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Disruptive Technology Assignment AI-Automation: Helping Business or Polarizing Jobs?

Richard Mentle (ENES464)

New technologies are integrating the physical, digital, and biological worlds in what has been called the “Fourth Industrial Revolution” (Schwab, 2016). Major technological innovations include drones, robotics, sustainable clean energy, ubiquitous communications/connectivity, 3D-printing, automation, and artificial intelligence (AI) to augment human capabilities, products, and business. These will undoubtedly have significant consequences on the future global community, but here we will examine how automation coupled with AI is changing many businesses, and in turn, is changing society.

 

Augmenting automation with AI has given new capabilities to simply robots. These enhancements provide innovation to both products and process. From AI-powered robots that automatically order stock when inventory runs low, to drones and self-driving trucks delivering merchandise, AI-automation is changing the way products are built and delivered. New companies will be created and others will grow who deliver the AI-automation tools. Companies could receive substantial revenue growth through product diversification and market growth, as was discussed in class. Companies may obtain new revenue streams, expand into new industries, and create new jobs to develop, deploy and support the AI-automation equipment.

 

From a process innovation perspective, AI-automation has the potential to reduce costs but at the expense of the current workforce. It can be used anywhere a repeatable and definable process is needed. Historically, this is the domain of the low-skilled worker. Overall, AI-automation can be used in the most core part of the value chain. By pulling out major labor costs, improving the economics of the business is done by reducing the cost of production and reducing the cost of delivery.  Therefore, your product can be manufactured at a lower cost with more consistency and higher quality.

 

Where automation works best is with repeatable processes. This impacts the low and unskilled labor force. Even McDonalds is moving from cashiers to kiosks; a person taking orders is no longer needed.  But automation with AI does not just impact low-skills occupations.  As shared by Morgenstern (2016), “in a test against three expert human radiologists, Enlitic, a start-up medical AI company’s system was 50% better at classifying malignant tumors and had a false-negative rate of zero, compared with 7% for the humans.” So even highly trained white-collar job tasks can be automated. Frey and Osborne (2013) examined the probability of computer automation for 702 occupations and found that close to 50% of total U.S. employment is at risk. Indeed, what determines susceptibility to automation is not so much the type or skill level of work concerned, but whether it is routine. As discussed in class, “job polarization” could be a significant consequence for global society. Increasing this segregation could lead to an increase in social tensions.

Bessen, J. (2016) The automation paradox: When computers start doing the work of people, the need for people often increases. The Atlantic. Retrieved from https://www.theatlantic.com/business/archive/2016/01/automation-paradox/424437/

Frey, C. B., and Osborne, M.A. (2013). The future of employment: How susceptible are jobs to computerisation? Oxford Martin School. University of Oxford, Oxford, England.

Schwab, K. (2016). The fourth industrial revolution: What it means, how to respond. Global Agenda. World Economic Forum.

Morgenstern, M. (2016). Automation and anxiety: Will smarter machines cause mass unemployment? Special Report: Artificial intelligence: The impact on jobs. The Economist. The Economist Group Limited, London.

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