Ethical issues in The 4th Industrial Revolution

Man analysing binary code on virtual screen

By Noor Fadillah Binti Jaafar, Lecturer, School of Business

The Fourth Industrial Revolution was created in 2016 by Klaus Schwab, the World Economic Forum founder and it was published in a book of the same name. Hence, It should be right to extract the idea of it from the book itself which is “The Fourth Industrial Revolution creates a world in which virtual and physical systems of manufacturing cooperate with each other in a flexible way at the global level”.Today, a Fourth Industrial Revolution is underway, in which superintelligent supercomputers are being integrated into daily life and industry, including artificial intelligence (AI) and the Internet of things (IoT). (Kwon, Hwang and Kim, 2019). It is known that the last 100 years of human society have created unprecedented technologies, but it is our social responsibility to keep our Industrial Revolutions “human-focused”. Watch any typical science fiction movie, and there comes a point in every plot where the advanced technologies meant to facilitate life begin to show signs of inevitable problems. Suffice to say, some of the crises highlighted due to advancement from the Fourth Industrial Revolution is somehow made sense. Job loss due to automation, invasion of privacy, information deception, the biases and discrimination by Artificial Intelligence and the ever-growing gap between the rich and the poor, must all be addressed from an ethical perspective.

Much of the concern regarding the fourth industrial revolution on humans losing jobs to the automated machines or robots have been supported by McKinsey Global report. It has been confirmed that up to 800 million jobs will have disappeared by 2030 as a result of automation. It is necessary to highlight that the risk of automation is high for jobs with lower educational requirements, the tasks of which demand lower communicative and cognitive skills. The possibility of the professional sectors like Construction and Manufacturing and Wholesale and Retail Trade for Organisation for Economic Co-operation and Development (OECD) Countries to be highly automated with the estimated percentage up to 45% until 2030. Most experts predict huge changes in occupations that require new skills sets, accompanied by the demise of many occupations; large-scale job losses and a growing amount of workforces whose skills will be taken over by robots; artificial intelligence and technology. Zervoudi (2019) also indicated that routine jobs with a high volume of tasks related to information exchange, sales, data management, manual work, product transfer and storage, constructions, and office work are more exposed to the risk of automation. It is imperative to acknowledge that The disruptive technologies of the Fourth Industrial Revolution are changing the way ordinary employees work and live, and what it means to work.

According to Onik, Kim and Yang (2019), Personal data and information has already turned out to be a new commodity and are currently identified as a `new oil’ or `new domain of warfare’. Personal information is increasingly tracked to deliver intelligent and personalised services while at the same time, disrupting privacy (Bloem et al., 2014). Issues such as invasion of data privacy, harmful transparency from data and information manipulation have been emphasized by Lasi et al (2014) that technology has broadened the scope of surveillance and impacted privacy. This data commodity eventually led to Big Data technology. Big data has evolved rapidly in recent years and widely used of this particular technology in all kinds of occupations bring out a series of repercussion on the users’ information. Thus, the risk of increased vulnerability to information deception, data breaches and data security issues due to the vast connected network led to malware threat enabling access and manipulation of the network for cybercrime and scam or fraud. In the majority of the companies and corporations, users’ information is tracked without permission and several immoral companies overly collect irrelevant personal private data (Chang, Ji & Arami, 2019). The more information is being accumulated, the personal information is at high risk to the danger.

Artificial Intelligence (AI) is the appropriate emerging technology to be concerned about. This has already resulted in virtual AI discriminating the capable candidates in the recruitment process. In the case of Amazon, they started an AI project in 2014. AI-powered algorithms assisted in reviewing job applicants’ resumes and rating applicants. This will cut short the time for recruiters so they don’t have to spend time filtering the resume manually. Fortunately, Amazon realized that their new AI recruiting system showed bias against women in 2015 by not rating them in fairly manner. According to Kantarci (2021), Amazon had used historical data from the last 10-years to train their AI model. There is an enormous amount of discrimination built into current AI systems because of the data they were trained on contained years of bias discrimination. Kantarci (2021) also added that based on historical data contained biases against women since there was male dominance across the tech industry and men were forming 60% of Amazon’s employees. Hence why Amazon’s recruiting system assumed that male candidates were preferable as it’s trained by humans and inherits human biases. It withdrew resumes that have the word “women’s,” in them. The lack of crystal clear frameworks on the artificial intelligence navigation on discrimination; indicated that the mentioned concerns are legitimately valid. For example, “anomaly detection.” It has been widely applied by law enforcement, airport security, and retail and event security firms. Both Davidson and Hongjing Zhang demonstrated in their study that these types of anomaly detection algorithms are more likely to predict that African Americans or darker-skinned males are anomalies. Based on the studies, it picked up on the algorithms that identification is usually relevant to people of colour. Due to this, AI just enhances an existing bias and prejudices in law enforcement. If the organization feed a biased data set into an algorithm, the result will be a biased algorithm. In addition, AI can be tricked and influenced by the bias in its decision-making to produce the desired results of the person managing it.

Another ethical issue that is worsening due to the Fourth Industrial Revolution is the income inequality gap. Nowadays, global income inequality is at very high levels with the richest 8% of the world’s population earning half of the world’s total income and the remaining 92% of people the other half (Zervoudi, 2019). Generally, it can be summarized that income inequality grows at an unprecedented rate. In fact, the income inequality in developing countries went up to 11% between 1990 and 2010. The fourth stage of the industrial revolution may have driven productivity and efficiency to a new level but it does not reduce the poverty in the poorest parts of the world. For example, in certain continents of the world like sub-Saharan Africa, Amazonia and South Asia where more than 800 million people still face extreme poverty.

This is the right time to reflect once more on the true meaning of the fourth industrial revolution and its ideas. The importance for greater social responsibility specifically in industry participation and government cooperation in managing these Fourth Industrial Revolution ethical issues is necessary. Industry 4.0 ultimately is an inevitable force of a total transformation to the economy. Whether one chooses to embrace it or not, it is here to stay. Responding and solving these issues in order to shape our societies direction is indeed crucial.  The formulation of solutions to create a world that is better for our future generations should be the top priority.

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