A recent example is the rise of generative artificial intelligence (AI) art from text prompts in the art and creative industry in 2021. Generative AI is within the area of cognitive automation. According to Engel et al. (2022), cognitive automation can be referred to as “automating knowledge and service work to realize value offered by AI, which is based on implementing artificial cognition that mimics and approximates human cognition in machines” (p. 339). There are a number of AI art generators on the Internet, such as OpenAI’s DALL-E 2 and Image Creator by Microsoft Designer, that every Internet user can easily use to generate images by inputting a text prompt, and it will deliver the desired image. Some artists called AI-generated art fake art due to how easily AI art generators can create the desired image within seconds using just text. Unlike how AI art generators can create images in seconds, human artists need to go through a much longer process that includes researching, finding references, creating sketches and roughs, and going to production. The difference in production time used to create desired images between AI art generators and human artists within the creative industry leads to human artists worrying that AI art generators will displace their jobs. If it is from the perspective of computer hackers from the 1900s, the AI art generators would fit the hacker ethic of "you can create art and beauty on a computer" (Turner, 2006). AI art generators can also be seen as a way to provide "freedom" to art creation, as anyone with or without knowledge or skills to create art can use the generator to create an image they want. 

Another example of automation and human labor is industry machines and factory workers. Charles Babbage's invention of the Difference Engine replaced individual human intelligence, which is human computers, with machine intelligence. However, according to Schaffer (1994), even if factories adopted the automatic system, it is difficult to see the factories themselves as intelligent (p. 222). Therefore, workers are needed to manage the automatic factory, which was formed by "mechanical and intellectual organs," and workers would work using machines and look after the machines (Marx, 1867, p. 544). 

The Gutenberg Myth can be used to explain the phenomena of individuals worrying that a single development of automation will displace human labor. According to Cook (1995), the Gutenberg myth refers to "a single technology being the sole cause of rapid and far-reaching social change" (p. 78). Where people see the Gutenberg Press as the cause of the revolution without understanding other factors, such as the development of paper, the invention of the Linotype, and people's literacy, played a role in the printing revolution; with all these factors, it took over hundreds of years after the invention of the Gutenberg Press to have a printing revolution. The idea of Gutenberg's myth can reflect the idea that people think one technological invention would completely displace humans in the workplace. For example, thinking about the development of Generative AI as the reason content creators will be displaced without thinking about other developments, such as the computer, the hardware in the computer, and the Internet. Automation development enhances productivity and improves accuracy and quality by eliminating some manual labor; however, a single automation will not completely displace human workers. 

Each subsection of the exhibit explores a different area of automation’s development and its relationship with the human role. Throughout the development of different automation from the past, humans have remained a critical part of the automation workflow. The subsections were organized from the least feasible automation area to the most feasible automation area that an individual can access and can be seen or found on a daily basis. Then, within each subsection, they were organized in chronological order based on the development of different automation in different areas.

Acemoglu, D., & Restrepo, P. (2020). Robots and Jobs: Evidence from US Labor Markets. The Journal of Political Economy, 128(6), 2188–2244. https://doi.org/10.1086/705716 

Cook, S. D .N. (1995). The Structure of Technological Revolutions and the Gutenberg Myth. In  Pitt, J.C. (eds), New Directions in the Philosophy of Technology. Philosophy and Technology, vol 11 (pp. 67 - 82). Springer, Dordrecht. https://doi.org/10.1007/978-94-015-8418-0_4 

Engel, C., Ebel, P., & Leimeister, J. M. (2022). Cognitive automation. Electronic Markets, 32(1), 339–350. https://doi.org/10.1007/s12525-021-00519-7

Marx, K. (1867). Capital, Volume I. Verlag von Otto Meisner.

Schaffer, S. (1994). Babbage's Intelligence: Calculating Engines and the Factory System. Critical Inquiry, 21(1), 203–227. https://doi.org/10.1086/448746

Turner, F. (2022). How Digital Technology Found Utopian Ideology: Lessons from the First Hackers’ Conference. In Critical Cyberculture Studies (pp. 255–269). New York University Press. https://doi.org/10.18574/nyu/9780814708903.003.0026