Comparative Study on Accuracy of Responses by Select AI Tools: ChatGPT and Perplexity AI Visa Vee Human Responses

This study explored questions whose solutions were provided by human experts, ChatGPT, and Perplexity AI. The responses were triangulated in discussions to identify oversights, alternative frames, and biases against human-generated insights. ChatGPT and Perplexity AI were selected due to their popularity, with ChatGPT gaining over 100 million users and Perplexity AI 87 million within a year. Educational specialists submitted questions across various fields, along with their responses, which were subsequently posed to the AI tools. These responses were coded and evaluated by twelve educational specialists and subject matter experts (N = 24) based on scientific accuracy, actionability, and comprehensibility. Descriptive statistics indicated that Human Experts achieved significantly higher mean scores in both Scientific Accuracy (M = 7.42, SD = 0.65) and Actionability (M = 7.25, SD = 0.77) compared to ChatGPT (M = 6.25, SD = 0.71; M = 5.42, SD = 0.99) and Perplexity AI (M = 4.33, SD = 0.79; M = 4.17, SD = 1.06). In terms of Comprehensibility, ChatGPT led with a mean score of 6.58 (SD = 0.99) compared to Human Experts (M = 7.08, SD = 1.24) and Perplexity AI (M = 5.43, SD = 0.55). Kruskal-Wallis tests revealed significant differences across all dimensions (p < 0.001 for Scientific Accuracy and Actionability; p = 0.015 for Comprehensibility). Post-hoc Dunn's tests confirmed that Human Experts outperformed both AI tools, while ChatGPT was significantly more comprehensible than Perplexity AI. These findings highlight the limitations of AI in delivering scientifically accurate and actionable insights due to factors like lack of emotional intelligence and common sense. The study recommends careful evaluation of AI integration in academic and research contexts to better understand their roles and limitations.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-04
DOI
https://doi.org/10.5281/zenodo.14274466
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
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article

Comparative Study on Accuracy of Responses by Select AI Tools: ChatGPT and Perplexity AI Visa Vee Human Responses

Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Healthcare and Education
article

Comparative Study on Accuracy of Responses by Select AI Tools: ChatGPT and Perplexity AI Visa Vee Human Responses

article en

Abstract

This study explored questions whose solutions were provided by human experts, ChatGPT, and Perplexity AI. The responses were triangulated in discussions to identify oversights, alternative frames, and biases against human-generated insights. ChatGPT and Perplexity AI were selected due to their popularity, with ChatGPT gaining over 100 million users and Perplexity AI 87 million within a year. Educational specialists submitted questions across various fields, along with their responses, which were subsequently posed to the AI tools. These responses were coded and evaluated by twelve educational specialists and subject matter experts (N = 24) based on scientific accuracy, actionability, and comprehensibility. Descriptive statistics indicated that Human Experts achieved significantly higher mean scores in both Scientific Accuracy (M = 7.42, SD = 0.65) and Actionability (M = 7.25, SD = 0.77) compared to ChatGPT (M = 6.25, SD = 0.71; M = 5.42, SD = 0.99) and Perplexity AI (M = 4.33, SD = 0.79; M = 4.17, SD = 1.06). In terms of Comprehensibility, ChatGPT led with a mean score of 6.58 (SD = 0.99) compared to Human Experts (M = 7.08, SD = 1.24) and Perplexity AI (M = 5.43, SD = 0.55). Kruskal-Wallis tests revealed significant differences across all dimensions (p < 0.001 for Scientific Accuracy and Actionability; p = 0.015 for Comprehensibility). Post-hoc Dunn's tests confirmed that Human Experts outperformed both AI tools, while ChatGPT was significantly more comprehensible than Perplexity AI. These findings highlight the limitations of AI in delivering scientifically accurate and actionable insights due to factors like lack of emotional intelligence and common sense. The study recommends careful evaluation of AI integration in academic and research contexts to better understand their roles and limitations.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 71%
Artificial Intelligence in Healthcare and Education
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