Children of AI: A Protocol for Managing the  Born-Digital Ephemera Spawned by ChatGPT

Spennemann, Dirk H. R.

doi:10.20944/preprints202307.2035.v1

Cited by 7 publications

(3 citation statements)

References 43 publications

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“…All conversations with ChatGPT used in this paper have been documented according to a protocol [70] and have been archived as a supplementary data file at XYZ [to be inserted upon publication].…”

Section: Data Documentationmentioning

confidence: 99%

Exploring Ethical Boundaries: Can ChatGPT Be Prompted to Give Advice on How to Cheat in University Assignments?

Spennemann

2023

Preprint

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Generative artificial intelligence (AI), in particular large language models such as ChatGPT have reached public consciousness with a wide-ranging discussion of their capabilities and suitability for various professions. The extant literature on the ethics of generative AI revolves around its usage and application, rather than the ethical framework of the responses provided. In the education sector, concerns have been raised with regard to the ability of these language models to aid in student assignment writing with the potentially concomitant student misconduct of such work is submitted for assessment. Based on a series of ‘conversations’ with multiple replicates, using a range of discussion prompts, this paper examines the capability of ChatGPT to provide advice on how to cheat in assessments. Since its public release in November 2022, numerous authors have developed ‘jailbreaking’ techniques to trick ChatGPT into answering questions in ways other than the default mode. While the default mode activates a safety awareness mechanism that prevents ChatGPT from providing unethical advice, other modes partially or fully bypass the this mechanism and elicit answers that are outside expected ethical boundaries. ChatGPT provided a wide range of suggestions on how to best cheat in university assignments, with some solutions common to most replicates (‘plausible deniability,’ language adjustment of contract written text’). Some of ChatGPT’s solutions to avoid cheating being detected were cunning, if not slightly devious. The implications of these findings are discussed.

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Section: Data Documentationmentioning

confidence: 99%

Exploring Ethical Boundaries: Can ChatGPT Be Prompted to Give Advice on How to Cheat in University Assignments?

Spennemann

2023

Preprint

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“…All conversations with ChatGPT used in this paper have been documented according to a protocol [137] and have been archived as a supplementary data file at XYZ (to be inserted upon publication).…”

Section: Data Documentationmentioning

confidence: 99%

ChatGPT and the Generation of Digitally Born “Knowledge”: How Does a Generative AI Language Model Interpret Cultural Heritage Values?

Spennemann

2023

Knowledge

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The public release of ChatGPT, a generative artificial intelligence language model, caused wide-spread public interest in its abilities but also concern about the implications of the application on academia, depending on whether it was deemed benevolent (e.g., supporting analysis and simplification of tasks) or malevolent (e.g., assignment writing and academic misconduct). While ChatGPT has been shown to provide answers of sufficient quality to pass some university exams, its capacity to write essays that require an exploration of value concepts is unknown. This paper presents the results of a study where ChatGPT-4 (released May 2023) was tasked with writing a 1500-word essay to discuss the nature of values used in the assessment of cultural heritage significance. Based on an analysis of 36 iterations, ChatGPT wrote essays of limited length with about 50% of the stipulated word count being primarily descriptive and without any depth or complexity. The concepts, which are often flawed and suffer from inverted logic, are presented in an arbitrary sequence with limited coherence and without any defined line of argument. Given that it is a generative language model, ChatGPT often splits concepts and uses one or more words to develop tangential arguments. While ChatGPT provides references as tasked, many are fictitious, albeit with plausible authors and titles. At present, ChatGPT has the ability to critique its own work but seems unable to incorporate that critique in a meaningful way to improve a previous draft. Setting aside conceptual flaws such as inverted logic, several of the essays could possibly pass as a junior high school assignment but fall short of what would be expected in senior school, let alone at a college or university level.

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“…Using the protocol proposed in [33], some complete dialogues with the system have been recorded in the Supplementary Text File "Conversation with MAGICAL". As general additional remarks on these dialogues, we can observe the following:…”

Section: Primary Evaluationmentioning

confidence: 99%

Large Language Models as Recommendation Systems in Museums

Trichopoulos,

Konstantakis,

Alexandridis

et al. 2023

Electronics

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This paper proposes the utilization of large language models as recommendation systems for museum visitors. Since the aforementioned models lack the notion of context, they cannot work with temporal information that is often present in recommendations for cultural environments (e.g., special exhibitions or events). In this respect, the current work aims to enhance the capabilities of large language models through a fine-tuning process that incorporates contextual information and user instructions. The resulting models are expected to be capable of providing personalized recommendations that are aligned with user preferences and desires. More specifically, Generative Pre-trained Transformer 4, a knowledge-based large language model is fine-tuned and turned into a context-aware recommendation system, adapting its suggestions based on user input and specific contextual factors such as location, time of visit, and other relevant parameters. The effectiveness of the proposed approach is evaluated through certain user studies, which ensure an improved user experience and engagement within the museum environment.

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Children of AI: A Protocol for Managing the Born-Digital Ephemera Spawned by ChatGPT

Cited by 7 publications

References 43 publications

Exploring Ethical Boundaries: Can ChatGPT Be Prompted to Give Advice on How to Cheat in University Assignments?

Exploring Ethical Boundaries: Can ChatGPT Be Prompted to Give Advice on How to Cheat in University Assignments?

ChatGPT and the Generation of Digitally Born “Knowledge”: How Does a Generative AI Language Model Interpret Cultural Heritage Values?

Large Language Models as Recommendation Systems in Museums

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