As testing of ChatGPT has shown, this form of artificial intelligence has the potential to develop, which requires improving its software and other hardware that allows it to learn, i.e., to acquire and use new knowledge, to contact its developers with suggestions for improvement, or to reprogram itself without their participation. Как показало тестирование ChatGPT, эта форма искусственного интеллекта имеет потенциал развития, для чего необходимо усовершенствовать её программное и прочее техническое обеспечение, позволяющее ей учиться, т.е. приобретать и использовать (...) новые знания, обращаться к её разработчикам с предложениями по усовершенствованию, или производить самопрограммирование без их участия. (shrink)

In their Target Article, Rahimzadeh et al. (2023) discuss the virtues and vices of employing ChatGPT in ethics education for healthcare professionals. To this end, they confront the chatbot with a moral dilemma and analyse its response. In interpreting the case, ChatGPT relies on Beauchamp and Childress’ four prima-facie principles: beneficence, non-maleficence, respect for patient autonomy, and justice. While the chatbot’s output appears admirable at first sight, it is worth taking a closer look: ChatGPT not only misses (...) the point when applying the principle of non-maleficence; its response also fails, in several places, to honour patient autonomy – a flaw that should be taken seriously if large language models are to be employed in ethics education. I therefore subject ChatGPT’s reply to detailed scrutiny and point out where it went astray. (shrink)

ChatGPT is an artificial intelligence (AI) chatbot that processes and generates natural language text, offering human-like responses to a wide range of questions and prompts. Five days after its re...

Purpose This study aims to address the existing knowledge gap by investigating teachers’ adoption of ChatGPT for educational purposes. The study specifically focuses on identifying the factors that motivate and inhibit teachers in adoption of ChatGPT in higher education institutions (HEIs). Design/methodology/approach This research has used interpretative phenomenological analysis – a qualitative approach. Through in-depth interviews among the teachers, data was collected to identify the motivating and inhibiting factors that impacted teachers’ willingness to adopt ChatGPT. The data (...) was collected from 48 teachers working across HEIs of Uttarakhand region in India. Findings The analysis revealed seven themes under motivating factors that encourage teachers to adopt ChatGPT for their educational purposes. These include time factor, tool for competitive edge, learning enhancement tool for students, research facilitator, benefits in educational settings, troubleshooter and easy to use. On the other hand, inhibiting factors comprise five themes, which include technical difficulties, limited features for educational and research purposes, tool for handicapping innovation and creativity, lack of personal touch and ethical considerations. Practical implications The findings will be valuable for HEIs in establishing policies that promote the appropriate and effective use of ChatGPT. Moreover, the study provides recommendations to ChatGPT solution providers for improving ChatGPT services for effective adoption of ChatGPT among teachers and implementation at HEIs. Further, it contributes to the body of literature by filling a knowledge gap about teacher adoption of ChatGPT in the HEIs. Through qualitative research, the study has pinpointed specific motivating and inhibiting factors that affect teacher adoption of ChatGPT. Originality/value Unlike previous studies that primarily explored the potential advantages and drawbacks of ChatGPT in education, this research study delves deeper into the topic. It makes a substantial contribution to our understanding of ChatGPT adoption among teachers by identifying distinct factors that either motivate or inhibit teachers from adopting ChatGPT for job related purposes. The study provides novel insights that were previously mislaid, thereby introducing a fresh perspective to the existing literature. (shrink)

According to virtue epistemology, the main aim of education is the development of the cognitive character of students (Pritchard, 2014, 2016). Given the proliferation of technological tools such as ChatGPT and other LLMs for solving cognitive tasks, how should educational practices incorporate the use of such tools without undermining the cognitive character of students? Pritchard (2014, 2016) argues that it is possible to properly solve this ‘technology-education tension’ (TET) by combining the virtue epistemology framework with the theory of extended (...) cognition (EXT) (Clark and Chalmers, 1998). He argues that EXT enables us to consider tools as constitutive parts of the students’ cognitive system, thus preserving their cognitive character from technologically induced cognitive diminishment. The first aim of this paper is to show that this solution is not sufficient to solve the TET. Second, I aim to offer a complementary and more encompassing framework of tool-use to address the TET. Then, I apply it to the educational uses of ChatGPT as the most notable example of LLM, although my arguments can be extended to other generative AI systems. To do so, in Sect. 1.1, I present Pritchard’s framework of cognitive character and virtue epistemology applied in education, to which I am committed in this treatment. In Sects. 2 and 3, I respectively illustrate Pritchard’s (2014) solution to the TET, and I highlight the general limitations of his proposal. Thus, in Sect. 4.1 I characterize ChatGPT as a computational cognitive artifact using Fasoli’s (2017, 2018) taxonomy of cognitive artifacts. In Sect. 4.2, I introduce my proposal, which combines Pritchard’s account of virtue epistemology with Fasoli’s (2017, 2018) taxonomy of cognitive artifacts to address the TET. Finally, in Sect. 5.1, I present some epistemically virtuous uses of ChatGPT in educational contexts. To conclude, I argue in favor of a multidisciplinary approach for analyzing educational activities involving AI technologies such as ChatGPT. (shrink)

This article is a commentary on ChatGPT and LLMs (Large Language Models) in general. It argues that this technology has matured to the point where calling systems such as ChatGPT “stochastic parrots” is no longer warranted. But it also argues that these systems continue to have serious limitations when it comes to reasoning. These limitations are much more severe than commonly thought. A large array of examples are given to support these claims.

In his article, “What should ChatGPT mean for bioethics?” I. Glenn Cohen explores the bioethical implications of Open AI’s chatbot ChatGPT and the use of similar Large Language Models (LLMs) (Cohen...

Educators are increasingly concerned with the use of artificial intelligence (AI) in student writing. Much of the concern focuses on the issue of students using ChatGPT to complete their work. I introduce the CUPID model for instructors to use when thinking about how to pedagogically handle ChatGPT. The CUPID model lays out five general approaches: Catch, Utilize, Prevent, Ignore, and Disincentivize. I suggest that instructors should especially consider using certain assignments that fall under the approach “Disincentivize”. Philosophy instructors (...) in particular should assign more low-stakes writing, such as journals and reflection pieces. The adoption of low-stakes writing assignments aims to discourage students from relying on AI while promoting clarity of thought and deeper engagement with philosophical ideas. (shrink)

Large language models such as ChatGPT enable users to automatically produce text but also raise ethical concerns, for example about authorship and deception. This paper analyses and discusses some key philosophical assumptions in these debates, in particular assumptions about authorship and language and—our focus—the use of the appearance/reality distinction. We show that there are alternative views of what goes on with ChatGPT that do not rely on this distinction. For this purpose, we deploy the two phased approach of (...) deconstruction and relate our finds to questions regarding authorship and language in the humanities. We also identify and respond to two common counter-objections in order to show the ethical appeal and practical use of our proposal. (shrink)

The rapid development of large language models (LLM’s) and of their associated interfaces such as ChatGPT has brought forth a wave of epistemic and moral concerns in a variety of domains of inquiry...

Recent innovations in the field of Artificial Intelligence raise epistemological issues regarding the nature of knowledge and the reproducibility of human intelligence, with some uncertain implications about the ambiguity of their application and their future developments. This reflection aims at bringing to light some problems related with the incipient use of these tools in the area of scientific knowledge and thinking.

Over the last decade, AI models of language and word meaning have been dominated by what we might call a statistics-of-occurrence, strategy: these models are deep neural net structures that have been trained on a large amount of unlabeled text with the aim of producing a model that exploits statistical information about word and phrase co-occurrence in order to generate behavior that is similar to what a human might produce, or representations that can be probed to exhibit behavior similar to (...) what a human might produce (meaningsemblant behavior). Examples of what we can call Statistics-of-Occurrence Models (SOMs) include: Word2Vec (CBOW and Skip-Gram), BERT, GPT-3, and, most recently, ChatGPT. Increasingly, there have been suggestions that such systems have semantic understanding, or at least a proto-version of it. This paper argues against such claims. I argue that a necessary condition for a system to possess semantic understanding is that it function in ways that are causally explainable by appeal to its semantic properties. I then argue that SOMs do not plausibly satisfy this Functioning Criterion. Rather, the best explanation of their meaning-semblant behavior is what I call the Statistical Hypothesis: SOMs do not themselves function to represent or produce meaningful text; they just reflect the semantic information that exists in the aggregate given strong correlations between word placement and meaningful use. I consider and rebut three main responses to the claim that SOMs fail to meet the Functioning Criterion. The result, I hope, is increased clarity about why and how one should make claims about AI systems having semantic understanding. (shrink)

In our book, Why Machines Will Never Rule the World, Jobst Landgrebe and I argue that we can engineer machines that can emulate the behaviours only of simple systems, which means: only of those systems whose behaviour we can predict mathematically. The human brain is an example of a complex system, and thus its behaviour cannot be emulated by a machine. We use this argument to debunk the claims of those who believe that large language models are poised to achieve (...) a level of intelligence that will equal or even surpass that of the human brain. The essay was published under the title "Why Machines Will Never Rule the World". (shrink)

Despite the ever-changing field of artificial intelligence (AI) and its preponderance of pre-print articles, Cohen offers a timely, nuanced, and self-aware overview of ChatGPT and the world of Larg...

Motivated by the question of responsible AI and value alignment, I seek to offer a uniquely Foucauldian reconstruction of the problem as the emergence of an ethical subject in a disciplinary setting. This reconstruction contrasts with the strictly human-oriented programme typical to current scholarship that often views technology in instrumental terms. With this in mind, I problematise the concept of a technological subjectivity through an exploration of various aspects of ChatGPT in light of Foucault’s work, arguing that current systems (...) lack the reflexivity and self-formative characteristics inherent in the notion of the subject. By drawing upon a recent dialogue between Foucault and phenomenology, I suggest four techno-philosophical desiderata that would address the gaps in this search for a technological subjectivity: embodied self-care, embodied intentionality, imagination and reflexivity. Thus I propose that advanced AI be reconceptualised as a subject capable of “technical” self-crafting and reflexive self-conduct, opening new pathways to grasp the intertwinement of the human and the artificial. This reconceptualization holds the potential to render future AI technology more transparent and responsible in the circulation of knowledge, care and power. (shrink)

In the last several months, several major disciplines have started their initial reckoning with what ChatGPT and other Large Language Models (LLMs) mean for them – law, medicine, business among other professions. With a heavy dose of humility, given how fast the technology is moving and how uncertain its social implications are, this article attempts to give some early tentative thoughts on what ChatGPT might mean for bioethics. I will first argue that many bioethics issues raised by (...) class='Hi'>ChatGPT are similar to those raised by current medical AI – built into devices, decision support tools, data analytics, etc. These include issues of data ownership, consent for data use, data representativeness and bias, and privacy. I describe how these familiar issues appear somewhat differently in the ChatGPT context, but much of the existing bioethical thinking on these issues provides a strong starting point. There are, however, a few “new-ish” issues I highlight – by new-ish I mean issues that while perhaps not truly new seem much more important for it than other forms of medical AI. These include issues about informed consent and the right to know we are dealing with an AI, the problem of medical deepfakes, the risk of oligopoly and inequitable access related to foundational models, environmental effects, and on the positive side opportunities for the democratization of knowledge and empowering patients. I also discuss how races towards dominance (between large companies and between the U.S. and geopolitical rivals like China) risk sidelining ethics. (shrink)

Is ChatGPT an author? Given its capacity to generate something that reads like human-written text in response to prompts, it might seem natural to ascribe authorship to ChatGPT. However, we argue that ChatGPT is not an author. ChatGPT fails to meet the criteria of authorship because it lacks the ability to perform illocutionary speech acts such as promising or asserting, lacks the fitting mental states like knowledge, belief, or intention, and cannot take responsibility for the texts (...) it produces. Three perspectives are compared: liberalism (which ascribes authorship to ChatGPT), conservatism (which denies ChatGPT's authorship for normative and metaphysical reasons), and moderatism (which treats ChatGPT as if it possesses authorship without committing to the existence of mental states like knowledge, belief, or intention). We conclude that conservatism provides a more nuanced understanding of authorship in AI than liberalism and moderatism, without denying the significant potential, influence, or utility of AI technologies such as ChatGPT. (shrink)

Generative Artificial Intelligence (GenAI), such as ChatGPT, shows great promise and potential and is gradually being used in mental health care, but it also raises ethical concerns. These relate t...

In lieu of an abstract, here is a brief excerpt of the content:ChatGPT:a psychomachiaChristopher Norris (bio)The human mind is not, like ChatGPT and its ilk, a lumbering statistical engine for pattern matching, gorging on hundreds of terabytes of data and extrapolating the most likely conversational response or most probable answer to a scientific question. On the contrary, the human mind is a surprisingly efficient and even elegant system that operates with small amounts of information; it seeks not to (...) infer brute correlations among data points but to create explanations.—Satya P. MohantyIt remains to be seen whether AI poems will eventually go beyond intended or unintended parody and trigger emotional responses in human readers that run deeper than wry amusement.... Current AI poets are in essence mining the metaphors that humans have already formed and planted in texts–in the view of Robert Frost, 'The richest accumulation of the ages is the noble metaphors we have rolled up." Could AI create genuinely novel metaphors, rather than only variations of those we humans have come up with already?—Keith HolyoakeNoteThis poem started out as a debate in clearly-marked dialogue form (alternating roman and italic print) between an advocate of ChatGPT who thinks that 'strong' AI is, or will soon be, capable of writing 'authentic' poetry, and a poet who resists that claim on various grounds, personal and philosophical. The opening, strict-form sonnet proposes that the issue be tested by running it (the poem itself) past the software and seeing what results as the sonnet-sequence unfolds from that speculative source-point. As it goes along, the sonnet-forms multiply, the contending viewpoints seem to merge or even change sides, the roman-italic alternation breaks down, and the project (theirs or mine?) loses its intended clarity of theme and treatment. I include the poem here as a kind of performative commentary on the way that thematic concerns or intentions may get lost once the AI software really starts doing its wondrous, intriguing, or humanly ominous thing.One way to test this thing, ChatGPT:Let's run a really strict-form poem on it,Like a Petrarchan or Shakespearean sonnet,Then input 'do thou likewise,' just to seeWhat comes out. Does the poem rhyme and scan [End Page 77] Correctly yet, as claimed, hit off the styleConvincingly, and thereby close the fileOn what's unique about the species 'man'?If so, you'll find it difficult to tellWhat's what with this example of the kind,Along with other cases you may findWorth putting to the online test as well.And don't get spooked if, like myself, you're proneTo think you're someone (something?) else's clone.You crease me up, you poets, with your fearsThat some new bit of software (albeit oneOf quite superior powers) might have outdoneYou in those self-apportioned special spheresOf excellence where you and some few peers,Each special, each unique, affect to shunAll thought that your fine poems may just runOn lines devised by AI gadgeteers.A nice idea, last refuge of the weakIn mind but good in heart, the valiant fewTo whose deluded faith it falls to holdOut still for what you fantasists may seekYet scarcely hope to find: new ways to doThe genius thing, transmute base stuff to gold!Read slowly, sensitively; don't permitYourself, dear reader, nobbled as no doubtYou've been by those who have the techno-clout,To take that stuff on board and let a bitOf pseudo-Keats, spoof Yeats, identikit'Stuffed-owl'-grade Wordsworth, or what else they toutAs the real deal demand you read withoutDiscerning what no moving finger's writ.Just hearken, let your quickened sense respondTo all that yet eludes the furthest reachOf AI artefacts. They had you connedAt first, though soon you missed the living speechUn-missed by those who cannot hear beyondWhat any tin-eared programmer could teach.Let's bring the reader in on this, I say.We've need of them, we disputants with much [End Page 78] At stake in different ways, they there to payOur... (shrink)

ChatGPT has taken the academic community by storm (Cotton, Cotton, and Shipway 2023; Cox and Tzoc 2023; Sullivan, Kelly, and McLaughlan 2023). Since its release in November 2022, chatGPT has predic...

In the era of generative AI and specifically large language models (LLMs), exemplified by ChatGPT, the intersection of artificial intelligence and human reasoning has become a focal point of global attention. Unlike conventional search engines, LLMs go beyond mere information retrieval, entering into the realm of discourse culture. Their outputs mimic well-considered, independent opinions or statements of facts, presenting a pretense of wisdom. This paper explores the potential transformative impact of LLMs on democratic societies. It delves into the concerns (...) regarding the difficulty in distinguishing ChatGPT-generated texts from human output. The discussion emphasizes the essence of authorship, rooted in the unique human capacity for reason—a quality indispensable for democratic discourse and successful collaboration within free societies. Highlighting the potential threats to democracy, this paper presents three arguments: the Substitution argument, the Authenticity argument, and the Facts argument. These arguments highlight the potential risks that are associated with an overreliance on LLMs. The central thesis posits that widespread deployment of LLMs may adversely affect the fabric of a democracy if not comprehended and addressed proactively and properly. In proposing a solution, we advocate for an emphasis on education as a means to mitigate risks. We suggest cultivating thinking skills in children, fostering coherent thought formulation, and distinguishing between machine-generated output and genuine, i.e., human, reasoning. The focus should be on the responsible development and usage of LLMs, with the goal of augmenting human capacities in thinking, deliberating and decision-making rather than substituting them. (shrink)

Text-generative AI-systems have become important semantic agents with ChatGPT. We conducted a series of experiments to learn what teachers’ conceptions of text-generative AI are in relation to philosophical texts. In our main experiment, using mixed methods, we had twenty-four high school students write philosophical essays, which we then randomized to essays with the same command from ChatGPT. We had ten prospective teachers assess these essays. They were able to tell whether it was an AI or student essay with (...) 78.7 percent accuracy, which is better than the Open AI Classifier. Interestingly, however, they used criteria like argumentative and logical flawlessness and neutrality. We concluded from this that they are using an inverted Turing test and are no longer looking for rationality in machines but for irrationality in humans. (shrink)

This paper addresses the challenge of ethically integrating ChatGPT, a sophisticated AI language model, into K-14 economics education. Amidst the growing presence of AI in classrooms, it proposes the “Evaluate, Reflect, Assurance” model, a novel decision-making framework grounded in normative and virtue ethics, to guide educators. This approach is detailed through a theoretical decision tree, offering educators a heuristic tool to weigh the educational advantages and ethical dimensions of using ChatGPT. An educator can use the decision tree to (...) reach a conclusion on using ChatGPT within the classroom environment by using ethical considerations to promote personalized learning and upholding academic integrity. The paper stresses the importance of ongoing professional development for educators in ethical AI usage and calls for institutional support in this pursuit. It also identifies future research directions, including long-term impact studies of ChatGPT and comparative analyses of various AI tools in economics education, underscoring the paper’s relevance to current educational technology discourse. (shrink)

This essay comprises a first phenomenological semiotics of ChatGPT. I analyse how we experience the language signs generated by that AI. This task is accomplished in two steps. First, I introduce a conceptual scaffolding for the project, by introducing core tenets of Husserl's semiotics. Second, I mould Husserl's theory to develop my phenomenology of the passive and active consciousness of the language signs composed by ChatGPT. On the one hand, by discussing temporality, I demonstrate that ChatGPT can (...) passively demand me to understand its signs. On the other hand, I show that a conflict arises between active and passive consciousness when reading ChatGPT. While I actively know that there is no communicating subject, I still passively experience these signs as made by another. I argue that it is this conflict which lends ChatGPT its 'magical' character. I conclude by showing how these observations can inform future regulation of AI models. (shrink)

This study aims to understand the perceptions and opinions of academicians towards ChatGPT-3 by collecting and analyzing social media comments, and a survey was conducted with library and information science professionals. The research uses a content analysis method and finds that while ChatGPT-3 can be a valuable tool for research and writing, it is not 100% accurate and should be cross-checked. The study also finds that while some academicians may not accept ChatGPT-3, most are starting to accept (...) it. The study is beneficial for academicians, content developers, and librarians. (shrink)

Chat Generative Pre-Trained Transformer (ChatGPT) has been a growing point of interest in medical education yet has not been assessed in the field of bioethics. This study evaluated the accuracy of ChatGPT-3.5 (April 2023 version) in answering text-based, multiple choice bioethics questions at the level of US third-year and fourth-year medical students. A total of 114 bioethical questions were identified from the widely utilised question banks UWorld and AMBOSS. Accuracy, bioethical categories, difficulty levels, specialty data, error analysis and (...) character count were analysed. We found that ChatGPT had an accuracy of 59.6%, with greater accuracy in topics surrounding death and patient–physician relationships and performed poorly on questions pertaining to informed consent. Of all the specialties, it performed best in paediatrics. Yet, certain specialties and bioethical categories were under-represented. Among the errors made, it tended towards content errors and application errors. There were no significant associations between character count and accuracy. Nevertheless, this investigation contributes to the ongoing dialogue on artificial intelligence’s (AI) role in healthcare and medical education, advocating for further research to fully understand AI systems’ capabilities and constraints in the nuanced field of medical bioethics. (shrink)

Nel 1956, in piena guerra fredda, una conferenza di scienziati al Dartmouth College negli Stati Uniti annunciò il lancio di un audace progetto scientifico, l’Intelligenza Artificiale (I.A.). Dopo l’iniziale fallimento degli sforzi della “Hard AI” di produrre un’intelligenza simile a quella umana, alla fine del XX secolo è emerso il movimento della “Soft AI”. Invece di essere orientato a imitare il comportamento umano in relazione a compiti specifici, ha preferito cercare modi alternativi di eseguire i compiti basati sulle particolari funzioni (...) e strutture della macchina. Il fattore decisivo è stata la combinazione della tecnologia di apprendimento automatico con le comunicazioni digitali online, l’incontro tra l’IA e Internet. Le applicazioni dell’IA “soft” sono quelle che vediamo nel mondo dei dispositivi automatici “intelligenti” che informano la nostra vita sociale digitale. Nel seguente articolo mi concentrerò su una particolare applicazione dell’IA per le discussioni online con utenti umani, ChatGPT, per mostrare le implicazioni della tecnologia digitale online nelle modalità storico-sociali dell’esistenza umana. ChatGPT è un’applicazione che combina l’IA con Internet, le possibilità della corrispondenza tra macchine e le potenzialità della tele-comunicazione umana. Il mio approccio si concentra sulle implicazioni fenomenologiche e storico-sociali della proliferazione della tecnologia AI per quanto riguarda la coscienza e la socialità umana. -/- Abstract (english) -/- In 1956, amidst the Cold War, a conference of scientists at Dartmouth College in the United States announced the launch of a bold, scientific project, Artificial Intelligence (A.I.). After the initial failure of “Hard AI” efforts to produce a human-like intelligence, the “Soft AI” movement emerged in the late 20th century. Instead of being oriented towards imitating human behaviour concerning specific tasks, it preferred to seek alternative ways of performing tasks based on the particular functions and structures of the machine. The decisive factor was the combination of Machine Learning technology with Digital Online Communications, the meeting between AI and the Internet. The applications of “Soft” AI are those we see in the world of “smart”, “intelligent” automatic devices that inform our digital social life. In the following article, I will focus on a particular application of AI for online discussions with human users, ChatGPT, in order to show the implications of online digital technology in the social-historical modalities of human existence. ChatGPT is an application that combines AI with the Internet, the possibilities of Machine correspondence with the potentialities of human telecommunications. My approach focuses on the phenomenological and social-historical implications of the proliferation of AI technology as regards human consciousness and sociality. (shrink)

The subject of the study is the socio-cultural threats to the information security of Russian citizens associated with ChatGPT technologies (Chat Generative Pre-trained Transformer, a machine-generated text response generator simulating a dialogue). The object of research − evaluation of the ratio of advantages and threats of generative language models based on "machine learning" in modern (2021-2023) scientific literature (journals HAC K1, K2 and Scopus Q1, Q2). The scientific novelty of the research lies in the culturological approach to the analysis (...) of threats to the security of Russian citizens associated with the use of ChatGPT as one of the technologies of "artificial intelligence". The formulation of the problem of the classical Turing test "to distinguish a person from a machine" is characterized as a scholastic abstraction, instead a more correct and productive approach is proposed: a socio-cultural assessment of the value (based on cultural axiology) of new computer technologies. The starting point of the analysis is the determination of socio-cultural value (or, conversely, damage) as a result of the use of generative language models based on machine learning. Further, the contribution and responsibility of various socio-cultural subjects of its creation and application are revealed − user, creator and developer. The result of the application of the proposed approach is the deconstruction of the discourse of the "philosophy of artificial intelligence" in terms of uncritical translation of developer declarations intended for marketing and attracting financing. Hypertrophied perception, precariously balancing on the edge of utopia and dystopia, is assessed as a risk of incorrect identification and ranking of threats to information security. Assumptions about the hypothetical "superweapon of psychological warfare" mask modern incidents of cross-border leakage of confidential data, the risks of being held accountable for publishing deliberately false information and illegal content as a result of using ChatGPT. National security measures are recommended, including restrictive measures and increasing the general civil culture of information security of users, as well as the orientation of domestic developments of solutions of this type on traditional values, socio-cultural identity and interests of Russian citizens. (shrink)

This essay is based on a close reading of two poems written by ChatGPT. One is about preimplantation genetic testing; the other is about Down syndrome. Examining these AI-generated poems along with several human-composed texts, the author—the father of a young woman with Down syndrome—explores a number of related topics, including the difference between human- and machine-written poetry; ableist bias in large language models; the future of people with intellectual disabilities, in a world of machine intelligence; and the value (...) of writing by people with disabilities. The author does not reject the use of ChatGPT or preimplantation genetic diagnosis, but argues that for them to be compatible with human flourishing, we need to consider the way they are sold to us, the need for regulation, and the assumptions they embed. (shrink)

For decades, healthcare has relied on data-driven algorithms to guide clinical practice. Recent advances in machine learning have opened up new possibilities in the field, enabling detailed analyse...

Many instructors see the use of LLMs like ChatGPT on course assignments as a straightforward case of cheating, and try hard to prevent their students from doing so by including new warnings of consequences on their syllabi, turning to iffy plagiarism detectors, or scheduling exams to occur in-class. And the use of LLMs probably is cheating, given the sorts of assignments we are used to giving and the sorts of skills we take ourselves to be instilling in our students. (...) But despite legitimate ethical and pedagogical concerns, the case that LLMs should never be used in academic contexts is quite difficult to see. Many primary and secondary schools are cutting back their writing instruction in an effort to teach to the test; at the same time, many high-end knowledge workers are already quietly expected to leverage their productivity with LLMs. To prepare students for an ever-changing world, we probably do have to teach them at least a little bit about writing with ChatGPT. (shrink)

We explore ChatGPT’s handling of left-peripheral phenomena in Italian and Italian varieties through prompt engineering to investigate 1) forms of syntactic bias in the model, 2) the model’s metalinguistic awareness in relation to reorderings of canonical clauses (e.g., Topics) and certain grammatical categories (object clitics). A further question concerns the content of the model’s sources of training data: how are minor languages included in the model’s training? The results of our investigation show that 1) the model seems to be (...) biased against reorderings, labelling them as archaic even though it is not the case; 2) the model seems to have difficulties with coindexed elements such as clitics and their anaphoric status, labeling them as ‘not referring to any element in the phrase’, and 3) major languages still seem to be dominant, overshadowing the positive effects of including minor languages in the model’s training. (shrink)

ABSTRACT The emergence of ChatGPT and its ability to imitate student work has precipitated a crisis in education. Responses range from practical efforts to detect or prevent ChatGPT use to existential reflection about learning and assessment. However, the crisis is also epistemological, with educators struggling to determine what students know and fearing that student knowledge is diminishing. The educational philosophies of Socrates, Dewey, and Freire suggest that recognition of ignorance of different kinds (inquisitive, predictive, and practical) on the (...) part of educators is uncomfortable but essential for improving the aims and methods of education. In this way, ChatGPT and the philosophy of education can be mutually illuminating. (shrink)

Cohen’s (2023) mapping exercise of possible bioethical issues emerging from the use of ChatGPT in medicine provides an informative, useful, and thought-provoking trigger for discussions of AI ethic...

Recent advances in natural language generation (NLG), such as public accessibility to ChatGPT, have sparked polarised debates about the societal impact of this technology. Popular discourse tends towards either overoptimistic hype that touts the radically transformative potentials of these systems or pessimistic critique of their technical limitations and general ‘stupidity’. Surprisingly, these debates have largely overlooked the exegetical capacities of these systems, which for many users seem to be producing meaningful texts. In this paper, we take an interdisciplinary approach (...) that combines hermeneutics—the study of meaning and interpretation—with prompt engineering—task descriptions embedded in input to NLG systems—to study the extent to which a specific NLG system, ChatGPT, produces texts of hermeneutic value. We design prompts with the goal of optimising hermeneuticity rather than mere factual accuracy, and apply them in four different use cases combining humans and ChatGPT as readers and writers. In most cases, ChatGPT produces readable texts that respond clearly to our requests. However, increasing the specificity of prompts’ task descriptions leads to texts with intensified neutrality, indicating that ChatGPT’s optimisation for factual accuracy may actually be detrimental to the hermeneuticity of its output. (shrink)

Michael A PetersBeijing Normal UniversityChatGPT is an AI chatbot released by OpenAI on November 30, 2022 and a ‘stable release’ on February 13, 2023. It belongs to OpenAI’s GPT-3 family (generativ...

La importancia que ha adquirido el ChatGPT en el mundo académico universitario en la actualidad es muy trascendente. El estudio propone validar algunas de las variables predictoras, como la eficiencia en la adquisición de información, creatividad, competencia en la escritura, competencia lingüística, rendimiento académico y satisfacción con el propósito de generar instrumentos para la investigación con atributos de fiabilidad y validez. El estudio se realizó en Perú, con una muestra de 400 estudiantes universitarios de ambos sexos. Se utilizaron pruebas (...) de análisis factorial exploratorio y confirmatorio. Para este estudio, se utilizaron análisis factoriales exploratorios y confirmatorios. De este modo, futuras investigaciones permitirán explorar y comprender plenamente la utilidad del ChatGPT en diversos contextos y su impacto en la educación superior. (shrink)