Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

AI Agents from Copilots to Coworkers: Historical Context, Challenges, Limitations, Implications, and Practical Guidelines

Version 1 : Received: 10 April 2024 / Approved: 10 April 2024 / Online: 10 April 2024 (10:48:44 CEST)

How to cite: Hayawi, K.; Shahriar, S. AI Agents from Copilots to Coworkers: Historical Context, Challenges, Limitations, Implications, and Practical Guidelines. Preprints 2024, 2024040709. https://doi.org/10.20944/preprints202404.0709.v1 Hayawi, K.; Shahriar, S. AI Agents from Copilots to Coworkers: Historical Context, Challenges, Limitations, Implications, and Practical Guidelines. Preprints 2024, 2024040709. https://doi.org/10.20944/preprints202404.0709.v1

Abstract

This paper examines the transformative journey of Artificial Intelligence (AI) agents from copilots to integral coworkers within diverse sectors. Beginning with a foundational overview, we delve into the historical evolution of AI agents, highlighting key technological milestones and the shift from simple automated tools to sophisticated decision-making systems capable of learning and adapting over time. We explore the capabilities of AI agents, including problem-solving, predictive analytics, and automation, and their applications across healthcare, business, and education, showcasing their role in diagnostics, customer service, and personalized learning, among other areas. We also address the integration of AI agents in the workplace, presenting strategies for collaboration between humans and AI, and outline the challenges and ethical considerations that accompany the development and deployment of AI technologies. A comprehensive tutorial provides insight into the development process of AI agents, emphasizing goal definition, data handling, algorithm selection, and ethical guidelines. We also consider the pathway towards Artificial General Intelligence (AGI) and the societal and ethical implications of widespread AI integration, proposing strategies for equitable and ethical AI use.

Keywords

artificial intelligence agents; human-AI collaboration; generative AI; artificial general intelligence; ethical AI

Subject

Computer Science and Mathematics, Artificial Intelligence and Machine Learning

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