Perception and Ethical Challenges for the Future of AI as Encountered by Surveyed New Engineers

Hisham O. Khogali () and Samir Mekid
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Hisham O. Khogali: Interdisciplinary Research Center for Intelligent Manufacturing and Robotics, King Fahd University for Petroleum and Minerals, Dhahran 31261, Saudi Arabia
Samir Mekid: Interdisciplinary Research Center for Intelligent Manufacturing and Robotics, King Fahd University for Petroleum and Minerals, Dhahran 31261, Saudi Arabia

Societies, 2024, vol. 14, issue 12, 1-23

Abstract: Our extensive history of embracing AI technological advances demonstrates that AI may be a useful tool if humans learn to use it intelligently, and that concerns about it replacing human occupations may be unwarranted. Indeed, a range of remarkable new AI approaches are fast transforming diverse human experiences and fundamentally disrupting our lives, but not without some drawbacks. This study reflects on how new engineers view AI’s influence on trust and ethical attitudes. Data-driven perceptions drive educated debates, education initiatives, and legislative decisions aimed at effectively addressing non-scientific AI concerns. This contributes to improving the future of AI-based learning through transdisciplinary research that considers the evidence of ethical challenges raised by AI misapplication. Our analysis of quantitative data from a survey of 715 recently graduated engineers from diverse fields, who often use information technologies, reveals that many believed AI-related difficulties were scientifically uncertain. According to this study’s findings, the observed variance in the trend relating to reduced fear of job losses due to AI (R 2 = 0.1121) suggests that specialties heavily impacted by crucial decision making have a lower level of fear. This provides strong evidence for an optimistic path to AI breakthroughs boosting the level of confidence in and acceptance of AI across many industries.

Keywords: artificial intelligence (AI); misuse of AI; learning with AI technology; AI challenges; AI trust; AI ethics (search for similar items in EconPapers)
JEL-codes: A13 A14 P P0 P1 P2 P3 P4 P5 Z1 (search for similar items in EconPapers)
Date: 2024
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