Summary The Ineffectiveness and Harm of Artificial Intelligence arxiv.org
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One Line
AI language models are useful for fact-checking, but exposure to AI-generated fact checks can actually reinforce false beliefs.
Slides
Slide Presentation (10 slides)
Key Points
- Artificial intelligence (AI) language models have shown impressive ability in fact-checking tasks, but their impact on human behavior is unclear.
- Participants who chose to view AI-generated fact checks were more likely to believe false headlines and more willing to share all headlines, regardless of their veracity.
- The document includes a list of references to various research papers and articles related to artificial intelligence, fact-checking, language models, and human-AI interaction.
- The study analyzed the effectiveness and harm of AI fact-checking and found significant mean differences in fact-checking scenarios, indicating that AI fact checks can be harmful.
- The document discusses the negative consequences and limitations of AI, including its ineffectiveness, potential for bias and discrimination, and the importance of accounting for AI accuracy.
- The study collected a sample of 1,500 participants with diverse demographics to analyze the effectiveness and harm of AI in fact-checking scenarios.
- Tables and figures in the document provide statistical analysis and regression models to examine the relationship between attitude towards AI, headline veracity, and belief/intent to share headlines.
Summaries
19 word summary
AI language models are effective in fact-checking tasks, but viewing AI-generated fact checks can increase belief in false headlines.
41 word summary
Artificial intelligence (AI) language models have been effective in fact-checking tasks, but their impact on human behavior is uncertain. In a randomized control experiment, researchers found that participants who viewed AI-generated fact checks were more likely to believe false headlines and
664 word summary
Artificial intelligence (AI) language models have shown impressive ability in fact-checking tasks, but their impact on human behavior is unclear. In a randomized control experiment, researchers investigated the effect of fact checks generated by an AI model on belief in and sharing
In a study on the effectiveness of AI fact-checking, researchers found that participants who chose to view AI-generated fact checks were more likely to believe false headlines and more willing to share all headlines, regardless of their veracity. These effects were more pronounced
This summary is unclear as it is not clear what specific information is being summarized.
The provided document contains a list of references to various research papers and articles related to artificial intelligence, fact-checking, language models, and human-AI interaction. These sources cover topics such as computational fact-checking, automated fact-checking, the capabilities
This summary provides a concise version of the text excerpt, preserving important details and highlighting key points. The summary is organized into separate paragraphs to distinguish distinct ideas for readability, while retaining the original order in which ideas were presented.
The text includes a list of
The document includes a list of URLs and references to various studies, surveys, and resources related to the effectiveness and harm of artificial intelligence (AI). These sources cover topics such as AI's ability to generate pro-vaccination messages, educational attainment in the
The document discusses the attitude towards AI and headline congruence. It also includes regression analyses on the ineffectiveness of AI fact checks.
The article discusses the ineffectiveness and harm of artificial intelligence (AI). It mentions the importance of accounting for AI accuracy and the choice between opt-in and opt-out approaches. Additionally, it includes an analysis of interactions and attitudes towards AI.
Headline congruence is discussed in section 4.2 of the document.
The document titled "The Ineffectiveness and Harm of Artificial Intelligence" discusses the negative consequences and limitations of AI. It emphasizes that AI algorithms are often ineffective and can lead to harmful outcomes. The document argues that AI systems are prone to bias and discrimination
Our study aimed to detect the effectiveness of artificial intelligence (AI) in fact-checking and its potential harm. We collected a sample of 1,500 participants, with a fairly equal gender distribution and diverse age and race segments. The participants also had
The study analyzed the effectiveness and harm of artificial intelligence (AI) in fact-checking scenarios. The results showed significant mean differences in fact-checking scenarios for both belief and share groups, indicating that AI fact checks can be harmful. However, a significant
The excerpt discusses the ineffectiveness of artificial intelligence (AI) and the potential harm it can cause. It presents statistical analysis and regression models to examine the relationship between attitude towards AI, headline veracity, and belief/intent to share headlines. The
The summary focuses on the key points and important details of the text excerpt, while organizing them into separate paragraphs for readability.
Table S11 presents the coefficients related to the ineffectiveness of AI fact checks for the belief group. The results show that participants
The excerpted text includes figures and tables from the document "The Ineffectiveness and Harm of Artificial Intelligence." The figures show the relationship between headline sharing intent and attitude towards AI (ATAI) in different conditions. The panels represent participants' responses to
The study analyzed the ineffectiveness and harm of artificial intelligence (AI). The results showed that opting out of AI had a significant effect on the outcome, with a negative coefficient. The interaction between opting out and veracity also had a positive coefficient.
Tables S27 and S28 show that there is no significant interaction between belief and share groups in any fact-checking scenario. Tables S29 and S30 examine the differences in behaviors based on headline congruence in the optional condition for the belief and
Table S25 presents the account for AI accuracy coefficients for the Congruence interaction in the Belief Group. The table includes estimates, standard errors, t values, and p values for various variables. Table S26 provides the same information but for the