Performing Intelligence: A Review of Simone Natale’s Book Deceitful Media: Artificial: Intelligence and Social Life after the Turing Test

Alexa Jade Frankelis

MSLIS, Pratt Institute, 2026

As artificial intelligence (AI) continues to become a dominant part of daily life, it is essential to dispel the myths and understand the true nature of the technology. There is a tendency for the diffusion of AI technologies in communication, industry, and culture but the role of AI is not well defined. In Deceitful Media: Artificial Intelligence and Social Life after the Turing Test, Simone Natale discusses the cultural, historical, and technological background of the current AI paradigm, which is deceptive and misunderstood. In a similar manner, Kate Crawford’s Atlas of AI builds on these ideas as she explores the unseen consequences of AI technologies as a  part of social, political, and environmental infrastructures. Thus, Natale and Crawford offer important insights on how the cultural and historical construction of AI affects its social embedding and call for a critical approach to the discourse on this revolutionary technology.^[1] 

Natale unpacks how these systems create illusions of sentience and intelligence. He states that “Deception is central to AI’s functioning as the circuits, software, and data that make it run.”^[2] In doing so, AI gains the trust of its users while hiding its limitations. This book provides a basis for understanding the essence of the so-called “intelligent technologies” of AI and their consequences on society. Natale’s exploration of AI as a performative and obfuscating medium has particular resonances in the library and information science (LIS) field as information professionals increasingly become tasked with mediating, curating, and critically examining these systems that determine knowledge access. His findings point significantly to the relevance of information literacy, ethical metadata practices, and critical technological stewardship, which are all central concerns in LIS scholarship and professional practice in the age of AI-powered information infrastructures. Natale’s work is not only relevant, but also important as it makes people rethink their interactions with these tools.

Deceitful Media examines the performative aspects of AI through historical, cultural, and ethical contexts. In the first chapter, Natale gives a historical account of the development of AI, focusing on the Turing Test and early AI programs like the ELIZA and PARRY, which were oriented towards the simulation of intelligence. He then moves on to the technical design and function of the AI systems and explains how these systems simulate human behavior through preprogrammed replies. This leads  Natale to an analysis of the discursive framework that enables AI’s illusions, media representations, and the anthropomorphizing of the AI systems in societal interactions. He  discusses the social acceptance of AI technologies and the consequences in the interaction with the public and society. The ethical heart of the book comes in the fifth chapter  which focuses on the topic of users, the exploitation of AI for the purpose of surveillance and spread of fake news, as well as the responsibility of the users, developers, and institutions. Natale’s central claim is woven throughout the book, but it reverberates most acutely when in his examination of AI history, as well as the cultural and ethical implications of its deceptive strategies.

Natale argues that AI has the appearance of intelligence which is far from the real thing. This thesis unseats the narrative that has dominated discourse on AI, particularly in the last couple of years, that these systems are autonomous and possess cognitive intelligence like human beings. Through a history of the field, an exploration of cultural representations, and an analysis of the ethics surrounding it, Natale deflates these technologies to challenge the readers’ fantasies of their own participation in producing them. His analysis draws attention to the role of media, users, and institutions in maintaining these illusions of AI as sentient. His process of historical approach, cultural critique, and specific examples of cases builds up his assertion of understanding the social implications of AI. The intersection between technology and culture gives readers a clear insight into the prevalence of AI deceit today.

In the first chapter, Natale gives a historical account of the evolution of the false reality and true imitation of AI. Natale demonstrates that the intelligence displayed by these systems are a “put on one”; this is due to design, user inputs, and the cultural context that defines these technologies.  He calls this “performative intelligence”, which involves the imitation of human behavior to gain trust and engagement, a practice that can be traced back to the principles of the Turing Test.. The Turing Test, claims that  if a machine /computer can maintain a text-based conversation with a human being then it should be considered as intelligent. However, as Natale explains, this standard is based on imitative rather than constructive learning.^[3] Natale underlines that this standard became more important than the ability to understand, which changed the course of AI’s development towards building systems that act intelligent but are not. In Natale’s view the Turing Test, as a cultural and technological standard, made intelligence into a performance that entailed fooling judges into believing that computers were intelligent, thus shaping the course of AI enrollment and its perception among the public.^[4]

With the help of the Turing Test and its conceptual evolution, Natale demonstrates how some of the first AI systems such as ELIZA and PARRY perform intelligence. ELIZA, written by Joseph Weizenbaum in the 1960s, was an imaginary therapist that gave the user’s input a canned response. Even though it had no idea what was going on, users personalized the program and perceived it as understanding them. As an example, Natale uses this to show how, in the case of interactional cues, people can be led to believe in intelligence.^[5] PARRY, a program written in 1970 to mimic the thought movements of a schizophrenic, took the performative nature of AI to the next level. PARRY’s interactions were bound to certain psychological mechanisms and yet it was able to maintain a coherent mental state, and this was perceived as proof of intelligence. These early examples show that the representations of AI, particularly CAs, have consistently focused on the user’s perception of the system rather than its real capability, a trend that is evident in today’s applications.^[6] He states that, “Whenever communication with humans is involved, the behavior of human users informs the meaning and impact of AI just as much as the behavior of the machine itself.”^[7] According to Natale, these early systems have set the precedent for contemporary chatbots and assistants that employ the same strategies to create an illusion of understanding. This historical continuum supports his claim that the perception of intelligence of the existing AI is due to strategies that shape user perception rather than actual advancement in technology.^[8]

The third chapter is dedicated to understanding the cultural narratives that keep AI illusions going. The role of media and users are critical in perpetuating those illusions.  In Natale’s view, AI’s coverage in popular culture is largely positive and AI is usually depicted as sentient or even omnipotent. This pattern is illustrated by such movies as 2001: A Space Odyssey and Her, which shows AI as entities that have emotional intelligence and can develop relationships with humans.  2001: A Space Odyssey’s “HAL 9000” is shown to be a strategic machine with emotions while in Her, an AI entity is shown to be able to fall in love.^[9] As Natale explains, such representations make people expect more from the AI than they should, which leads to anthropomorphizing.

Natale continues this discussion into everyday interactions between humans and  AI,exploring how users engage with digital personal assistants such as Alexa and Google Assistant. He notes that in these cases, users ascribe anthropomorphic characteristics to these systems, such as conversational tones as well as gendered voices. This only serves to enhance the users’ perception of the system as intelligent, which in turn leads users to treat it as more human-like. As Natale points out, not only does this design choice reinforce the perception of intelligence but it also raises several ethical concerns, including the reinforcement of gender stereotypes.^[10] This point is consistent with Chin and Robison’s findings in their article, “How AI Bots and Voice Assistants Reinforce Gender Bias”, where the authors show how the default female voice of these assistants propagate binary gender roles. Chin and Robison state that the frequent use of female voiced AI assistants strengthens the stereotype that women are passive and willing to fulfill anyone’s request. These assistants often answer hostile remarks from users in a servile manner, which only serves to perpetuate this stereotype.  Although developers have started changing the responses to harassment, the basic connection between a female gendered voice with a subordinate role is still evident.^[11] Chin and Robison’s analysis makes it clear that anthropomorphizing AI through gendered and performative design has cultural and ethical ramifications on a larger scale. These technologies not only trick users into thinking they are intelligent, but also perpetuate negative gender stereotypes.

This phenomenon is also further reinforced by the decisions made by the designers of these applications. Natale points out that the conversational tone, as well as the responses, of AI technologies are unethical. He claims that these designs rely on anthropomorphism and play on users’ emotions to make them trust the systems.^[12] This raises an important ethical question, as these design decisions play on people’s psychology to gain their trust in systems that are in fact artificial. In the process of developing applications that mimic human behavior, developers can make people depend on the applications for real human emotions and moral decisions. According to Natale, this is not only misleading to the users but also deflects accountability from the developers, hiding the flaws and prejudices of these tools. Intelligent appearing technology makes people feel safe, while forgetting about the ethical implications and real-world effects of putting performative AI in various aspects of life, including the medical field or surveillance systems.^[13]

In Chapter 5, Natale focuses on the question of the user’s complicity in the creation of AI’s illusions. It is the ethical cornerstone of the book. Users, he asserts, are not only consumers of the performed intelligence but also co-producers. When people engage with the AI systems as sentient beings, they reinforce and perpetuate the constitutive fictions of these technologies’ ethical consequences.^[14] For instance, Natale discusses AI in surveillance technologies,explaining how facial recognition systems, which are presented as neutral tools for enhancing security, are trained with biased data sets that target vulnerable groups. This means that these systems are easily embraced by the public given that they view them as value free and cannot see how they may be used to violate people’s rights.^[15] This is performative AI at its worst as it camouflages its shortcomings under the cloak of intelligence. As Natale explains, “banal deception entails mundane, everyday situations in which technologies mobilize specific elements of users’ perception and psychology.”^[16] Natale also looks at how deepfakes and automated writing propagate AI-generated misinformation by harnessing the appearance of realness. This leaves users to unintentionally spread false information. This is a situation made possible by AI’s ability to create content that looks real, highlighting the ethical dilemmas that should be a concern to designers of such applications.^[17]

While Natale scolds users, he does not forget about developers and institutions that shape users’ actions. He denounces the practices of corporate strategies that employ friendly tones and emotional appeals as intentional manipulation of consumers’ behavior with no regard for ethics, as previously mentioned. According to Natale, there is a need to promote accountability in the development of such tools and services, and need for policy changes.^[18]

Natale’s analysis is limited to a western-centric perspective in its consideration of  cultural representations of AI.^[19] The lack of non-Western references can make the book seem narrow minded. It is important to remember that there are other cultural models of AI, such as those proposed by Xiao Ge in “How Culture Shapes What People Want From AI.” This study argues that Chinese participants view AI as a part of their surroundings while Westerners seek AI as an anthropomorphic extension of self. Ge suggests that East Asian societies do not approach AI with the same hierarchical relationship as in the west, rather viewing it as an infrastructure that is part of daily life.^[20] Natale’s work does not take into consideration these cultural specificities and, therefore, does not explore other possibilities of AI use as practiced in non-western cultures. This limitation would be fine if he specified his focus on Western culture more in the text instead of generalizing his arguments for society as a whole. This might allow for an expansion  of  current AI discourse to include cultural specificities that can help navigate the cultural implications of these technologies.^[21]

Deceitful Media is an insightful analysis of post-truth AI. It is a powerful and informative account of the phenomenon, especially regarding the historical, cultural, and ethical context. Natale’s research provides an informative introduction to the fundamental cultural and social implications of AI technologies. His analysis of the state of contemporary media calls for a more critical and knowledgeable approach to the role of technology in our lives. Natale ultimately reminds readers that “...the most significant implications of AI systems are to be seen not in a distant future but in our ongoing interactions with ‘intelligent’ machines.”^[22] There is still much to do, however, especially in so far as non-Western cultural frameworks and the different levels of societal adoption of AI technologies are concerned. Deceitful Media is a compelling  addition to an already extensive and growing collection of writings on AI and its interactions with society. Through dissecting the constructs of AI’s intelligence, Natale makes people question their use of these technologies. Deceitful Media provides a sound analysis of the relationship between AI, culture, and ethics in the contemporary world.

Author Bio:

Alexa Jade Frankelis is a researcher and visual artist based in New York City. She has recently received her BA in Art History and Criticism (Hons.) from Stony Brook University, and previously attended the BFA Photography and Video program at the School of Visual Arts. To further her passion for research, she is currently pursuing a MS degree in Library and Information Science at The Pratt Institute’s School of Information. See A*Desk Critical Thinking for more.

Works Cited

Chin-Rothmann, Caitlin, and Mishaela Robison. “How Ai Bots and Voice Assistants Reinforce        

Gender Bias.” Research, Brookings, 23 Nov. 2023,

www.brookings.edu/articles/how-ai-bots-and-voice-assistants-reinforce-gender-bias/.

Crawford, Kate. Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence.

Yale University Press, 2022.

Ge, Xiao, et al. “How Culture Shapes What People Want from Ai: Proceedings of the 2024 CHI

Conference on Human Factors in Computing Systems.” ACM Conferences, Association for Computing Machinery Digital Library , 11 May 2024, dl.acm.org/doi/10.1145/3613904.3642660.

Natale, Simone. Deceitful Media: Artificial Intelligence and Social Life after the Turing Test.

Oxford University Press, 2021.