Revolution Ethics of Data Science and AI

Introduction

Data science, big data, and AI have been increasingly recognized as major driving forces for next-generation innovation, economy, and education (Cao, 2017). At a high level, Data Science (DS) is the set of fundamental principles that support and guide the principled extraction of information and knowledge from data. Possibly the most closely related concept to data science is data mining - the actual extraction of knowledge from data via technologies that incorporate these principles (Provost & Fawcett, 2013). The term “Data Science” has emerged in the last few years to make it easier to understand the basic work related to data. Data science technology initially involved only statistical analysis. Finally, it adopted new age technologies such as artificial intelligence (AI), machine learning (ML) and data mining. Data science is an ever-evolving technology with huge potential to bring massive improvements in the future. Although Data Science and Artificial Intelligence have existed since the 1950s, both fields have only very recently experienced a surge in popularity as a result of the expansion in the capabilities of technology (Ong & Uddin, 2020). Initially Data Science (DS) which is said to be in the form of future data analysis was started in 1962 by John Turey. The traditional database system was created in 1970. After several years, i.e. in 1974, the concept of neural networks was introduced at the NPIS conference. Then again Jacob Zahavi in the year of 1999 introduced data mining for large data sets. He later proposed the Cleveland Data Science Plan again in 2001. In 2005, Big Data was released to maintain a large number of datasets with high processing speed on the server. In 2006, the concept of Deep Learning was again introduced for Algorithm implementations. Then the concept of machine learning was introduced in 2011 by Watson Jeopardy. Finally, in 2018, the Data Science Global Mainstream emerged to handle the processing of large datasets. Similarly the term “artificial intelligence” was coined by John McCarthy in 1956. McCarthy, along with other pioneers such as Marvin Minsky and Claude Shannon, believed that machines could be programmed to mimic human intelligence. The 1980s saw a resurgence in artificial intelligence research, fueled by the development of new algorithms and the availability of powerful computers. In the 1990s, machine learning emerged, allowing computers to learn from data and improve their performance over time.