, B. T., Bormann, U., Muntz, A., Niehaus, G., Soler, G. J., & von Brauchitsch, B. (2017). Artificial intelligence and robotics and their impact on the workplace. IBA Global Employment Institute.