Exploring Societal Concerns and Perceptions of AI: A Thematic Analysis through the Lens of Problem-Seeking
Naomi Omeonga wa Kayembe

TL;DR
This paper introduces a framework distinguishing problem-seeking from problem-solving to better understand human intelligence versus AI, analyzing YouTube discussions to reveal societal perceptions and ethical considerations surrounding AI.
Contribution
It proposes a novel conceptual framework emphasizing problem-seeking as central to human intelligence and analyzes public discourse to inform responsible AI development.
Findings
Public discourse shows fascination and skepticism towards AI.
Themes include privacy, job displacement, misinformation, and ethics.
Humans integrate goal-setting with cognition, unlike current AI limitations.
Abstract
This study introduces a novel conceptual framework distinguishing problem-seeking from problem-solving to clarify the unique features of human intelligence in contrast to AI. Problem-seeking refers to the embodied, emotionally grounded process by which humans identify and set goals, while problem-solving denotes the execution of strategies aimed at achieving such predefined objectives. The framework emphasizes that while AI excels at efficiency and optimization, it lacks the orientation derived from experiential grounding and the embodiment flexibility intrinsic to human cognition. To empirically explore this distinction, the research analyzes metadata from 157 YouTube videos discussing AI. Conducting a thematic analysis combining qualitative insights with keyword-based quantitative metrics, this mixed-methods approach uncovers recurring themes in public discourse, including privacy,…
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Taxonomy
TopicsEthics and Social Impacts of AI
MethodsSparse Evolutionary Training
