Home / Research Articles Hub / Generative AI and ChatGPT: Applications, challenge...
🤖 Artificial Intelligence OpenAlex

Generative AI and ChatGPT: Applications, challenges, and AI-human collaboration

📅 Published: July 3, 2023 👤 Fiona Fui‐Hoon Nah, Ruilin Zheng, Jingyuan Cai et al. 📖 Journal of Information Technology Case and Application Research 📊 1,206 citations
AI-Generated Summary

Artificial intelligence (AI) has elicited much attention across disciplines and industries (Hyder and colleagues, Citation2019). In recent years, AI has made a comeback with the introduction of AlphaGo in 2015 and ChatGPT in 2022.

⚡ This is an original paraphrased summary — not copied from the abstract. Full paper available at the source link below.

Key Findings
  • 1 AI has been defined as “a system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation” (Kaplan & Haenlein, Citation2019, p.
  • 2 AI has gone through several development stages and AI winters.
  • 3 In the first two decades (i.e., 1950s and 1960s), AI demonstrated success which included programs such as General Problem Solver (Newell and colleagues, Citation1959) and ELIZA (Weizenbaum, Citation1966).
Why It Matters

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

This summary is based on publicly available metadata and abstract. For the full research paper, visit the original source:

Read Full Paper at OpenAlex
More Artificial Intelligence Papers ← Back to Hub 📚 Learning Hub
Article Details
Source OpenAlex
Category 🤖 Artificial Intelligence
Published Jul 3, 2023
Journal Journal of Information Technology Case and Application Research
DOI 10.1080/15228053.2023.2233814
Citations 1,206
Authors Fiona Fui‐Hoon Nah, Ruilin Zheng, Jingyuan Cai, Keng Siau, Langtao Chen