How Automation Is Playing In The Current Set Up Of The Economy And How The Rapid Progress In The Same Is Leading To Taking Away The Jobs From The People?
The automation in the technology and the processes and accounting has made a rapid change in the mind set and the way in which people foresee the future of manpower resourcing. It is foreseen that the rapid automation spree will eat away the jobs in hand and will render the humans jobless in the long run. All the manual processes which used to take a lot of time in the past are now getting automated and with the introduction of the modern technologies like cloud computing, blockchain technology and artificial intelligence it will become all the more difficult for the human beings to stay in competition with the machine and automation. In the coming section, the impact of the automation and the way forward has been discussed.
In the given article it has been mentioned that with the advance in the automation, all the social and the psychological ills of joblessness among the people will grow day in and day out and will thereby lead to economic recession and unemployment among the youth which in turn will result in the loss of personal identity. The rise in the automation practices has made human activities redundant and has crept in laziness amongst the peoplw who are losing creativity and zeal to add to the value chain (Alexander, 2016). On the other hand, efficiency and effectiveness has grown big time with the advent to automatic machines and programs which drive things based on a fixed instruction and time. This is also attributable to the growth in artificial intelligence which will slowly take away all the manual practices and do work on its own. Therefore, the idea now is what else is beyond automation because even the machines would need human intervention to check if there are any issues and shortcomings or what if there would be better thinking machines to assist the set of people who can then produce miraculous results (Boccia & Leonardi, 2016). Another useful insight of the automation is the big data management which has emerged in recent times such that the data of all types and companies are being retrieved over the cloud and different types of study can be made out of it. The progress in automation is a threat to humans in a way that automation is a one time investment and is cheap as compared to employing the human labour but the disadvantage of the same is that the machines cannot make accurate and exact decision as the humans can make it. So there needs to be made a proper balance between the human intelligence and decision making and how far it can be supported by the intelligent machines (Belton, 2017).
The threat of automation to the human behaviour and the manpower can thus be turned into a set of opportunities if seen in a different perspective. There are various avenues and examples where it can be seen that knowledgeable workers do collate with the machines and technologies to give out results that would otherwise not have been achievable in case they would have worked alone. It is therefore, important to find and establish the right mix of the technology and the human effort so that the efficiency and effectiveness with which the work is being done can be maximised and humans can be best utilised with alongside automation (Bromwich & Scapens, 2016). Automation is sometimes being regarded as pain as it is a race to the bottom and humans generally prefer to be served by the humans. Furthermore, it will lead to the substantial displacement of the unskilled workers who will be rendered jobless in the economy and the fear of unemployment would be looming large. But instead there would be an increase in jobs working alongside smart machines. Some of the knowledge based jobs which can be automated in the long run are teacher or professor with the online content and robotic lecturing, lawyer with predictive coding, accountants with automated audits and taxation functions, radiologist with automated detection of cancer, reporter with automated report writing based on the various scenarios, marketer with pre-fit personalized email functions, financial advisors with robo based advisors, architect with automated drafting and designing, financial asset manager with indexed funds and pharmaceutical scientists with cognitive creation technologies of new drugs (Choy, 2018). Therefore, most of the knowledge based work can also be replaced with machines and automation but the question is how accurate it will be and what can be the inefficiencies and shortcomings for which the human effort and intelligence will be required as any stage. Some of the technologies which are driving the knowledge based work automation include machine learning, rule engines, analytics and big data, complex event processing, robotic process automation, cognitive computing, and integration of all of these technologies in the cognitive cloud environment (Fay & Negangard, 2017).
From the above issue, it can be interpreted that the need of the hour is to find a way by which humans can add value in the value chain and can use automation to the best without letting go away their jobs. There are basically 5 methods or approaches that can be used to make peace with the smart machines (Dumay & Baard, 2017). The 1st one is stepping up to the higher level of cognitive thinking or models which the machines won’t be able to follow or can’t reach to. The 2nd approach which can be taken is to step aside and draw on various forms of intelligence that machines cannot reach out to or they lack the same. The 3rd approach would be use the automation and monitor it continuously to find out the inner intrecacies, if any, post which necessary adjustments can be made to the computer’s decision making process (Grenier, 2017). The 4th approach is opting for specialising in one of the core areas and to use this expertise to add value as automation cannot solve all the issues and hence manual support is always required. And, the final and 5th approach that can be followed is creating next generation machines or making further innovation in the existing ones so that they can be augmented and supplemented by the worker’s strength to give innovative results (Zhou, 2018). All the approaches mentioned above can bring a leap frog development to the very idea of automation. The very prespective of looking at the automation needs to change, it does not really means elimination of the manpower or human resource and replacing the humans with machine, it rather means handing over the redundant and routine and non value adding activities to the automation bound programs so that the humans can focus on other critical and significant topics (Marques, 2018).
There have been alltogether 3 eras of the automation process, the 1st one in the 19th century taking away the manual labour and reliveing the humans from it by the use of machines and industrial equipment. The 2nd one was in 20th century when machines took away all the dull and routine services job from the humans and call centres took charge of the clerical and routine transactions (Piesse, 2017). The 3rd and final era of automation in the 21st century is the most interesting one when the automation has developed in such a way that the machines are being able to tae decisions based on the model of artificial intelligence and other intelligent systems making it faster than humans and reliably.
The impact on people is what we need to access: whether it is truly automation or augmentation. Smart people working with smart machines simultaneously, this is augmentation, humans do this by supporting machines in tasks where humans are better than machines and similarly take help of the systems in few tasks where machines are better and faster than humans. The classic example of the augmentation is the freestyle chess which are better than humans and automated chess system working alone. It has got multiple computer recommended moves amongst which the humans can choose and thereby it can be said that the humans know the strengths and weaknesses of the different systems and programs (Vieira, et al., 2017). We can also see similar examples in excel, etc. Augmentation is likely to prevail in many areas like where knowledge and experience is the bottleneck like veterinary diagnosis and treatment, the fields where quality decision making required with utmost consistency like underwriting the insurance policies, where there is too much data or content for humans to act and analyse like digital marketing (Visinescu, et al., 2017).
Conclusion
From the above discussion and analysis, it can be said that automation has brought about disruptive changes in the market and it has made difficult for the unskilled workers to handg up to their jobs. Thsus, there is a need of cognitive thinking and skill development among the humans so that they can work alongside smart machines and can get the work done. From the organizational perspective, augmentation is the idea which should be persisted with picking up right technology for the problem and encouraging simultaneous working of the smart humans and smart machines, giving them options to bring about the transition in a phased manner. For government, it is important that they give a public dialogue on augmentation and automation and they need to guarantee the jobs, not income and engaging NGOs and private sector organizations for planning and policy formulation. Thus, it can be conclude that the though the technology is good and improving faster in terms of automation but it should be seen beyond that and augmentation of humans and machine is required alongwith improvement and innovation in the cognitive processes.
References
Alexander, F., 2016. The Changing Face of Accountability. The Journal of Higher Education, 71(4), pp. 411-431.
Belton, P., 2017. Competitive Strategy: Creating and Sustaining Superior Performance. London: Macat International ltd.
Boccia, F. & Leonardi, R., 2016. The Challenge of the Digital Economy: Markets, Taxation and Appropriate Economic Models. s.l.:Springer.
Bromwich, M. & Scapens, R., 2016. Management Accounting Research: 25 years on. Management Accounting Research, Volume 31, pp. 1-9.
Choy, Y. K., 2018. Cost-benefit Analysis, Values, Wellbeing and Ethics: An Indigenous Worldview Analysis. Ecological Economics, p. 145.
Dumay, J. & Baard, V., 2017. An introduction to interventionist research in accounting.. The Routledge Companion to Qualitative Accounting Research Methods, p. 265.
Fay, R. & Negangard, E., 2017. Manual journal entry testing : Data analytics and the risk of fraud. Journal of Accounting Education, Volume 38, pp. 37-49.
Grenier, J., 2017. Encouraging Professional Skepticism in the Industry Specialization Era. Journal of Business Ethics, 142(2), pp. 241-256.
Marques, R. P. F., 2018. Continuous Assurance and the Use of Technology for Business Compliance. Encyclopedia of Information Science and Technology, pp. 820-830.
Piesse, E., 2017. Mobile phones and Siri-style assistants a growing threat to online security, s.l.: s.n.
Vieira, R., O’Dwyer, B. & Schneider, R., 2017. Aligning Strategy and Performance Management Systems. SAGE Journals, 30(1).
Visinescu, L., Jones, M. & Sidorova, A., 2017. Improving Decision Quality: The Role of Business Intelligence. Journal of Computer Information Systems, 57(1), pp. 58-66.
Zhou, C. &. P. A., 2018. Developing creativity and learning design by information and communication technology (ICT) in developing contexts. Encyclopedia of Information Science and Technology, pp. 4178-4188.
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