The DOI matches its Crossref record; 115 of the 115 references it cites were found in a registry or an index; none of the 58 sources its claims cite is checked for support yet.
Generative AI Literacy: Twelve Defining Competencies
Open accessAbstract
This article introduces a competency-based model for generative artificial intelligence (AI) literacy covering essential skills and knowledge areas necessary to interact with generative AI. The competencies range from foundational AI literacy to prompt engineering and programming skills, including ethical and legal considerations. These 12 competencies offer a framework for individuals, policymakers, government officials, and educators looking to navigate and take advantage of the potential of generative AI responsibly. Embedding these competencies into educational programs and professional training initiatives can equip individuals to become responsible and informed users and creators of generative AI. The competencies follow a logical progression and serve as a roadmap for individuals seeking to become familiar with generative AI and for researchers and policymakers to develop assessments, educational programs, guidelines, and regulations.
Overview
AI snapshot
Written from the paper’s full text.
TL;DR
The paper proposes a competency-based model for generative AI literacy consisting of twelve competencies, from basic AI literacy to prompt engineering, programming, ethical, and legal knowledge. It argues these competencies can guide education, policy, and professional training for responsible generative AI use.
Key findings
- The model identifies twelve competencies: basic AI literacy; knowledge of generative AI models; knowledge of capacity and limitations; skill to use generative AI tools; ability to detect AI-generated content; ability to assess output; prompt engineering; ability to program and fine-tune; knowledge of contexts; knowledge of ethical implications; knowledge of legal aspects; and ability to continuously learn.
- A preliminary database search in December 2023 using “generative AI literacy” OR “generative artificial intelligence literacy” across five databases returned 6 records after duplicates, indicating no well-established concept; existing papers often conflate generative AI literacy with general AI literacy.
- The paper defines generative AI literacy as a long-term, continuous process of identifying, acquiring, practicing, and mastering core competencies to effectively and responsibly understand, assess, and work with generative AI technologies.
- It proposes the competencies as a foundation for assessments, curricula, professional development, public-sector guidelines, and further research, while noting that positive and negative implications of each competency are mostly speculative.
Methods
- Preliminary database search in ACM Digital Library, IEEExplore, Clarivate Web of Science, Scopus, and Dimensions with the query “generative AI literacy” OR “generative artificial intelligence literacy”; after removing duplicates, 6 records were included and summarized.
- Because of the topic’s novelty, the authors conducted a non-systematic, comprehensive literature review in English covering AI literacy, systematic reviews on generative AI applications, prompt engineering, and competency models.
- The authors identified twelve competencies from the literature, described each in detail with illustrative examples, and used a speculative approach for discussing potential implications due to scarce prior research.
Limitations
- The paper states that the novelty of the topic made a long-standing review approach infeasible, that the potential implications are mostly speculative and based on informed opinions and current trends, and that the competencies are designed based on the current state of the field and may need revision as technology advances.
- The text makes evident that the framework is conceptual and is not empirically validated or tested with a sample; no assessment instrument, proficiency metrics, or outcome data are reported.
- The preliminary database search was limited to one exact query and five databases, yielding only 6 records, which the authors use to justify the non-systematic review approach.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
0 of 58 cited sources checked · 0 supported · 0 flagged
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Given the low amount of results (6 records in total, as described in Section 3.1), all the articles are described in Table 1.”
- Also stated in: § 3.1 Preliminary Database Search · plain
“After removing duplicates, this search resulted in a total of 6 records, which have been included and summarized in Table 1.”
§ Generative AI Literacy: Twelve Defining Competencies > 2 METHODOLOGY
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None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“Despite this, the concept of AI literacy has not evolved, and existing frameworks do not differentiate between generative and predictive models [61,62].”
- Also stated in: § 3.4 Need for a Generative AI Literacy competency model · plain
“the existing literacy frameworks do not differentiate between them.”
§ Generative AI Literacy: Twelve Defining Competencies > 3.2 AI literacy and generative AI
What the sources say
- Not matchedcites [61]
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None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“In the case of ChatGPT, for example, these include the temperature, which determines the “creativity” of the model, the maximum number of tokens to be used, and the top_k and top_p to limit the number of next word choices of the model and the probability of the next word choices, respectively [60,83].”
§ Generative AI Literacy: Twelve Defining Competencies > 5.7 Skill in prompting generative AI tools (Prompt Engineering)
What the sources say
- Not matchedcites [60]
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In the paper
“The output of ChatGPT and other LLMs can often contain a mixture of facts and completely false and fabricated statements, and awareness of this is fundamental [1,5].”
§ Generative AI Literacy: Twelve Defining Competencies > 5.3 Knowledge of the capacity and limitations of generative AI tools
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In the paper
“With the advance of generative AI, it has become increasingly difficult to discern which contents have been entirely human-generated, AI-generated, or AI-enhanced [29].”
§ Generative AI Literacy: Twelve Defining Competencies > 5.5 Ability to detect AI-generated content
What the sources say
- Not matchedcites [29]
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In the paper
“Most generative models that are deployed at the time, whether they are LLMs, text-to-speech, or text-to-image, rely on certain hyperparameters that can be adjusted by the users.”
§ Generative AI Literacy: Twelve Defining Competencies > 5.7 Skill in prompting generative AI tools (Prompt Engineering)
What the sources say
- Not matchedcites [60]
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- Not matchedcites [83]
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In the paper
“This includes a verification of the content of the output with the aid of trusted sources, so to prevent or minimize the effect of model hallucinations [1,3,5].”
§ Generative AI Literacy: Twelve Defining Competencies > 5.6 Ability to assess the output of generative AI tools
What the sources say
- Not matchedcites [1]
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None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“Despite this, the concept of AI literacy has not evolved, and existing frameworks do not differentiate between generative and predictive models [61,62].”
§ Generative AI Literacy: Twelve Defining Competencies > 3.2 AI literacy and generative AI
What the sources say
- Not matchedcites [61]
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- Not matchedcites [62]
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In the paper
“It is important to note that prompt engineering is not limited to LLMs, but to all types of generative AI that use text as input, including text-to-image models, as evidenced by the existing literature and guidelines for text-to-image prompt engineering [57,108].”
§ Generative AI Literacy: Twelve Defining Competencies > 5.7 Skill in prompting generative AI tools (Prompt Engineering)
What the sources say
- Not matchedcites [57]
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- Probably not a substantial claim. 25
- It may state two separate claims as one. 14
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The competencies follow a logical progression and serve as a roadmap for individuals seeking to get familiar with generative AI and for researchers and policymakers to develop assessments, educational programs, guidelines, and regulations.”
- Also stated in: § 4 A COMPETENCY-BASED MODEL FOR GENERATIVE AI LITERACY · plain
“the ordering of these competencies is purposeful and follows a logical progression to represent a structured learning path reflecting a continuum of learning”
§ Generative AI Literacy: Twelve Defining Competencies > Abstract
Tests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
- Rests on an assumption: The rapid rise of generative AI tools and their widespread adoption in various disciplines have created a unique set of skills specific to these novel tools, which go beyond the traditional competencies associated with data literacy, digital literacy, or AI literacy.
- Also stated in: § 4 A COMPETENCY-BASED MODEL FOR GENERATIVE AI LITERACY · plain
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“Generative AI had a disruptive impact on different domains, and not all authorities and organizations have had the time to adapt to it by developing guidelines and rules, as in the case of the scientific and academic world [89,90].”
§ Generative AI Literacy: Twelve Defining Competencies > 5.9 Knowledge of the contexts where generative AI is used
What the sources say
- Not matchedcites [89]
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Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
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In the paper
“some of these detectors tend to overestimate the probability that a text, image, or video is AI-generated, while others underestimate it, and there is often a great divergence in results across different AI detection tools [97].”
§ Generative AI Literacy: Twelve Defining Competencies > 5.5 Ability to detect AI-generated content
What the sources say
- Not matchedcites [97]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
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In the paper
“In recent years, there has been a surge in software and AI models to detect AI-generated content, both text (such as ZeroGPTfoot_9 , GPTZerofoot_10 , PlagiarismCheckfoot_11 , GPT Radarfoot_12 , Writer.comfoot_13 , among others) [18,66,97], images (AI or Not 14 or Is it AI? 15 ) and videos [45,75].”
§ Generative AI Literacy: Twelve Defining Competencies > 5.5 Ability to detect AI-generated content
What the sources say
- Not matchedcites [18]
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Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
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None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“this has become a noteworthy skill to have in the labor market, as increasingly more companies require employees who can use and master generative AI [14,31].”
§ Generative AI Literacy: Twelve Defining Competencies > 5.4 Skill to use generative AI tools
What the sources say
- Not matchedcites [14]
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Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The twelve competencies identified in this paper can be intended as a complement to the existing framework on AI literacy, providing additional guidance on the specific toolbox that a user of generative AI tools needs.”
§ Generative AI Literacy: Twelve Defining Competencies > Abstract
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
- Rests on an assumption: The rapid rise of generative AI tools and their widespread adoption in various disciplines have created a unique set of skills specific to these novel tools, which go beyond the traditional competencies associated with data literacy, digital literacy, or AI literacy.
In the paper
“This concept of generative AI literacy is associated with that of prompt engineering, which is the ability to design effective prompts for generative AI models to produce desired outputs [79].”
§ Generative AI Literacy: Twelve Defining Competencies > Abstract
What the sources say
- Not matchedcites [79]
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In the paper
“However, human detection of AI-generated photos and texts becomes increasingly difficult [68], making AI detectors always more significant.”
§ Generative AI Literacy: Twelve Defining Competencies > 5.5 Ability to detect AI-generated content
What the sources say
- Not matchedcites [68]
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In the paper
“Multimodal prompting, including images and other formats as input, has also emerged and increased in popularity [76]”
§ Generative AI Literacy: Twelve Defining Competencies > 5.7 Skill in prompting generative AI tools (Prompt Engineering)
What the sources say
- Not matchedcites [76]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
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In the paper
“Different sets of guidelines have been written on prompt engineering for ChatGPT and LLMs, highlighting its importance [2,34,87,100].”
§ Generative AI Literacy: Twelve Defining Competencies > 5.7 Skill in prompting generative AI tools (Prompt Engineering)
What the sources say
- Not matchedcites [2]
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As observed from Table 1, there is not a well-established concept of generative AI literacy in the current academic literature.”
- Also stated in: § 3.1 Preliminary Database Search · plain
“The few existing papers tend to conflate it with the more general and better-established concept of AI literacy.”
§ Generative AI Literacy: Twelve Defining Competencies > 3.1 Preliminary Database Search
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Also stated in: § 3.1 Preliminary Database Search · plain
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This paper aims to fill a gap at the intersection of the topics of AI literacy and generative AI, as no set of competencies specific to the use of generative AI had been previously proposed.”
- Also stated in: § 2 METHODOLOGY · plain
“The scarcity of results highlighted the novelty of the concept and the current gap in academic literature.”
- Also stated in: § 3.4 Need for a Generative AI Literacy competency model · plain
“the database search showed the absence of literature defining the concept of generative AI literacy and also a comprehensive framework that systematically addresses competency acquisition in navigating and utilizing generative AI tools.”
§ Generative AI Literacy: Twelve Defining Competencies > Abstract
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Also stated in: § 2 METHODOLOGY · plain
In the paper
“As noted, AI literacy does not equate to computing literacy, nor is computing literacy necessary for AI literacy, as individuals may recognize, learn about, and use AI without necessarily being able to program or having experience in computer science and engineering [61].”
§ Generative AI Literacy: Twelve Defining Competencies > 5.1 Basic AI Literacy
What the sources say
- Not matchedcites [61]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
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In the paper
“the existing frameworks on AI literacy tend to be quite generic, failing to address the specificities of generative AI tools.”
§ Generative AI Literacy: Twelve Defining Competencies > 3.4 Need for a Generative AI Literacy competency model
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“A number of techniques have emerged for this purpose, including automatically generated prompts [86], Chain of Thoughts prompting [50,98,107] and Tree of Thoughts prompting [62,104].”
§ Generative AI Literacy: Twelve Defining Competencies > 5.7 Skill in prompting generative AI tools (Prompt Engineering)
What the sources say
- Not matchedcites [86]
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In the paper
“Guidelines and techniques to help users identify which images, videos, and text have been created by AI [39] are already being discussed.”
§ Generative AI Literacy: Twelve Defining Competencies > 5.5 Ability to detect AI-generated content
What the sources say
- Not matchedcites [39]
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Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“while prompt engineering is one of the competencies and is crucial for generative AI literacy, the proposed model goes well beyond it and the more technical features of generative AI, and considers the contextual and situational aspects.”
§ Generative AI Literacy: Twelve Defining Competencies > Abstract
Load-bearingStrength:boosted· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
- Rests on an assumption: The rapid rise of generative AI tools and their widespread adoption in various disciplines have created a unique set of skills specific to these novel tools, which go beyond the traditional competencies associated with data literacy, digital literacy, or AI literacy.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Hence, fixing these parameters is an additional and more advanced skill to know when mastering prompt engineering.”
§ Generative AI Literacy: Twelve Defining Competencies > 5.7 Skill in prompting generative AI tools (Prompt Engineering)
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Prompt engineering consists of a broad skill set, with different methods that allow to effectively interact with generative models [82].”
§ Generative AI Literacy: Twelve Defining Competencies > 5.7 Skill in prompting generative AI tools (Prompt Engineering)
What the sources say
- Not matchedcites [82]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Generative AI literacy goes beyond technical proficiency and requires combining it with other proficiencies such as adaptive usage, ethical considerations, and legal awareness.”
§ Generative AI Literacy: Twelve Defining Competencies > 7 CONCLUSION
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Generative AI literacy is not a static set of skills, but an evolving one.”
§ Generative AI Literacy: Twelve Defining Competencies > 7 CONCLUSION
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
- Rests on an assumption: Generative AI technology is evolving rapidly, with new models and techniques continually emerging, each with its own set of intricacies.
In the paper
“As part of organizations, individuals already use (or can use) generative AI applications for tasks such as note-taking, summarization, time management, and providing faster support to common queries [12].”
§ Generative AI Literacy: Twelve Defining Competencies > 6.2 Relevance for the Public Sector
What the sources say
- Not matchedcites [12]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
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In the paper
“in 2023 President Joe Biden issued Executive Order 14110 on Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence [40]”
§ Generative AI Literacy: Twelve Defining Competencies > 5.11 Knowledge of Legal Aspects
What the sources say
- Not matchedcites [40]
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In the paper
“In addition to its role in supporting policy development and regulation, generative AI has the potential to ease access to internal knowledge and databases through chat and also provide answers to frequently asked questions by citizens [28].”
§ Generative AI Literacy: Twelve Defining Competencies > 6.2 Relevance for the Public Sector
What the sources say
- Not matchedcites [28]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Thus, the competencies outlined here are not confined to specialists; rather, they cater to a broader audience, reflecting the growing integration of AI into various aspects of daily life.”
§ Generative AI Literacy: Twelve Defining Competencies > 7 CONCLUSION
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
In the paper
“An example of such a scenario occurred during the campaign for Switzerland's 2023 elections [99].”
§ Generative AI Literacy: Twelve Defining Competencies > 5.10 Knowledge of the Ethical Implications
What the sources say
- Not matchedcites [99]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“AI is already employed at various levels in the public sector, including service delivery, management, and monitoring [10,43,64,95].”
§ Generative AI Literacy: Twelve Defining Competencies > 6.2 Relevance for the Public Sector
What the sources say
- Not matchedcites [10]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites [43]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites [64]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites [95]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“While at the time of writing this paper, only a few countries have begun a legislative process regulating AI and its applications, it is likely that several others will follow [37,65].”
§ Generative AI Literacy: Twelve Defining Competencies > 5.11 Knowledge of Legal Aspects
What the sources say
- Not matchedcites [37]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites [65]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“Indeed, in March 2024 the European Parliament approved the European AI Act [32], determining a set of norms to be followed with respect to several aspects of AI at large [41,42,63].”
§ Generative AI Literacy: Twelve Defining Competencies > 5.11 Knowledge of Legal Aspects
What the sources say
- Not matchedcites [32]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites [41]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites [42]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites [63]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Not matched
In the paper
“Several universities have developed guidelines for the use of LLMs in assignments [26].This differs from campus to campus, with some of them prohibiting LLMs altogether, and others allowing them for certain types of coursework.”
§ Generative AI Literacy: Twelve Defining Competencies > 5.9 Knowledge of the contexts where generative AI is used
What the sources say
- Not matchedcites [26]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Not matched
In the paper
“several states from the United States have begun to adopt laws targeting specific aspects of AI [17]”
§ Generative AI Literacy: Twelve Defining Competencies > 5.11 Knowledge of Legal Aspects
What the sources say
- Not matchedcites [17]
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
- Not matched
The paper relies on this without support.
The rapid rise of generative AI tools and their widespread adoption in various disciplines have created a unique set of skills specific to these novel tools, which go beyond the traditional competencies associated with data literacy, digital literacy, or AI literacy.
“the rapid rise of generative AI tools and their widespread adoption in various disciplines have created a unique set of skills specific to these novel tools, which go beyond the traditional competencies associated with data literacy, digital literacy, or AI literacy.”
The paper relies on this without support.
Generative models have the potential to fabricate highly realistic content and give rise to ethical dilemmas about misinformation, authenticity, and societal impact.
“Generative models are ingrained with the potential to fabricate highly realistic content and give rise to ethical dilemmas about misinformation, authenticity, and societal impact.”
The paper relies on this without support.
The outputs of generative AI raise critical questions on authorship, ownership, and originality.
“In the third place, the outputs of generative AI raise critical questions on authorship, ownership, and originality.”
The paper relies on this without support.
Generative AI tools are increasingly becoming accessible and user-friendly, necessitating additional aspects of AI literacy for the general public, not just for people specialized in technology.
“Finally, generative AI tools are increasingly becoming accessible and user-friendly, necessitating additional aspects of AI literacy for the general public, not just for people specialized in technology.”
The paper relies on this without support.
Most prompt engineering techniques include an assessment of the output.
“most prompt engineering techniques include an assessment of the output, but this does not necessarily imply that the user is fully proficient in prompt engineering.”
The paper relies on this without support.
Most users will neither have nor need programming and fine-tuning ability for their specific goals, and can still be literate on generative AI without it.
“Most users will neither have nor need this ability for their specific goals, and still be literate on generative AI without it.”
The paper relies on this without support.
Generative AI technology is evolving rapidly, with new models and techniques continually emerging, each with its own set of intricacies.
“Generative AI technology is evolving rapidly, with new models and techniques continually emerging, each with its own set of intricacies.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“The result is a paradox: tools designed to accelerate research can, when used uncritically, undermine the very skills graduate education is meant to cultivate [1].”
From Students' Practices and Skills in the LLM-Era: "You Can't Outsource the Struggle and Still Get the Skill" (2026) · cites this paper as [1]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“The innovation dimension relates to developing and tailoring new AI tools and workflows to specific educational needs and engaging in human-AI co-creation (Annapureddy et al., 2025).”
From An integrated AI literacy framework for higher‑education teachers: a critical review and conceptual synthesis (2026) · cites this paper as Annapureddy et al., 2025
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“A few studies have proposed AI literacy frameworks for higher education, identifying core competencies such as prompt engineering, ethical awareness, and critical evaluation of AI outputs [1, 22].”
From Students' Practices and Skills in the LLM-Era: "You Can't Outsource the Struggle and Still Get the Skill" (2026) · cites this paper as [1]
The check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“The study identified significant gaps in ethical understanding, innovative use of AI and institutional support among faculty.”
From An integrated AI literacy framework for higher‑education teachers: a critical review and conceptual synthesis (2026) · cites this paper as Annapureddy et al., 2025
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Pentagon example changes from a video to a photo
MinorThe example describes a viral AI-generated video, whereas both cited references describe the incident as a fake picture or photo.
“A recent example from 2023 is the case of a viral AI-generated video of the Pentagon on fire, which created some panic [23,38].”
“38. Mohammed Haddad. 2023. Fake Pentagon explosion photo goes viral: How to spot an AI image.”
AI-literacy definition is cited to the wrong reference
MinorThe text attributes the definition to Long and Magerko as reference [61], but reference 61 is a paper by Leo S. Lo. Long and Magerko are listed as reference 62.
“An often-cited definition of AI literacy is given by Long and Magerko [61]”
“61. Leo S. Lo. 2023. The CLEAR path: A framework for enhancing information literacy through prompt engineering.”
NIH competency definition is cited to the wrong reference
MinorThe quoted competency definition is attributed to the National Institute of Health as reference [70], but reference 70 is by Noh and Han. The NIH entry is reference 71.
“this paper adopts the definition given by the National Institute of Health (NIH), according to which "Competencies are: Knowledge (Information developed or learned through experience, study, or investigation), Skills (The result of repeatedly applying knowledge or ability); Abilities (An innate potential to perform mental and physical actions or tasks); Behaviors (The observable reaction of an individual to a certain situation)" [70].”
“70. YangJin Noh and Songlee Han. 2023. Exploring perception and support strategies for Generative AI Literacy: Focusing on pre-service secondary teachers.”
Citations
Cites
Transformers: State-of-the-Art Natural Language Processing
Wolf, T., Debut, L., Sanh, V., Chaumond, J., Delangue, C., Moi, A., Cistac, P., Rault, T., Louf, R., Funtowicz, M., et al. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations · doi:10.18653/v1/2020.emnlp-demos.6 · Cited by 8,741
ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education
Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · doi:10.35542/osf.io/5er8f · Cited by 7,552
ChatGPT for good? On opportunities and challenges of large language models for education
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · Learning and Individual Differences · doi:10.1016/j.lindif.2023.102274 · Cited by 7,326 · cited 1×
“Multiple systematic reviews have been published on the topic [78, 81] and discussing the impacts of ChatGPT and generative AI in general on different areas including education [6, 47, 49, 58, 72, 81, 88], healthcare [4, 52, 56, 92, 93], research [77, 80, 88], and society [7], among others.”
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., et al. (2023) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2023.102642 · Cited by 4,584
Generative Adversarial Networks: An Overview
Creswell, A., White, T., Dumoulin, V., Arulkumaran, K., Sengupta, B., & Bharath, A. A. (2018) · IEEE Signal Processing Magazine · doi:10.1109/msp.2017.2765202 · Cited by 4,540
Chain-Of-Thought Prompting Elicits Reasoning in Large Language Models
Wei, J., Wang, X., Schuurmans, D., Bosma, M., Ichter, B., Xia, F., Chi, E., Le, Q. V., & Zhou, D. (2022) · Advances in Neural Information Processing Systems 35 · doi:10.52202/068431-1800 · Cited by 4,505
Liu, P., Yuan, W., Fu, J., Jiang, Z., Hayashi, H., & Neubig, G. (2023) · ACM Computing Surveys · doi:10.1145/3560815 · Cited by 4,361
Liu, P., Yuan, W., Fu, J., Jiang, Z., Hayashi, H., & Neubig, G. (2021) · arXiv · doi:10.48550/arxiv.2107.13586 · Cited by 4,352
Large language models in medicine
Thirunavukarasu, A. J., Ting, D. S. J., Elangovan, K., Gutierrez, L., Tan, T. F., & Ting, D. S. W. (2023) · Nature Medicine · doi:10.1038/s41591-023-02448-8 · Cited by 3,944
BAİDOO-ANU, D., & OWUSU ANSAH, L. (2023) · Journal of AI · doi:10.61969/jai.1337500 · Cited by 3,939
Flagged first, then by citations
Research works printed but not linked: 2
- Yoon Chae. 2020. US AI regulation guide: Legislative overview and practical considerations. Journal of Robotics, Artificial Intelligence & Law 3 (2020), 17–40.
- Tambiama Madiega. 2021. Artificial Intelligence Act. European Parliamentary Research Service.https://policycommons.net/artifacts/1894362/artificial-intelligence-act/2644377/#::text=https%3A//policycommons.net/artifacts/1894362/artificial%2Dintelligence%2Dact/2644377/
Cited by
Sorted by citations
Items 301–335 of 335
Educação brasileira: estudos e pesquisa
Sobral, M. N., Linhares, R. N., Andrade, C. D. C., & Horsth, T. A. (2026) · doi:10.17564/2026.88303.42.9
Du, Z., Dong, T., & Wei, B. (2026) · Interactive Learning Environments · doi:10.1080/10494820.2026.2744398
A trajetória da disciplina escolar de história na educação brasileira: persistências e mudanças
Queiroz, J., Ferronato, C. D. J., & Sobral, M. N. (2026) · doi:10.17564/2026.88303.42.9.2
Das concepções de letramento ao letramento digital na educação brasileira
Silva, M. C. R., & Andrade, L. R. D. S. (2026) · doi:10.17564/2026.88303.42.9.11
Linhares, R. N., & Sobral, M. N. (2026) · doi:10.17564/2026.88303.42.9.1
Lima, G. C. D. B. B., Reis, N. R. O. G., Chagas, A. M., & Linhares, R. N. (2026) · doi:10.17564/2026.88303.42.9.18
Avaliação externa da alfabetização em sergipe: análise documental dos indicadores (2015–2025)
Neri, M. J. F., & do Nascimento, R. R. (2026) · doi:10.17564/2026.88303.42.9.8
CIEPS e CAICS enquanto “escolas-casa”: um projeto de educação integral
Amorim, A., Horsth, T. A., & do Nascimento, R. R. (2026) · doi:10.17564/2026.88303.42.9.9
The nexus between agility-fostering competences and AI literacy of higher education students
Chwiłkowska-Kubala, A., Malewska, K. M., & Szumowski, W. (2026) · Management · doi:10.58691/man/235769
Prompt Engineering as Distributed Cognition and Epistemic Infrastructure in Higher Education
Alam, A. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-8332-3.ch004
A Feasibility Study of GenAI Integrated CT Lessons for Second GradersPreprint
Rutherford, T. A., Veng, S., Anisiobi, O. C., & Duque-Baird, S. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.7583918
Sieciński, K., & Oliński, M. (2026) · Industry and Higher Education · doi:10.1177/09504222261498278
Undheim, T. A., Malik, M. Q., & Hashmi, N. (2026) · SoftwareX · doi:10.1016/j.softx.2026.103125
Ma, W., Yuan, F., & Luo, H. (2026) · Journal of Research on Technology in Education · doi:10.1080/15391523.2026.2735312
Wang, X., Chen, C., & Li, S. (2026) · Frontiers in Education · doi:10.3389/feduc.2026.1955702
Weli, W., Purba, S. D., Darmoyo, S., & Josephine, K. O. (2026) · Industry and Higher Education · doi:10.1177/09504222261498330
Reframing AI in Higher Education: From Institutional Regulation to Human-Centered Literacy
Takane, S., Youyue, T., Wang, J., & Shaw, R. (2026) · Springer eBooks · doi:10.1007/978-981-92-2544-6_10
Assessment of New Competencies for Human - AI Teaming in Air Traffic Control
Tuncal, A., & Dursun, E. (2026) · Human factors in aviation and aerospace. · doi:10.26650/hfaa.2026.1965760
From Competence Mapping to ESCO-Aligned Job Profiles for Generative AI and Large Language Models
Katsis, M., Ioannidou, I., & Sirmakessis, S. (2026) · Pan-Hellenic Conference on Progress in Computing and Informatics (PCI) · doi:10.1145/3829216.3829267
Khlud, V., Makhmudova, A., & Туганбекова, Н. (2026) · Engineering Management in Production and Services · doi:10.2478/emj-2026-0016
Fuentes-Henríquez, C. (2026) · Editora Artemis eBooks · doi:10.37572/edart_1710263699
Adnin, R., Saha, A., & Das, M. (2026) · International ACM SIGACCESS Conference on Computers and Accessibility (ASSETS) · doi:10.1145/3797867.3829007
Bessala, J. P. B. (2026) · Journal of Human Resource and Sustainability Studies · doi:10.4236/jhrss.2026.144025
Shari, S., Tarmizi, W. A. M. A., Azmi, N. A., & Daud, M. S. (2026) · International Journal of Modern Education · doi:10.35631/ijmoe.831095
Beimel, D., Amzalag, M., Zviel-Girshin, R., & Voloch, N. (2026) · Education and Information Technologies · doi:10.1007/s10639-026-14178-8
Yong, X., Wu, J. G., & Wang, G. (2026) · International Conference on Intelligent Education and Computer Technology (IECT) · doi:10.1145/3845354.3845531
Design and Evaluation of a Student-Led Generative AI Workshop for Non-Technical University Students
Sendyka, A. (2026) · International Journal of Pedagogy Innovation and New Technologies · doi:10.71358/ijpint.3267
Dušek, M., Bartovčak, G. K., & Frank, D. (2026) · IEEE International Symposium on Intelligent Systems and Informatics (SISY) · doi:10.1109/sisy71351.2026.11738564
From Automation to Augmentation
Mallouli, M., & Mezghani, K. (2026) · International Journal of Human Capital and Information Technology Professionals · doi:10.4018/ijhcitp.426550
EFL learners’ epistemic agency in AI-supported digital storytelling: a rhizomatic analysis
Wang, W.-H., & Yu, B. (2026) · Computer Assisted Language Learning · doi:10.1080/09588221.2026.2756909
Deja, M., Głowacka, E., Kisilowska, M., Pamuła, N., Świgoń, M., & Wojciechowska, M. D. (2026) · The Journal of Academic Librarianship · doi:10.1016/j.acalib.2026.103366
Metadata
- Authors
- Annapureddy, R., Fornaroli, A., & Gatica-Perez, D.
- Affiliations
- École Polytechnique Fédérale de Lausanne (CH)
- Idiap Research Institute (CH)
- Idiap Research Institute, Martigny, Switzerland and EPFL, Lausanne, Switzerland
- Venue
- Digital Government: Research and Practice
- Published
- 2025-02-13
- Volume
- 6
- Issue
- 1
- Pages
- 1-21
- ISSN
- 2639-0175 (ISSN-L)
- 2691-199X
- OpenAlex
- W4401288535
- Cited by
- 333
- References
- 95
- Citations by year
- 2026: 245 · 2025: 81
- FWCI
- 166.06
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Digital Government Research and Practice (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion, cc-by-nc-nd)
- arXiv (Cornell University)
- Funders
- European Union’s Horizon 2020 IcARUS project (882749)
- Horizon Europe ELIAS project (101120237)
- Topics
- Social Sciences › Education › Digital literacy in education
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Social Sciences › Education › Artificial Intelligence in Education
- Keywords
- generative AI literacy, competency-based model, prompt engineering, AI ethics, responsible AI use, artificial intelligence in education, professional training, AI regulation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-11-06, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-11-06 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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