Placebo or Assistant? Generative AI Between Externalization and Anthropomorphization

Educational Psychology Review (2024) 36:58 https://doi.org/10.1007/s10648-024-09894-x ESSAY Placebo or Assistant? Generative AI Between Externalization and Anthropomorphization Alexander Skulmowski1 Accepted: 9 May 2024 © The Author(s) 2024 Abstract Generative AIs have been embraced by learners wishing to offload (parts of) complex tasks. However, recent research suggests that AI users are at risk of failing to correctly monitor the extent of their own contribution when being assisted by an AI. This difficulty in keeping track of the division of labor has been shown to result in placebo and ghostwriter effects. In case of the AI-based placebo effect, users overestimate their ability while or after being assisted by an AI. The ghostwriter effect occurs when AI users do not disclose their AI use despite being aware of the contribution made by an AI. These two troubling effects are discussed in the context of the conflict between cognitive externalization and anthropomorphization. While people tend to offload cognitive load into their environment, they also often perceive technology as human-like. However, despite the natural conversations that can be had with current AIs, the desire to attribute human-like qualities that would require the acknowledgment of AI contributions appears to be lacking. Implications and suggestions on how to improve AI use, for example, by employing embodied AI agents, are discussed. Keywords Cognitive externalization · Anthropomorphization · Artificial intelligence · Embodiment · Ethics Introduction As in previous cases of technological progress, the current developments surrounding the introduction of generative artificial intelligence (AI) into everyday life are destined to lead to profound changes. Since generative AIs are used to create texts, pictures, videos, and other types of content from simple text prompts, there * Alexander Skulmowski 1 Digital Education, Institute for Informatics and Digital Education, Karlsruhe University of Education, Bismarckstr. 10, 76133 Karlsruhe, Germany 13 Vol.:(0123456789) 58 Page 2 of 18 Educational Psychology Review (2024) 36:58 is an enormous potential to automatize different types of complex and cognitively demanding tasks. Decades ago, the Internet made a wealth of information accessible in an instantaneous manner, leading to the emergence of the “Google effect” in which people memorize where to find information instead of the information itself (Sparrow et al., 2011). Crucially, technology use can lead to overconfidence regarding abilities and knowledge (Eliseev & Marsh, 2023; Fisher & Oppenheimer, 2021; Ward, 2021) and distorting source memory (Siler et al., 2022). The consequential change in how memory is offloaded (e.g., Fisher et al., 2022; for an overview, see Risko & Gilbert, 2016) is likely to be followed by a normalization of the externalization of entire tasks to generative AIs (Skulmowski, 2023). In contrast to merely offloading memories, the utilization of generative AIs has several consequences that alter the relationship between humans and technology. While external memory stores play a more passive role and simply deliver information on demand, generative AIs (as their name implies) feature a creative element that, until now, was considered uniquely human. These novel capabilities strongly resembling human creative efforts have raised the question of AI authorship (e.g., Draxler et al., 2024; Thorp, 2023) and the ethical use of AI-generated output (e.g., Eaton, 2023; Lund et al., 2023). Most importantly, an emerging field of research investigates the effects of generative AI use on cognition. This paper offers an overview of some of the most important current results and their implications. After a discussion of the technical background of generative AIs and the problem of (academic) dishonesty arising from its use, recent findings concerning the AI-related overestimation of abilities will be presented. These effects have wide-ranging implications for learning and instruction that will be discussed. The Technical Basis of Generative Artificial Intelligence The chatbot ChatGPT has mainstreamed the possibilities of using AI to produce summaries, critical considerations, and even research ideas simply by chatting on a web page. As the output of ChatGPT is in most cases indistinguishable from human writing, this new and popular technology can be seen as a substantial challenge for academic norms at various levels of education (e.g., Bouteraa et al., 2024; Bringula, 2023). Due to the short time this technology has been widely available, few academic norms regarding its use exist. However, incorporating writing or ideas generated using an AI application without acknowledgment is likely to be considered as a form of plagiarism by most (see Mogavi et al., 2024; Tlili et al., 2023). After the Internet had become widely adopted by consumers, copy-and-paste plagiarism has established itself as a major problem in academic settings. Although technology-based solutions such as automated checking software are used by many educational institutions and publishers, idea plagiarism and other forms of plagiarism remain difficult to detect (Roe & Perkins, 2022). Chatbots operating on large language models (LLMs) will likely further complicate this issue. Such chatbots can be used to answer questions spanning a vast area 13 Educational Psychology Review (2024) 36:58 Page 3 of 18 58 of publicly available knowledge, generate summaries of research topics, and can even identify gaps in the literature in order to come up with research ideas. The appeal of chatbots such as ChatGPT lies in their ability to autonomously write high-quality texts based on simple commands such as “Write a summary of the history of Psychology,” “Explain the modality effect,” or “What are some of the open research questions concerning cognitive load in digital learning?”. LLM-based chatbots will usually generate a short overview of the research area, summarize two or more perspectives on the topic, and may end with suggestions regarding topics that may be investigated in the future. These not overly long “replies” could easily be combined into an essay or even a thesis in many academic environments, in particular given that the chat can be continued with additional questions until sufficient material has been generated (Giray, 2023). In contrast to copy-and-paste plagiarism, there exists no definitive method of checking the provenience of the texts (and underlying ideas) at the moment (see Gao et al., 2023). This issue has sparked debate among educators as to whether essays can remain a viable examination method and how academic writing in general will be affected by this technology. Generative Artificial Intelligence Blurring the Line Between a Tool and a Collaborator Besides the problem of currently being impossible to crawl using conventional plagiarism checking software, the similarity of chatbots to other AI-bas (...truncated)