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Human-Created and AI-Generated Text: What’s Left to Uncover?

  • Steven Salter,
  • Phoey Lee Teh,
  • Richard Hebblewhite

摘要

The advent of generative Artificial Intelligence (AI) has brought about profound changes in society, education, and the professional realm. Machine Learning models have created remarkably sophisticated language generators, blurring the line between human-authored content and AI-generated text. This poses a challenge for educators and professionals in distinguishing authentic work from instances of plagiarism. This study investigates the fundamental distinctions between human and AI texts by analyzing perspectives from human points of view. It aims to present the outcome of those five questions that we examined about human perceptions of text composition and contrasting them with computer-generated text. By exploring this, it aids in upholding academic integrity and contributes to advancing our comprehension of Natural Language Processing. In essence, this research strives to maintain academic credibility in a landscape transformed by AI and nurtures the growth of more equitable AI technologies.