How do children acquire knowledge about voice assistants? A longitudinal field study on children’s knowledge about how voice assistants store and process data

Szczuka, Jessica M.; Strathmann, Clara; Szymczyk, Natalia; Маврина, Л Н; Krämer, Nicole C.

doi:10.1016/j.ijcci.2022.100460

Cited by 21 publications

(7 citation statements)

References 26 publications

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“…For instance, students in Kreinsen and Schultz's (2021) study described AI as having feelings. They also conceptualized AI as the brain of robots, suggesting that AI is comparable to the human brain (see also Emmert-Streib et al, 2020, Szczuka et al, 2022. Kreinsen and Schultz's (2021) findings provide twofold cues about the nature of AI conceptions.…”

Section: Peoples' Conceptions Of Aimentioning

confidence: 99%

“…Thus, in line with Long and Magerko (2020) we argue that distinguishing between narrow and general AI is one of the most important contents of AI literacy education in K-12 contexts. There is emerging evidence that everyday encounters with human-like AI such as voice assistants support the development of anthropomorphic conceptions (Szczuka et al, 2022). Thus, it would be valuable to "demystify" AI by exploring the technical principles of the "human-like" AI solutions students encounter in their everyday life.…”

Section: Pedagogical Implicationsmentioning

confidence: 99%

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Finnish 5th and 6th grade students’ pre-instructional conceptions of Artificial Intelligence (AI) and their implications for AI literacy education

Mertala¹,

Fagerlund²,

Calderón³

2022

Preprint

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There is a common agreement that teaching children about AI should be an integral part of contemporary education. However, not much is known about children’s pre-instructional conceptions of AI, which means that the design of relevant curricula has less than solid footing. The present paper contributes to filling this gap in knowledge by reporting the findings of a qualitative survey study that investigated 195 Finnish 5th and 6th grade students’ conceptions of 1) AI as a technology, 2) where AI is used, and 3) why AI is used. The students conceptualized AI in varying forms, such as robots, devices with sensors, and voice assistants, which, in terms of level of concreteness, varied from high (e.g., sensory technology) to low (e.g., dangerous technology). AI was conceptualized as situated in a variety of locales between home and work environments and everyday and non-everyday contexts, and even ubiquitously. Third, ranging between micro (everyday life) and macro (global policies) levels, AI was perceived as making things easier, providing efficiency, and gaining power over others. Pedagogical implications are discussed.

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Section: Peoples' Conceptions Of Aimentioning

confidence: 99%

Section: Pedagogical Implicationsmentioning

confidence: 99%

Finnish 5th and 6th grade students’ pre-instructional conceptions of Artificial Intelligence (AI) and their implications for AI literacy education

Mertala¹,

Fagerlund²,

Calderón³

2022

Preprint

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“…Particularly in this context, it is crucial to comprehend the mechanisms involved in data storage and access, as research conducted by Szczuka and colleagues demonstrated that such understanding is negatively associated with children's inclination to disclose private information to a voice assistant. More precisely, the language employed by the voice assistant in their study (e.g., using the phrase "I am silent as a grave" when asked about entrusting a secret) holds the potential to prompt children to disclose susceptible information, which can subsequently be accessed by unauthorized individuals [69]. As the act of safeguarding information is integral to the process of identity formation, this naturally includes highly sensitive details concerning body perception and sexuality.…”

Section: Psychological Aspects and Ethical Considerationsmentioning

confidence: 99%

The Usage of Voice in Sexualized Interactions with Technologies and Sexual Health Communication: An Overview

Szczuka,

Mühl

2024

Curr Sex Health Rep

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Purpose of Review The present overview addresses the importance of voice in human-technology interactions within the sexual realm. It introduces empirical evidence within two key domains: (a) sexualized interactions involving artificial entities and (b) communication about sexuality-related health. Moreover, the review underscores existing research gaps. Recent Findings Theories and first empirical studies underline the importance of voice within sexualized interactions with voice assistants or conversational agents as social cues. However, research on voice usage in sexual health-related contexts reveals contradicting results, mainly because these technologies ask users to vocalize potentially sensitive topics. Summary Although the utilization of voice in technology is steadily advancing, the question of whether voice serves as the optimal medium for social interactions involving sexually related artificial entities and sexual health-related communication remains unanswered. This uncertainty stems from the fact that certain information must be conveyed verbally, which could also be communicated through alternative means, such as text-based interactions.

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“…On another note, several contemporary black box technological platforms that utilize AI, such as voice assistants and LLMs, are presented as agentic beings, in all likelihood contributing to specific kinds of misconceptions via children's everyday experiences (e.g., Szczuka et al, 2022). Previous research has suggested that educators should avoid using language that portrays AI and ML algorithms as sentient and agentic beings to avoid the formation of anthropomorphic misconceptions (Mertala & Fagerlund, 2024).…”

Section: Pedagogical Implicationsmentioning

confidence: 99%

Finnish primary school students’ conceptions of machine learning

Mertala,

Fagerlund,

Lehtoranta

et al. 2024

Preprint

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Background and context Language is a powerful tool in shaping thought about abstract domains, including the realm of computing and digital technologies. Review of research on children's machine learning (ML) conceptions suggests that participating children were often provided with conceptual clues about the principles of ML before being asked about their conceptions (i.e., asking them how one could teach a computer). Since the term ML is not explicit about who is learning and from whom, this procedure has arguably steered their answers: with less nudging instruction, ML could also be understood as a process in which a human uses a machine, a computer, for instance, for learning purposes.ObjectiveThis study investigates what kind of conceptions primary school students have about ML if they are not conceptually "primed" with the idea that in ML, humans teach computers.MethodQualitative survey responses from 197 Finnish primary schoolers were analyzed via an abductive method.FindingsWe identified three partly overlapping ML conception categories, starting from the most accurate one: ML is about teaching machines (34%), ML is about coding (7.6%), and ML is about learning via or about machines (37.1%).ImplicationsThe findings suggest that without conceptual clues, children's conceptions of ML are varied and may include misconceptions such as ML is about learning via or about machines. The findings underline the importance of clear and systematic use of key concepts in computer science education. Besides researchers, this study offers insights for teachers, teacher educators, curriculum developers, and policymakers.

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How do children acquire knowledge about voice assistants? A longitudinal field study on children’s knowledge about how voice assistants store and process data

Cited by 21 publications

References 26 publications

Finnish 5th and 6th grade students’ pre-instructional conceptions of Artificial Intelligence (AI) and their implications for AI literacy education

Finnish 5th and 6th grade students’ pre-instructional conceptions of Artificial Intelligence (AI) and their implications for AI literacy education

The Usage of Voice in Sexualized Interactions with Technologies and Sexual Health Communication: An Overview

Finnish primary school students’ conceptions of machine learning

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