Journal articles on the topic 'Parrots, fiction'

One of the key criteria given to the judges of the Women’s Prize for Fiction is ‘accessibility’. Accessibility, readability and more recently ‘relatability’, have gained traction in recent years over other indices of literary value, such as quasi-modernist notions of difficulty and alterity. This article questions the gendering of accessibility as well as its relationship to neoliberalism. Its specific focus is on the 2006 winner of the Women’s Prize for Fiction, Zadie Smith’s On Beauty, a book that foregrounds questions of aesthetics and aesthetic value and attempts in its form and content to negotiate between the popular and the literary. Simultaneously problematising and simplifying ideas of beauty and artistic worth, the novel’s success was arguably due, in part, to the way that it at once tapped into and resolved insecurities surrounding judgements of aesthetic value. Controversies over literary awards are routine, but this article argues that they were especially rife in the 2000s. This article also sets these controversies over literary value and the novel’s own various engagements with the aesthetic in the context of recent, postcritical backlashes against the hermeneutics of suspicion that came to influence literary and critical theory in the 1980s and 1990s.

The current research elegantly examines the majority of the time,enveloping the reader in a dreamscape of currencies, parrots, and exquisite meals. Joshi's narrating technique is captivating and the time passes quickly in the globe she has created. Nevertheless, her prose occasionally devolves into elaborate cramps and there are omissions and inconsistencies in her portrayal of the class structure in 1950s India, especially regarding ladies. Reading this straight historical fiction is a mistake; writing about class in a reliable or full of thought thinking will compose more about brutality and injustice. The current class and religious character issues in India are a section of the goal the state is in disorder today. Nevertheless, the study of Margaret Mitchell's Gone with the Wind, where a blameless Black Lives Matter strike is taking place, has the same effect.

[First paragraph]Women Pirates and the Politics of the Jolly Roger. ULRIKE KLAUSMANN, MARION MEINZERIN & GABRIEL KUHN. New York: Black Rose Books, 1997. x + 280 pp. (Paper US$ 23.99)Pirates! Brigands, Buccaneers, and Privateers in Fact, Fiction, and Legend. JAN ROGOZINSKI. New York: Da Capo Press, 1996. xvi + 398 pp. (Paper US$ 19.95)Sir Francis Drake: The Queens Pirate. HARRY KELSEY. New Haven: Yale University Press, 1998, xviii + 566 pp. (Cloth US$ 35.00)A General History of the Robberies and Murders of the Most Notorious Pirates. CAPT. CHARLES JOHNSON (edited and with introduction by DAVID CORDINGLY). New York: Lyons Press. 1998 [Orig. 1724]. xiv + 370 pp. (Cloth US$ 29.95)The subject of piracy lends itself to giddy jokes about parrots and wooden legs, but also talk of politics, law, cultural relativism, and of course Hollywood. This selection of new books on piracy in the Caribbean and beyond touches on all these possibilities and more. They include a biography of the ever-controversial Elizabethan corsair, Francis Drake; an encyclopedia of piracy in history, literature, and film; a reissued classic eighteenth-century pirate prosopography; and an anarchist-feminist political tract inspired by history and legend. If nothing else, this pot-pourri of approaches to piracy should serve as a reminder that the field of pirate studies is not only alive and well, but gaining new ground.

The 18th century explorer Alexander von Humboldt discovered the remnants of a dead language in a parrot he found in the South American rain forest. The Ature people had originated from the lands around the Orinoco river in Venezuela, but disappeared when the tribe was murdered by the rival group of Carib Indians in the last years of the 18th century. Von Humboldt discovered that the pet parrot of these dead people had survived with their language, albeit in a limited form, and he set about transcribing the language phonetically. Schützenberger tells a similar story of a parrot that retained the voice of a long dead family patriarch in France, who still had power over his family through his now disembodied voice being parroted by an old family pet. This paper will explore how depression can be perpetuated or kept alive in the words, phrases and voices, literal or metaphorical, which exist in families. Material from fictional and biographical family accounts will be presented in examining how families might learn to re-voice the language they use for each other and the world, to move away from maladaptive ways of interacting with the world.“Happy families are all alike; every unhappy family is unhappy in its own way.”Anna Karenina(Tolstoy, 1878/2003)

Abstract The strict boundaries between disciplines have been seriously challenged by various links established between them through cross-fertilization. Links between literary and translation studies are not new. However, in the (post)-modern world, when interdisciplinarity is starting to give way to transdisciplinarity, a new meeting point has been found in transfiction, enabling translation to become an interpretative paradigm for literature. Attempting to support this rather neglected approach, this paper analyzes Julian Barnes’s Flaubert’s Parrot in the light of the relationship between source and target texts and the concept of the invariant as a reflection of the postmodern quest for truth, claiming that the novel makes a fictional dethronement of the source text and calls for a shift from instrumentalism to the hermeneutic approach in translation.

The article deals with the change in the semantic spectrum of the zoonym 'parrot'. The purpose of the study is to show the dynamics of cultural meanings in modern Russian usage in speech (on the example of using animalistic images in speech), which can be identified through the methodology for analyzing the text environment of lexemes which involves the following parameters: the function of the lexeme in the text and the features of functioning of the lexeme in the text. The author interprets modern speech usage as the usage of a lexeme in fiction and journalistic literature of the 20th–21st centuries. The analysis of examples of zoonym usage in speech demonstrates how the figurative meaning of the word is becoming more positive. The study of the functioning of the zoonym 'parrot' in different types of contexts revealed the neutralization of the animalistic features of the object and the strengthening of the anthropological ones.

Abstract Analysing Julian Barnes’s postmodernist novel, Flaubert’s Parrot, this essay shows that the past is exposed as a story and a palimpsest. We demonstrate that in Julian Barnes’s novel, the past is rewritten as a story with various truths about Flaubert’s identity and biography. The past is presented through a series of symbols, being a palimpsestic construct open to our analysis and understanding. The concepts of historical truth, the past, the present, the writer’s voice are approached in a postmodernist manner and are nothing but a palimpsest.

The essay puts to the test Darwinian evolutionist theories, especially the key concepts of adaptation, natural selection and survival of the fittest, in the reading of several plots and fictions (some of them Ark-related animal fictions) concerned with evolution, trauma, adaptability, mimicry/mimesis and survival: Julian Barnes’s Flaubert Parrot and A History of the World in 10½ Chapters, Timothy Findley’s Not Wanted on the Voyage, Robert Kroetsch’s The Studhorse Man and John Fowles’s The French Lieutenant’s Woman. Weaving its critical argument with reference to several of Derrida’s reflections – on the impossibility of a pure origin, the proximity between commencement and commandment, the logic of obsequence, or relation between being and following (je suis), applied deconstructively to the traditional hierarchy between the human and the animal, mastery and monstrosity, and logos and bêtise, etc. – ‘Zo(o)graphies’ is structured in a series of interlinked tableaux, bestiaries as well as insets (Thomas Pynchon’s Gravity’s Rainbow, Jacques Derrida’s Glas). Following from the opening evocation of Peter Greenaway’s Vermeer-themed film A Zed and Two Noughts, which introduces the joint semantics of zographein: to paint from life, and zoon: animal, discreetly at work throughout, this study will eventually attempt to recast the problematic of the evolution of literature and literary forms as involution and regression.

In at least two aspects, Buddhist Avadāna literature shares a strong affinity with Chinese literature. One type of stories can be seen as parallel tales that bear striking resemblances to Chinese tales, while the other type has been assimilated by Chinese writers and transformed into Chinese tales. Regarding the first kind, there are many parallels between Buddhist and Chinese stories throughout the Six Dynasties (222–589), and it was only later that these stories were somehow compiled into collections that brought these parallels to light. As an example of the second type, in linggui zhi 靈鬼志 (The Record of Magical Ghosts) of the Jin Dynasty (265–402), the story of waiguo daoren 外國道人 (“the Foreign Master”) adapts the magical plot in which a man throws up a jug from the story of fanzhi tuhu 梵志吐壺 (“a Brahmin Spits a jug”) in the Buddhist text, yet it changes certain objects of the story to items with Chinese characteristics and develops new meaning. In Xu qixiezhi 續齊諧志 (Further Records of Qixie [Supernatural tales]), the famous e’long shusheng 鵝籠書生 (“the Goose Cage Scholar”, also known as the yangxian shushing 陽羨書生” (the Scholar from Yangxian)”), takes the same story to another level. The structure of the story is changed, and a number of literati aesthetic interests are added, improving the literary color, smoothing down the language, and making substitutions in the text’s specifics, thus, bolstering the sense of realism and history. Meanwhile, in Liu Yiqing’s 劉義慶 (403–444) Xuanjianj 宣驗記 (Records Manifest Records of Manifest Miracles), the Avadāna tale yingwu jiuhuo 鸚鵡救火 (“the Parrot Putting Out the Fire”) that he collected is not only associated with Buddhism but can also be seen as a commentary on the turbulent times and a hint of literati optimism if we view it in the context of Liu Yiqing’s Youminglu 幽明錄 (Record of the Hidden and Visible Worlds). The literary elites of the Six Dynasties drew inspiration from Buddhist Avadāna sources and imaginatively mixed them with historical circumstances to create Chinese fiction with new intentions. The rich resources of Avadāna literature from India and the fable tradition in Chinese literature create cultural conditions for these two sources to combine and mutually develop, forming a world of literature with colorful and meaningful stories.

In this paper, I would like to discuss the contribution that post-structuralist semiotics has brought to the analysis of academic discourse. The semiotic model was developed initially for the analysis of tales and myths. It has been gradually extended to various forms of fiction (novels, short stories), and then, according to "a growing degree of complexity and abstraction", to all "forms of social production of meaning" (p. 5). This is the project stated in the first pages to a book entitled “Introduction to Discourse Analysis in Social Sciences” (A.J. Greimas & E. Landowski eds, 1979). The generalized extension is based on a typology of discourses that has been illustrated by specific analyses published in the 1980s (Bastide 1981, Bastide & Fabbri 1985, Landowski 1986, Bordron 1987). One may be considered that the research project led by Greimas and Landowski is thus located at the farthest point of development and initial application of the model and it is therefore a test for the narrative hypothesis. In doing so, the semiotic approach took the risk of being confronted with other models of analysis, such as they were elaborated in theoretical frameworks resulting from rhetoric (renewed in the 1950s by Chaim Perelman and his school ), pragmatics (cf Parret 1983 & 1987), sociology of knowledge (from the founding work of Berger & Luckmann 1966), or as they relate to other theoretical currents in the language sciences (in particular, In France, the Althusserian discourse analysis). For the discourse in social sciences, these models offer two advantages over that of semiotics: on the one hand, it seems that the theoretical postulates on which they are worked out are more directly in accord with this type of discourse; on the other hand, they can count on a solid tradition of studies to ensure the sustainability of the results. Nevertheless, the model of semiotic analysis is original and it has also an advantage: it is general. I will put forward the benefits of this generality. ---DOI: http://dx.doi.org/10.22409/gragoata.2017n44a1033

In this paper, I would like to discuss the contribution that post-structuralist semiotics has brought to the analysis of academic discourse. The semiotic model was developed initially for the analysis of tales and myths. It has been gradually extended to various forms of fiction (novels, short stories), and then, according to "a growing degree of complexity and abstraction", to all "forms of social production of meaning" (p. 5). This is the project stated in the first pages to a book entitled “Introduction to Discourse Analysis in Social Sciences” (A.J. Greimas & E. Landowski eds, 1979). The generalized extension is based on a typology of discourses that has been illustrated by specific analyses published in the 1980s (Bastide 1981, Bastide & Fabbri 1985, Landowski 1986, Bordron 1987). One may be considered that the research project led by Greimas and Landowski is thus located at the farthest point of development and initial application of the model and it is therefore a test for the narrative hypothesis. In doing so, the semiotic approach took the risk of being confronted with other models of analysis, such as they were elaborated in theoretical frameworks resulting from rhetoric (renewed in the 1950s by Chaim Perelman and his school ), pragmatics (cf Parret 1983 & 1987), sociology of knowledge (from the founding work of Berger & Luckmann 1966), or as they relate to other theoretical currents in the language sciences (in particular, In France, the Althusserian discourse analysis). For the discourse in social sciences, these models offer two advantages over that of semiotics: on the one hand, it seems that the theoretical postulates on which they are worked out are more directly in accord with this type of discourse; on the other hand, they can count on a solid tradition of studies to ensure the sustainability of the results. Nevertheless, the model of semiotic analysis is original and it has also an advantage: it is general. I will put forward the benefits of this generality.---------------------------------------------------------------------------------Semiótica e Estudos do DiscursoNeste artigo, eu gostaria de discutir a contribuição que a semiótica pós-estruturalista deu à análise do discurso acadêmico. O modelo semiótico foi desenvolvido inicialmente para as análises de fábulas e mitos. Ele tem sido gradualmente estendido às várias formas de ficção (romances, contos) e, então, de acordo com “um grau de crescimento de complexidade e abstração”, para todas as “formas de produção social de sentido” (p. 5). Este é o projeto declarado nas primeiras páginas de um livro intitulado “Introdução à Análise do Discurso nas Ciências Sociais” (A. J. Greimas & E. Landowski (eds), 1979). A extensão generalizada toma como base uma tipologia de discursos que tem sido ilustrada por análises específicas publicadas nos anos 1980 (Bastide, 1981; Bastide & Fabbri, 1985; Landowski, 1986; Bordron, 1987). Pode-se considerar que o projeto de pesquisa liderado por Greimas e Landowski está então localizado no ponto mais distante do desenvolvimento e aplicação inicial do modelo e, portanto, é um teste para a hipótese narrativa. Ao fazê-lo, a abordagem semiótica correu o risco de ser confrontada com outros modelos de análises, tais como foram elaborados na perspectiva teórica resultante da retórica (renovado nos anos 1950 por Chaim Perelman e sua escola), da pragmática (cf. Parret, 1983 & 1987), da sociologia do conhecimento (pelo trabalho fundador de Berger & Luckmann, 1966), ou como elas se relacionam com outras correntes teóricas nas ciências da linguagem (em particular, na França, a análise do discurso althusseriana). Quanto ao discurso nas ciências sociais, esses modelos oferecem duas vantagens sobre a semiótica: por um lado, parece que os postulados teóricos nos quais são trabalhados estão diretamente de acordo com esse tipo de discurso; por outro lado, eles podem contar com uma sólida tradição dos estudos para garantir a sustentabilidade dos resultados. Mesmo assim, o modelo de análise semiótica é original e tem também uma vantagem: ela é geral. Apresentarei os benefícios dessa generalidade. ---DOI: http://dx.doi.org/10.22409/gragoata.2017n44a1033

En este artículo, la autora desarrolla varias ideas sobre la teoría y la práctica de los campos científicos desde un punto de vista social y pedagógico directamente relacionado con la literatura y las artes plásticas para niños. La cuestión es analizada desde el marco teórico diseñado por Jean Perrot en su último libro, Du jeu, des enfants et des livres à l’heure de la mondialisation (Editions du Cercle de la Librairie, Paris, 2011). Jean Perrot es un reconocido estudioso de la literatura y la ficción infantil y el director fundador del Instituto Internacional Charles Perrault de Francia. En su última obra, el autor reflexiona sobre las metamorfosis de los libros y la cultura para niños en la era de la "videoesfera" y la "sociedad del espectáculo" bajo el impacto de la globalización. Explora de forma relevante los numerosos fenómenos nuevos conectados a la "producción para niños" que describe como una cuestión particularmente compleja.El libro de Jean Perrot supone una mirada exhaustiva sobre la investigación realizada en el campo de la literatura infantil en los albores del tercer milenio, con análisis relevantes sobre el público objetivo, la tentación de considerar el libro como un objeto, la compleja relación entre discurso y pintura, y el tema del cuerpo fantástico en obras y novelas dirigidas a jóvenes lectores. La conclusión que Jean Parrot elabora en su libro es lúdica y optimista en la medida en que, por medio de una sutil estrategia intertextual, el autor adopta y adapta la idea del “eterno retorno” en referencia a Harry Potter, el “león” de la infancia y Friedrich Nietzsche. In the present paper, the author develops several ideas about the theory and practice of scientific fields from a social and educational viewpoint directly connected to children’s literature and visual arts. The issue is analyzed inside the theoretical frame designed by Jean Perrot in his latest book, Du jeu, des enfants et des livres à l’heure de la mondialisation (Editions du Cercle de la Librairie, Paris, 2011). Jean Perrot is a well-known scholar of literature and children’s fiction and the founding director of Charles Perrault International Institute in France. In his latest work, the author reflects on the metamorphoses of children’s books and culture in the era of the “video-sphere” and of the “show society” under the impact of globalization. He relevantly explores the numerous new phenomena that are connected to “children’s production” which he describes as a particularly complex issue. Jean Perrot’s book is an overall view on research done in the field of children’s literature at the beginning of the third millennium, with relevant analyses of the target audience, of the temptation of the book seen as an object, of the complex relationship between discourse and picture, of the theme of the fantasy body in plays and novels addressing young readers. The conclusion that Jean Perrault draws in his book is ludic and optimistic as, through a subtle intertextual strategy, the author adopts and adapts the idea of the “eternal return” when referring to Harry Potter, to the childhood “lion” and to Friedrich Nietzsche.

Abstract In an experiment, the authors tried to find out how professional readers deal with unnatural narrators (such as a narrating parrot and a speaking coin). The hypotheses and research questions were mostly derived from Jan Alber’s proposed reading strategies and operationalized to be measured with the help of a close-ended questionnaire. Thirty-two students of English from RWTH Aachen University took part in the study and were presented with four text passages that featured two natural and two unnatural first-person narrators. These excerpts represented a gliding scale of defamiliarization or estrangement in the sense of Shklovsky that ranges from (1) a realist backpacking tourist in India to (2) a narrator who suffers from hallucinations (both natural), and from there to (3) a narrating parrot and, finally, (4) a speaking coin (both unnatural). The results indicate that the participants perceived the narratives that featured unnatural narrators as being more estranging than the ones that contained natural narrators, and that unnaturalness was regarded as an indicator of fictionality. Furthermore, it was easier for the participants to emotionally engage with the natural (compared to the unnatural) narrators. The study also shows that blending was used as a strategy to make sense of the unnatural narrators, and that the participants thought that fictional worlds were relevant for their own world experiences – regardless of whether the narrators were unnatural or not. Furthermore, most of the participants were reminded of familiar genres (fantasy stories or fairy tales) when they dealt with the unnatural narrators.

Marshall, Rita, and Etienne Delessert. I Hate to Read! Mankato, MN: Creative Education, 1992. Print. As you might guess from the title, this book invites reluctant readers to discover the wondrous adventures that can be accessed through turning the pages of a book, as opposed to tuning into TV programs. The cover features the narrator—third-grader Victor Dickens—on a dragon’s back, with flames licking out of the pages of a stack of books. Readers are told that Victor is a “really good kid” “most of the time,” and many children will be able to relate to his academic difficulties: “Victor got As in math and Bs in science, but Fs when it came to the ABCs”. He calls himself a “victim of the hate to read syndrome”. One night, Victor is visited by a series of storybook creatures, including a crocodile in a white coat, a field mouse carrying gold coins, a pirate parrot, and a white rabbit in black barn boots; all of whom attempt to convince him to read. He repeats his usual mantra, “I hate to read,” until gradually he begins turning pages, and his imagination takes over. Fictional characters morph into people from his real life: Sleeping Beauty turns into Natalie Nickerson, on whom Victor appears to have a bit of a crush. The turning point comes when one of the characters whispers: “It’s fun to read even when you’re not supposed to.” This thought appeals to his sense of juvenile rebellion, and he continues in his literary reverie, even missing his favourite TV program. He imagines his teacher as a witch, throwing books into a cauldron, and his classmates, led by Natalie, shouting, “We hate to read!” Instead of joining in, however, Victor thinks of how sad he would be to lose all of his new friends, so he looks for them in his book: “And as he read each page, he just hated…to come to the end.” Writer and designer Rita Marshall and illustrator Etienne Delessert have each been awarded numerous literary prizes for their work. The large-scale drawings of the storybook creatures are whimsical and inviting. They also contain small details that might not be noticed on the first reading. For example, the toes and talons of the dragon on the cover also form crow-like birds with pointy beaks. In another image, letters of the alphabet are hidden in animal tracks. On the other hand, the book includes some literary references that would likely be lost on a typical third-grader. For example, Victor’s parents are said to have bought all 56 volumes of the Encyclopedia Britannica to help pique his interest in reading. It is unlikely that many families would have this set in their homes, nor would a child normally encounter one in an elementary school library. However, these details will perhaps prompt questions from curious readers. On the whole, “I hate to read” is highly likely to achieve its principal goal. Much like Victor, most children will probably hate to see it come to an end. Not to fear, they can continue to follow Victor’s adventures in “I Still Hate to Read,” which was published in 2007. Highly recommended: 4 out of 4 starsReviewer: Kim Frail Kim is a Public Services Librarian at the H.T. Coutts Education Library at the University of Alberta. Children’s literature is a big part of her world at work and at home. She also enjoys gardening, renovating and keeping up with her two-year old.

Introduction Author Arthur C. Clarke famously argued that in science fiction literature “any sufficiently advanced technology is indistinguishable from magic” (Clarke). On 30 November 2022, technology company OpenAI publicly released their Large Language Model (LLM)-based chatbot ChatGPT (Chat Generative Pre-Trained Transformer), and instantly it was hailed as world-changing. Initial media stories about ChatGPT highlighted the speed with which it generated new material as evidence that this tool might be both genuinely creative and actually intelligent, in both exciting and disturbing ways. Indeed, ChatGPT is part of a larger pool of Generative Artificial Intelligence (AI) tools that can very quickly generate seemingly novel outputs in a variety of media formats based on text prompts written by users. Yet, claims that AI has become sentient, or has even reached a recognisable level of general intelligence, remain in the realm of science fiction, for now at least (Leaver). That has not stopped technology companies, scientists, and others from suggesting that super-smart AI is just around the corner. Exemplifying this, the same people creating generative AI are also vocal signatories of public letters that ostensibly call for a temporary halt in AI development, but these letters are simultaneously feeding the myth that these tools are so powerful that they are the early form of imminent super-intelligent machines. For many people, the combination of AI technologies and media hype means generative AIs are basically magical insomuch as their workings seem impenetrable, and their existence could ostensibly change the world. This article explores how the hype around ChatGPT and generative AI was deployed across the first six months of 2023, and how these technologies were positioned as either utopian or dystopian, always seemingly magical, but never banal. We look at some initial responses to generative AI, ranging from schools in Australia to picket lines in Hollywood. We offer a critique of the utopian/dystopian binary positioning of generative AI, aligning with critics who rightly argue that focussing on these extremes displaces the more grounded and immediate challenges generative AI bring that need urgent answers. Finally, we loop back to the role of schools and educators in repositioning generative AI as something to be tested, examined, scrutinised, and played with both to ground understandings of generative AI, while also preparing today’s students for a future where these tools will be part of their work and cultural landscapes. Hype, Schools, and Hollywood In December 2022, one month after OpenAI launched ChatGPT, Elon Musk tweeted: “ChatGPT is scary good. We are not far from dangerously strong AI”. Musk’s post was retweeted 9400 times, liked 73 thousand times, and presumably seen by most of his 150 million Twitter followers. This type of engagement typified the early hype and language that surrounded the launch of ChatGPT, with reports that “crypto” had been replaced by generative AI as the “hot tech topic” and hopes that it would be “‘transformative’ for business” (Browne). By March 2023, global economic analysts at Goldman Sachs had released a report on the potentially transformative effects of generative AI, saying that it marked the “brink of a rapid acceleration in task automation that will drive labor cost savings and raise productivity” (Hatzius et al.). Further, they concluded that “its ability to generate content that is indistinguishable from human-created output and to break down communication barriers between humans and machines reflects a major advancement with potentially large macroeconomic effects” (Hatzius et al.). Speculation about the potentially transformative power and reach of generative AI technology was reinforced by warnings that it could also lead to “significant disruption” of the labour market, and the potential automation of up to 300 million jobs, with associated job losses for humans (Hatzius et al.). In addition, there was widespread buzz that ChatGPT’s “rationalization process may evidence human-like cognition” (Browne), claims that were supported by the emergent language of ChatGPT. The technology was explained as being “trained” on a “corpus” of datasets, using a “neural network” capable of producing “natural language“” (Dsouza), positioning the technology as human-like, and more than ‘artificial’ intelligence. Incorrect responses or errors produced by the tech were termed “hallucinations”, akin to magical thinking, which OpenAI founder Sam Altman insisted wasn’t a word that he associated with sentience (Intelligencer staff). Indeed, Altman asserts that he rejects moves to “anthropomorphize” (Intelligencer staff) the technology; however, arguably the language, hype, and Altman’s well-publicised misgivings about ChatGPT have had the combined effect of shaping our understanding of this generative AI as alive, vast, fast-moving, and potentially lethal to humanity. Unsurprisingly, the hype around the transformative effects of ChatGPT and its ability to generate ‘human-like’ answers and sophisticated essay-style responses was matched by a concomitant panic throughout educational institutions. The beginning of the 2023 Australian school year was marked by schools and state education ministers meeting to discuss the emerging problem of ChatGPT in the education system (Hiatt). Every state in Australia, bar South Australia, banned the use of the technology in public schools, with a “national expert task force” formed to “guide” schools on how to navigate ChatGPT in the classroom (Hiatt). Globally, schools banned the technology amid fears that students could use it to generate convincing essay responses whose plagiarism would be undetectable with current software (Clarence-Smith). Some schools banned the technology citing concerns that it would have a “negative impact on student learning”, while others cited its “lack of reliable safeguards preventing these tools exposing students to potentially explicit and harmful content” (Cassidy). ChatGPT investor Musk famously tweeted, “It’s a new world. Goodbye homework!”, further fuelling the growing alarm about the freely available technology that could “churn out convincing essays which can't be detected by their existing anti-plagiarism software” (Clarence-Smith). Universities were reported to be moving towards more “in-person supervision and increased paper assessments” (SBS), rather than essay-style assessments, in a bid to out-manoeuvre ChatGPT’s plagiarism potential. Seven months on, concerns about the technology seem to have been dialled back, with educators more curious about the ways the technology can be integrated into the classroom to good effect (Liu et al.); however, the full implications and impacts of the generative AI are still emerging. In May 2023, the Writer’s Guild of America (WGA), the union representing screenwriters across the US creative industries, went on strike, and one of their core issues were “regulations on the use of artificial intelligence in writing” (Porter). Early in the negotiations, Chris Keyser, co-chair of the WGA’s negotiating committee, lamented that “no one knows exactly what AI’s going to be, but the fact that the companies won’t talk about it is the best indication we’ve had that we have a reason to fear it” (Grobar). At the same time, the Screen Actors’ Guild (SAG) warned that members were being asked to agree to contracts that stipulated that an actor’s voice could be re-used in future scenarios without that actor’s additional consent, potentially reducing actors to a dataset to be animated by generative AI technologies (Scheiber and Koblin). In a statement issued by SAG, they made their position clear that the creation or (re)animation of any digital likeness of any part of an actor must be recognised as labour and properly paid, also warning that any attempt to legislate around these rights should be strongly resisted (Screen Actors Guild). Unlike the more sensationalised hype, the WGA and SAG responses to generative AI are grounded in labour relations. These unions quite rightly fear the immediate future where human labour could be augmented, reclassified, and exploited by, and in the name of, algorithmic systems. Screenwriters, for example, might be hired at much lower pay rates to edit scripts first generated by ChatGPT, even if those editors would really be doing most of the creative work to turn something clichéd and predictable into something more appealing. Rather than a dystopian world where machines do all the work, the WGA and SAG protests railed against a world where workers would be paid less because executives could pretend generative AI was doing most of the work (Bender). The Open Letter and Promotion of AI Panic In an open letter that received enormous press and media uptake, many of the leading figures in AI called for a pause in AI development since “advanced AI could represent a profound change in the history of life on Earth”; they warned early 2023 had already seen “an out-of-control race to develop and deploy ever more powerful digital minds that no one – not even their creators – can understand, predict, or reliably control” (Future of Life Institute). Further, the open letter signatories called on “all AI labs to immediately pause for at least 6 months the training of AI systems more powerful than GPT-4”, arguing that “labs and independent experts should use this pause to jointly develop and implement a set of shared safety protocols for advanced AI design and development that are rigorously audited and overseen by independent outside experts” (Future of Life Institute). Notably, many of the signatories work for the very companies involved in the “out-of-control race”. Indeed, while this letter could be read as a moment of ethical clarity for the AI industry, a more cynical reading might just be that in warning that their AIs could effectively destroy the world, these companies were positioning their products as seemingly magical—“digital minds that no one – not even their creators – can understand”—making them even more appealing to potential customers and investors. Far from pausing AI development, the open letter actually operates as a neon sign touting the amazing capacities and future brilliance of generative AI systems. Nirit Weiss-Blatt argues that general reporting on technology industries up to 2017 largely concurred with the public relations stance of those companies, positioning them as saviours and amplifiers of human connection, creativity, and participation. After 2017, though, media reporting completely shifted, focussing on the problems, risks, and worst elements of these corporate platforms. In the wake of the open letter, Weiss-Blatt extended her point on Twitter, arguing that media and messaging surrounding generative AI can be broken down into those who are profiting and fuelling the panic at one end of the spectrum, and those who think the form of the panic (which positions AI as dangerously intelligent) is deflecting from the immediate real issues caused by generative AI at the other. Weiss-Blatt characterises the Panic-as-a-Business proponents as arguing “we're telling you will all die from a Godlike AI… so you must listen to us”, which coheres with the broader positioning narrative of generative AI’s seemingly magical (and thus potentially destructive) capabilities. Yet this rhetoric also positions the companies creating generative AI as the ones who should be making the rules to control it, an argument so effective that in July 2023 the Biden Administration in the US endorsed the biggest AI companies—Amazon, Anthropic, Google, Inflection, Meta, Microsoft, and OpenAI—framing future AI development with voluntary safeguards rather than externally imposed policies (Shear, Kang, and Sanger). Fig. 1: Promotors of AI Panic, extrapolating from Nirit Weiss-Blatt. (Algorithm Watch) Stochastic Parrots and Deceitful Media Artificial Intelligences have inhabited popular imaginaries via novels, television, and films far longer than they have been considered even potentially viable technologies, so it is not surprising that popular culture has often framed the way AI is understood (Leaver). Yet as Emily Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell argue, Large Language Models and generative AI are most productively understood as “a stochastic parrot” insomuch as each is a “system for haphazardly stitching together sequences of linguistic forms it has observed in its vast training data, according to probabilistic information about how they combine, but without any reference to meaning” (Bender et al. 617). Generative AI, then, is not creating something genuinely new, but rather remixing existing data in novel ways that the systems themselves do not in any meaningful sense understand. Going further, Simone Natale characterises current AI tools as “deceitful media” insomuch as they are designed to deliberately appear generally intelligent, but this is always a deception. The deception makes these tools more engaging for humans to use but is also fundamental in selling and profiting from the use of AI tools. Rather than accepting claims made by the companies financing and creating contemporary AI, Natale argues for a more pedagogically productive path: we must resist the normalization of the deceptive mechanisms embedded in contemporary AI and the silent power that digital media companies exercise over us. We should never cease to interrogate how the technology works, even while we are trying to accommodate it in the fabric of everyday life. (Natale 132) Real Issues Although even a comprehensive list is beyond the scope of this short article, is it nevertheless vital to note that in looking beyond the promotion of AI Panic and deceptive media, ChatGPT and other generative AI tools create or exacerbate a range of very real and significant ethical problems. The most obvious problem is the lack of transparency in terms of what data different generative AI tools were trained on. Generally, these tools are thought to get better by absorbing ever greater amounts of data, with most AI companies acknowledging that scraping the Web in some form has been part of the training data harvesting for their AI tools. Not knowing what data have been used makes it almost impossible to know which perspectives, presumptions, and biases are baked into these tools. While many forms of bias have plagued technology companies for many years (Noble), for generative AI tools, in “accepting large amounts of web text as ‘representative’ of ‘all’ of humanity we risk perpetuating dominant viewpoints, increasing power imbalances, and further reifying inequality” (Bender et al. 614). Even mitigating and working to correct biases in generative AI tools will be a huge challenge if these companies never share what was in their training data. As the WGA and SAG strike discussed above emphasises, the question of human labour is a central challenge for generative AI. Beyond Hollywood, more entrenched forms of labour exploitation haunt generative AI. Very low-paid workers have done much of the labour in classifying different forms of data in order to train AI systems; data workers are routinely not acknowledged at all, even sometimes directly performing the tasks that are ascribed to AI, to the extent that “distracted by the specter of nonexistent sentient machines, an army of precarized workers stands behind the supposed accomplishments of artificial intelligence systems today” (Williams, Miceli, and Gebru). It turns out that people are still doing the work so that companies can pretend the machines can think. In one final but very important example, there is a very direct ecological cost to training, maintaining, and running generative AI tools. In the context of global warming, concerns already existed about the enormous data centres at the heart of the big technology platforms prior to ChatGPT’s release. However, the data and processing power needed to run generative AI tools are even larger, leading to very real questions about how much electricity and water (for cooling) are used by even the most rudimentary ChatGPT queries (Lizarraga and Solon). While not just an AI question, balancing the environmental costs of data centres with the actual utility of AI tools is not one that is routinely asked, or answered, in the hype around generative AI. Messing Around and Geeking Out Escaping the hype and hypocrisy deployed by AI companies is vital for repositioning generative AI not as magical, not as a saviour, and not as a destroyer, but rather as a new technology that needs to be critically and ethically understood. In seminal work exploring how young people engage with digital tools and technologies, Mimi Ito and colleagues developed three genres of technology participation: hanging out, where engagement with any technologies is largely driven by friendships and social engagement; messing around, which includes a great deal of experimentation and play with technological tools; and geeking out, where some young people will find a particular focus on one platform, tool or technology that inspires them to focus enough to develop expertise in using and understanding that tool (Ito et al.). If young people, in particular, are going to be living in a world where generative AI tools are part of their social worlds and workplaces, then messing around with ChatGPT is, indeed, going to be important in testing out how these tools answer questions and synthesise information, what biases are evident in responses, and at what points answers are incorrect. For some young people, they may well move from messing around to completely geeking out with generative AI, a process that will be even more fruitful if these tools are not seen as impenetrable magic, but rather as commercial tools built by for-profit companies. While the idea of digital natives is an unhelpful myth (Bennett, Maton, and Kervin), if young people are going to be the first generation to have generative AI as part of their information, creative, and search landscapes, then safely messing around and geeking out with these tools will be more vital than ever. We mentioned above that most Australian state education departments initially banned ChatGPT, but a more optimistic sign arrived as we were finishing this article insomuch as the different Australian states agreed in mid-2023 to work together to create “a framework to guide the safe and effective use of artificial intelligence in the nation’s schools” (Clare). Although there is work to be done, moving away from a ban to a setting that should allow students to be part of testing, framing, and critiquing ChatGPT and generative AI is a clear step in repositioning these technologies as tools, not magical systems that could never be understood. Conclusion Generative AI is not magic; it is not a saviour or destroyer; it is neither utopian nor dystopian; nor, unless we radically narrow the definition, is it intelligent. The companies and corporations driving AI development have a vested interest in promoting fantastical ideas about generative AI, as it drives their customers, investment, and future viability. When the hype is dominant, responses can be overdetermined, such as banning generative AI in schools. But in taking a less magical and more material approach to ChatGPT and generative AI, we can try and ensure pedagogical opportunities for today’s young people to test out, scrutinise, and critically understand the AI tools they are most likely going to be asked to use today and in the future. The first wave of generative AI hype following the public release of ChatGPT offers an opportunity to reflect on exactly what the best uses of these technologies are, what ethics should drive those uses, and how transparent the workings of generative AI should be before their presence in the digital landscape is so entrenched and mundane that it becomes difficult to see at all. Acknowledgment This research was supported by the Australian Research Council Centre of Excellence for the Digital Child through project number CE200100022. References Algorithm Watch [@AlgorithmWatch]. “Mirror, Mirror on the Wall, Who Is the Biggest Panic-Creator of Them All? 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