Zhu Yanling is deputy director, assistant researcher and postdoctoral fellow at the Communication Center of the Institute of Public Policy, South China University of Technology.

Human intelligence and artificial intelligence

Collecting scholars’ views from different disciplines and regional backgrounds, this book constructs a unified conceptual, theoretical and methodological framework, that is, through critical analysis of the composition, impact and potential inequality of artificial intelligence to explore the significance of artificial intelligence to everyone.

This book starts with a critical discussion of human-computer dualism and explores its historical origins and current dilemmas. In Chapter 2, Andreas Kaplan () briefly introduces the history and definition of artificial intelligence. He believes that artificial intelligence is characterized by its ability to interpret external data and use it for learning to achieve complex goals and tasks. In Chapter 3, Wolfgang Hoffkishnell further discusses the relationship between humans and machines by examining the sometimes confused areas of digital humanism. He proposed a dialectical model to construct human-computer relationships by affirming () and combining ().

Jenna Ng (Chapter 4) focuses on the philosophical nature of creativity, elaborating on another understanding of creative AI and the significance of AI's "creativeness" to the humanities. Dan McQuillan () (Chapter 5) further discusses humanism, which explores the status of AI as a common solution in social problems by analyzing how AI promotes solidarity and unity in times of crisis.

The struggles on values, social norms and ideology should not be seen as “an insignificant absurdity, an absurdity that is opposite to the importance of science and its technological inference” (Habach, 1983, p. 37). Different views on intelligent reproduction highlight some important issues, namely how to optimize and adjust the boundaries of art and humanities to overcome the limitations of human-computer dualism and ensure that the existing human-computer interaction model meets the contemporary needs of human society. Today, we are becoming more and more adaptable to the system of human-computer interaction, but it is not difficult for us to recall an era of mass communication dominated by a top-down public media system. During that period, national broadcasters such as the BBC were at a central position in the field of public communication.

Despite rapid changes in communication modes and policy measures, competition and balance of power between institutions and individuals remain central to the relevant debate in terms of issues in the cultural field. As O'Hara and Hall (2020) say, "The Internet is not just about improving itself: it has evolved into an open system, the result of a joint action of a series of philosophical and political decisions, as well as technical decisions" (p. 28).

Artificial Intelligence Ethics and Governance

In the second part "About AI Discourse and Myth", Rehak and others discussed the normative issues about the nature of "ideal" AI systems and the necessary conditions for realizing "ideal" AI systems. They have a relatively mild critical attitude towards this type of issue. Rehak (Chapter 6) explores the metaphorical narratives that people often use when talking about “human-like intelligence” and digital technologies, and tells the relevant terms in detail.

By reflecting on the struggles of ownership and power relations, Angela Daly, S. Kate and Mann (Chapter 7) introduce and discuss their “Good Data” approach in an attempt to clarify the boundary issues between AI ethics and governance. They discuss AI governance from the political evolutionary approach and propose that when discussing the ethical principles of data use, prioritize the values ​​and interests of marginalized communities over the discourse power of digital conglomerates and governments. After discussing capitalism and democracy, James Steinhof (Chapter 8) critically analyzed the social reconstruction phenomenon of artificial intelligence and discussed its potential utility issues and neglected feasibility issues.

Benedetta Brevini ( ) (Chapter 9) analyzes European AI policies and reveals the internal logic that supports the legitimacy of capitalism in the theory of artificial intelligence. Brevini believes that judging from the policy guidelines issued by the European Commission (2020) aimed at promoting social trust in artificial intelligence, understanding the public's discourse construction of artificial intelligence will help improve the arguments and concepts dominated by technology determinism in the policy agenda. Alkim Akdag Salah (Chapter 10) focuses on the production process of artistic computing and how it affects people’s understanding of the predictability and depth of creativity.

These five chapters are rich in content, and Brevini () Discourse Analysis (Chapter 9) focuses on the ethics and regulatory framework of artificial intelligence in the European context. At present, local governments and non-governmental organizations have found many controversial issues when promoting the application of technology. Brevini pointed out that in terms of collecting data and determining the ownership and use of data, the legislative bodies of various countries need to introduce and improve relevant policies for data supervision to regulate corresponding collection and use behaviors. The universal normative principles of artificial intelligence ethics remain relevant to discussions of power and social equity, and the interaction between competitive forces negotiated around data-driven industry rules reflects the social context of the discussion. As Denadis (, 2014) argues, the mutual balance between political regulation, business needs and civil rights will continue to shape a policy framework based on the digital regulatory regime. This view is endorsed by sociologists and lawyers who advocate the regulation of digital cultural spaces, and the EU's strengthening of the legal framework for data protection and competition law is exemplified.

The power of artificial intelligence and its regulation

The third part, “The Power of AI and Social Inequality”, consists of 5 chapters, which start from different disciplines and explain the social functions of AI. Kelly O'Connell and Chad Van (Chapter 11) studied the concept of negative entropy in Wiener () and explored the significance of applying artificial intelligence in contemporary society from the perspectives of predictive function and stress.

From a sociological perspective, Jenez Prodnik (.) (Chapter 12) analyzed the algorithmic logic of digital capitalism. In a society full of competitive and instability, he critically reveals the principles and achievements of AI algorithms. Aswasa Babu and Saif (Chapter 13) also looked at controversies about biometrics and biopolitics, conducting case studies on laws prohibiting the use of facial recognition software in the California Police Department.

Rafael Gromann and William Fernandez (Araújo) discuss the impact of global artificial intelligence platforms on labor through an empirical study of Turkish robots (Turk) in Brazil (Chapter 14). Lina (Chapter 15) explores the issue of artificial intelligence governance from the perspective of labor and reevaluates the relationship between human labor and artificial intelligence. To address injustice in society, he also proposed "data justice unionism" (p. 267). In exploring the relationship between social dataization and citizen digital rights, Dansik advocates the establishment of a policy framework on the overall social and economic rights of workers in terms of algorithmic management of labor sites.

The final part of this trilogy introduces readers to the main challenges facing AI governance in terms of individual rights, data protection, ethics and equity. At the beginning of the discussion, the author proposed a dichotomy that distinguished humans from machines, and reflected on the possible connections between the two by comparing the nuances of the two. In the description of this book, the future prospects between artificial intelligence and human society may be bleak, as data-driven technologies are easily manipulated by large groups and institutions, leading to crises. The technical principles and risk governance of artificial intelligence need urgent attention.

Regarding artificial intelligence technology applied to media communication, the narrative of this book highlights the theoretical picture of artificial intelligence on the ontology of artificial intelligence and studies theoretical issues related to artificial intelligence ethics and governance. The author aims to establish a more systematic conceptual framework through valuable empirical research to explain how technological innovation and cultural space activities interfere with each other in the context of contemporary society. The examples in this book help to understand the complexity of political, economic and socio-cultural dilemmas in AI governance, but technical, legal and policy measures to deal with risks deserve more in-depth discussion when conceiving a sustainable AI model based on social interests.

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Translator of this article: Jiang Zao. Translated from Zhu, Y. (2022). (Ed.), AI for ? . ,16, 931–934.