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Exploring excitement counterbalanced by concerns towards AI technology using a descriptive-prescriptive data processing method

Computer Science

Exploring excitement counterbalanced by concerns towards AI technology using a descriptive-prescriptive data processing method

S. Oprea and A. Bâra

This research conducted by Simona-Vasilica Oprea and Adela Bâra delves into how the public perceives AI technologies, such as facial recognition and driverless cars. Through a hybrid data analysis approach, distinct clusters of excitement and concern were identified, providing valuable insights for informed policy discussions on AI adoption.

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Playback language: English
Abstract
This research explores public sentiment towards AI technologies, focusing on facial recognition, social media algorithms, and driverless cars. A hybrid descriptive-prescriptive data processing method, combining visualization, cross-tabulation, K-means clustering, PCA, ANOVA, and Random Forest prediction, was used to analyze a large survey dataset (over 5000 respondents). Three distinct clusters were identified, revealing varied levels of excitement and concern regarding AI. The model accurately predicted cluster affiliation (F1 score of 0.99 for the test set and 0.98 for the out-of-sample set). The findings offer insights into public perception and can inform policy and dialogue around AI adoption.
Publisher
Humanities and Social Sciences Communications
Published On
Mar 11, 2024
Authors
Simona-Vasilica Oprea, Adela Bâra
Tags
AI technologies
public sentiment
facial recognition
social media algorithms
driverless cars
data analysis
public perception

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