Pathways to Artificial General Intelligence: A Brief Overview of Developments and Ethical Issues via Artificial Intelligence, Machine Learning, Deep Learning, and Data Science

• Published in: Advances in Artificial Intelligence and Applied Cognitive Computing pp. 73 - 87
• Main Authors: Iman, Mohammadreza, Arabnia, Hamid R., Branchinst, Robert Maribe
• Format: Book Chapter
• Language: English
• Published: Cham Springer International Publishing 2021
• Series: Transactions on Computational Science and Computational Intelligence
• Subjects: Artificial general intelligence; Artificial intelligence; Artificial neural network; Data science; Deep learning; Ethics; Machine learning; Reinforcement learning; Un/semi/supervised learning
• ISBN: 9783030702953; 3030702952
• ISSN: 2569-7072; 2569-7080
• DOI: 10.1007/978-3-030-70296-0_6

Today, devices and applications powered by artificial intelligence (AI) include modes of transportation, home appliances, and mobile applications; in short, they are ubiquitous. Many people will have at least heard of AI and perhaps even subdivisions of AI such as Machine Learning (ML) and Deep Learning (DL). Each of these represents an advanced tool of data science explored in this article. First, we briefly review the history of these developments in data science, tracing the history from the first mechanical computer in 1850 to the current state of DL in 2020. Each section overviews some basic definitions, tenets, and current and future developments. We discuss possible future directions of AI—including the transition to Artificial General Intelligence (AGI). Finally, we explore some of the ethical dilemmas posed by such advances and offer a call to data and social scientists to carefully consider the implications of these technologies.