Myths, mis- and preconceptions of artificial intelligence: A review of the literature
Myths, mis- and preconceptions of artificial intelligence: A review of the literature
复制标题
关于人工智能的神话、误解和先入之见：文献综述
DOI：
10.1016/j.caeai.2023.100143
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Nerdel, Claudia
中科院分区：
文献类型：
--
作者：
Bewersdorff, Arne;Zhai, Xiaoming;Roberts, Jessica;Nerdel, Claudia
人工智能（AI）几乎在我们生活的各个方面都很普遍。然而，最近的研究发现，围绕人工智能存在大量的困惑和误解。为了在人工智能领域制定有效的教育计划，至关重要的是要检查和理解学习者对人工智能的预先和误解以及神话。本研究对591项研究进行了分析。通过应用以下资格标准确定了25项相关研究：英语书面的关于教育和人工智能的原始实证研究，以及在正式学习环境中报告人工智能概念。该审查发现了来自六大洲的研究，其中大多数在欧洲和北美进行。这些研究主要侧重于中学和大学一级。调查结果揭示了一系列关于人工智能的偏见，误解和神话，例如：学习者通常在技术层面上对人工智能的理解有限。他们倾向于将类似人类的特征或属性归因于人工智能系统，并且可能对人工智能的范围，能力和局限性有狭隘的看法。审查还表明，学习者往往对人工智能的威胁，危险和好处有二元和不具体的看法。有效的教育计划是增强学习者对人工智能理解的关键，从而帮助他们就人工智能融入社会做出明智的决定，而不是被错误信息和不必要的恐惧所左右。这项审查可能有助于为人工智能教育中更有效的教学和推广策略的发展提供信息。
Artificial Intelligence (AI) is prevalent in nearly every aspect of our lives. However, recent studies have found a significant amount of confusion and misunderstanding surrounding AI. To develop effective educational programs in the field of AI, it is vital to examine and understand learners' pre- and misconceptions as well as myths about AI. This study examined a corpus of 591 studies. 25 relevant studies were identified by applying the following eligibility criteria: English-written original empirical research on education and AI and reporting AI conceptions in a formal learning context. The review found studies from six continents, with the majority conducted in Europe and North America. The studies predominantly focus on the school and university levels. Findings reveal a range of preconceptions, misconceptions, and myths about AI, such as: Learners often have limited understanding of AI on a technical level. They tend to attribute human-like characteristics or attributes to AI systems and may have narrow views of AI's scope, capabilities, and limitations. The review also shows that learners often have binary and unspecific views about the threats, dangers, and benefits of AI. Effective educational programs are key to empower learners' understanding of AI, thus helping them make informed decisions about the integration of AI in our society, rather than being swayed by misinformation and unnecessary fear. This review may help inform the development of more effective teaching and outreach strategies in AI education.
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影响因子：
9.9
作者：
Pelau, Corina;Dabija, Dan-Cristian;Ene, Irina
通讯作者：
Ene, Irina
元学习和概念变革
影响因子：
2.3
作者：
R. White;R. Gunstone
通讯作者：
R. Gunstone
DOI：
10.12973/ejmste/75414
发表时间：
2007
影响因子：
--
作者：
G. Ozdemir;Douglas B. Clark
通讯作者：
Douglas B. Clark
DOI：
10.1088/1742-6596/1714/1/012039
发表时间：
2021
期刊：
Journal of Physics: Conference Series
影响因子：
--
作者：
Shubham Joshi;R. Rambola;Prathamesh P. Churi
通讯作者：
Prathamesh P. Churi
接近人工智能和人类的软版本——他们怎么想？
DOI：
10.48550/arxiv.2305.06450
发表时间：
2022
期刊：
ArXiv
影响因子：
--
作者：
A. Lopes
通讯作者：
A. Lopes