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2021 | OriginalPaper | Chapter

15. Humanity in the Era of Autonomous Human–machine Teams

Author : Shu-Heng Chen

Published in: Systems Engineering and Artificial Intelligence

Publisher: Springer International Publishing

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Abstract

In this chapter, we address the meaning of the development of autonomous human–machine teams undergirded by the trio, namely, data, the Internet, and algorithms. We first review and examine this issue against a general background related to the philosophy and history of science and technology, symbiosis and cyborgs, and an evolutionary viewpoint from the Anthropocene and Novacene. We then argue that the meaning for humanity in this increasingly intensive autonomous human–machine interaction environment is two-fold, namely, individuality and the democratization of individuality (capability development). Nevertheless, to not leave the future of humanity to be dominated and solely determined by machines (the trio), humanistic scholars have to get involved themselves in the autonomous human–machine teams. In fact, some of their earlier actions have already taken place and have contributed to the changing face of the humanities, which will also be highlighted in this chapter.

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previous chapter Contextual Evaluation of Human–Machine Team Effectiveness

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Cyborgs is short for cybernetic organisms (Clynes and Kline, 1960). For treating the Internet of Everything as an expanded version of cyborgs, the interested reader is referred to Chen (2019).

Chen (2020) proposes a twin-space theory to characterize the current digital society. It is argued that the recent revolution in information, communication, and digital technology (ICDT) has gradually mapped our physical space into its digital counterpart. In other words, the planet will have its “mirror” in the digital space. Despite the twin relation, the physical space only exists in the now time (the present time) as it is a slice of the history cut at a specific position and disappears forever when it becomes the past; the data in the cyber space, however, are not subject to such a time restriction, and they can remain forever once they are registered.

Ostensibly, other expressions or characterizations also exist, such as the society of Web 2.0 or higher, or the era of user-initiated-and-supplied contents, etc. (O'Reilly, 2017). However, it is the Internet of Everything which technologically makes its kaleidoscopically rich contents suppliable.

While in this chapter, we will mainly use the term algorithms, different nomenclatures are also commonly seen in other places, such as machines, software agents, autonomous agents, etc. These terms may be used interchangeably in this chapter, so long as the ontology of concern to us is the computer programs (software), and not the physical entity (hardware). Even though the object with which humans interact can be wearable devices, chatbots, drones, driverless cars, or sensors, what interests us are the interactions or connections or communications between men and machines, and these interactions are mainly driven by software, which is related to interaction design, user experience design (UXD), and user interaction design (UID).

In his Joyless Economy, Tibor Scitovsky introduced the essence of culture in consumption, which distinguishes the enjoyable life from the good life. By comparing the consumption culture between the US and European countries, Scitovsky argued that consumers in an economy underpinned by an impoverished culture may still be able to afford a good or even a luxurious life, but not an enjoyable life.

Compared to the abundant literature on the philosophy of science, that existing on the philosophy of technology is relatively scant. Among the few studies that exist, Crocker (2012) is the one that is closely pertinent to this chapter; in particular, it also introduces a symbiotic model to frame the co-evolution of humanity and technology (see Sects. 2.2 and 2.3 below).

STS is a field that normally refers to a movement that places science and technology education in a social, political, economic, and humanistic context. It is not just to equip students with scientific facts, but, more importantly, with their meaning or significance for society as a whole. The movement already existed in the 1960s, but has seen much expansion in recent decades (Pittinsky, 2019).

In fact, Nobert Wiener (1894–1964), the founder of cybernetics, has already drawn our attention to this direction, as shown in Wiener (1948) and Wiener (1950); he can be regarded as a pioneer of STS. When documenting Wiener, Gleick (2011) stated, “Much of the success of his book, abstruse and ungainly as it was, lay in Wiener's always returning his focus to the human, not the machine. He was not as interested in shedding light on the rise of computing–to which, in any case, his connections were peripheral–as in how computing might shed light on humanity” (Ibid, p. 240; italics added).

The term Homo Machines has not been formally used in the public academic dialogues; the term, which we use here, is mainly motivated by James Lovelock (Lovelock, 2019) in his visionary discussion of the machines in Novacene. An alternative and more familiar term is Homo Techno.

Given its significance, a new version has recently been published by the MIT press (Shelley, 2017). By adding many annotations, remarks, and essays from leading experts, this book is mainly prepared for those young talents who are preparing themselves to work in science and engineering or to be an inventor.

Although humans are frail and very constrained, they are capable of inventing tools and machines to set them free. Machines under incessant technological advances enable humans, little by little, to have an overwhelming grasp of the planet. Anthropocene, a new geological term, has been proposed for this age characterized by increasing mechanization. The definition given by the Cambridge Dictionary is “the time from the eighteenth century until now, in which it is possible to see the effect that people have had on the environment and climate (= weather conditions).”

This definition distinguishes the notion of individuality from the notion of individualism. See also Siedentop (2014).

See also Chen (2020).

For example, if digital traces can be properly quantified with the natural language processing techniques, then some clustering tools, such as K nearest neighbors (Chen et al., 2007), may be applicable to identify those neighboring traces of life.

As we have indicated in Sect. 3.3.1, StarLogo and NetLogo are both from the Logo pedigree, initially founded by Seymour Papert. StarLogo was initially developed by Mitchel Resnick at the MIT Media Lab. Uri Wilensky took the baton from him to further extend StarLogo into NetLogo.

This can be further illustrated by two local examples. One example is the https://agilepoint.com, which, albeit business-oriented, takes a university–industry collaboration model to help educational institutes to gain access to it. The other example is that some universities have decided to invest in their own low-code development platform; for example, Tunghai university, one of the largest Catholic universities in Taiwan, provides students with CT2Flow (Computational Thinking To Flowchart) and CT2Code (Computational Thinking To Code), requiring students to mainly focus on the design of the flowchart and leaving machines to translate it into code. See http://ct.thu.edu.tw.

The term idea used here is inclusive; thus, each term which we put inside the brackets can be used interchangeably with it. In fact, different scholars based on their unique interests may prefer different terms. For example, Kenneth Boulding (1910–1993) chose the word image and Robert Shiller chose the word narrative, while they were both discussing the possible causes of business cycles (Boulding, 1956; Shiller, 2019). For our purpose, it is, therefore, preferable to have all of these related terms in the basket.

The agent-based modeling of social epidemics is an example.

The recent dystopian movie, “Ready Player One,” directed by Steven Spielberg (Spielberg et al., 2018), enables us to see how various types of historical knowledge can be vividly appreciated and used by readers while they rely on them to find a way out in a gaming situation.

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Title: Humanity in the Era of Autonomous Human–machine Teams
Author: Shu-Heng Chen
Publisher: Springer International Publishing
Book: Systems Engineering and Artificial Intelligence
Print ISBN: 978-3-030-77282-6

Electronic ISBN: 978-3-030-77283-3

Copyright Year: 2021
DOI: https://doi.org/10.1007/978-3-030-77283-3_15

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