The starting point is far from now...as the only known highly intelligent creature, human has a long history of dreaming creating or finding other creatures which are smarter than us. However, it was only a dream (science fictions, old myths, and efforts in finding aliens) until human invented modern computer.
The word "computer" was firstly used in 1613 (in the book 'The Yong Mans Gleanings' by Richard Braithwait), long before the invention of modern computer. The foundation theory of modern computer was proposed by Alan Turing. In his 1936 paper "On Computable Numbers, with an Application to the Entscheidungsproblem" [1], Alan Turing provided a formalization of the concepts of algorithm and computation with a "Universal Computing machine". It is now known as Turing machine, which can be considered a model of a general-purpose computer.
Based on Turing's work, John von Neumann and his team built ENIAC (Electronic Numerical Integrator And Computer) in 1946, which was the the first electronic, Turing-complete device in the world. From then, with only over 80 years, computer science and industry developed rapidly, which has significantly changed human society.
ENIAC (Image source: https://spectrum.ieee.org/tech-talk/tech-history/dawn-of-electronics/untold-history-of-ai-invisible-woman-programmed-americas-first-electronic-computer)
The early stage of computer science and industry (and more widely scope of "information technology") focused on hardware, especially on computational power. Governments made a large amount of investment to build supercomputer [2]. And the most influential companies in the markets were hardware manufactories.
Later, when computer (especially PC) were popularized, software became more important and software industry was established. To ensure the quality of software, a methodology called "software engineering" emerged and had great success. Such success had its impact out of the scope of software industry, and many ideas of software engineering have become the standing operating ideas of conducting project management.
Around 1990s, the Internet was invented and popularized. The world became more connected. And now the Internet may be the most important infrastructure, supporting various innovations and businesses. Another phenomenal trend is so called "big data". As Internet users are using more social networking services, sensors, and various other online services, a large amount of data are accumulated in an accelerating rate. People realized the great potential value within the data, and invented various business models to mine value from the data, forming so-called “data economy” (or even “data capitalism”).
To extract knowledge and value from data, we need model. And the model should be able to utilized a large amount of data. Otherwise, big data is burden. Therefore, machine learning, especially deep learning with a large amount of parameters to be trained with data, is necessary.
To summarize, we are in the transformation from digitalization to intelligentization. For the industries, the focus is about extracting value from data with AI. For research, such transformation brings a new paradigm, which is data-driven or computation-driven research [3].
With the increasing amount of data, rapid growing computation capability, and advance of modeling technology (machine learning, especially deep learning), AI is presently becoming the new engine for the rapid development of productivity, heralding a new era that is being unfolded at a pace and scale never previously witnessed in history. AI is also reshaping public administration in profound ways [4, 5], unavoidably making society more knowable and controllable in a dynamic way. While many traditional public administration methods will disappear, a new type of intelligent, automatic, personalized, and data-driven public administration is emerging, e.g., to enhance administrative decision-making [6], optimize public transport [7], solve urban problems [8], formulate policy and plans [9], and guide operational governance [10].
All the contents in these notes are to equip you necessary knowledge of utilizing data with AI models, to prepare for this trend in PA.