1.1 Research Background
People make decisions every day and even every second, such as deciding how to go to work or which route to drive. If you were a company manager, you might make many managerial or strategic decisions. The emergence of information technology (IT) dramatically changed people’s way of life and business operations. Information technology enabled us to live more conveniently and work more efficiently.
To date, each emerging technology has brought great change to people and business. Enterprises introduced automation technology to reduce labor and increase productivity. People could acquire the product or service at low cost because of less human cost and mass-production. With the popularity of the Internet, people could obtain information more easily than before. To recognize and respond to the rapidly changing needs of customers, enterprise regarded information technology as an important asset for supporting itself and becoming more efficient.
As information technology changed from the motivation factor to the hygiene factor, it became an indispensable part of enterprise. Due to this situation, information technology accumulated many of the best practices from various industries.
The best-practice-embedded information technology was a nice example for enterprises or individuals who understood less than information technology. In addition, the maturation or appearance of a new technology often accompanied innovation or transformation, because the barrier or the challenge could be handled due to advanced IT. For example, with the popularity of mobile devices and networks, the barrier to location-based service (LBS) was decreased and it became easier to provide relevant services. Based on the gradually completing infrastructure, more and more innovative business models were created and made profitable.
According to Moore’s Law, chip performance doubles every 18 months (Moore, 1998). With the emergence and progress of technology, IT linking with emerging technologies, such as sensors, cloud computing, big data and Internet of Things, can create a greater variety of applications; that is, the roles of IT become more diverse.
For example, Rolls-Royce first created an innovative service business model: sell the “flight hours and maintenance service” rather than the engine. The sensors that were embedded in the aircraft engine collected and sent data back to Rolls-Royce Engine Health Management where it is continuously monitored by professional staff. With big data analysis and a cloud platform, Rolls-Royce could exactly monitor the engine health status and provide real-time notification and precise maintenance service to always
2
keep the engine in the best condition. The engine and aircraft information was also provided to the pilot to support decision-making such as the landing plan, maintenance plan or fuel plan.
With the combining of these technologies, IT can collect more data and generate valuable information. The decision environment and condition also became more rapidly changing and unpredictable. Today, IT plays a diverse role that can help people to make rapid and precise decisions instead of only providing automation or support.
Meanwhile, Gartner (2016) announced that artificial intelligence is one of the Top 10 Strategic Technology Trends for 2017.
A typical case was the autonomous car, which involved the application of artificial intelligence, navigation, sensors, automated control, cloud computing, big data analysis, Internet of Things (V2V and V2I), and required the most dynamic use of IT. To drive safely, the autonomous car collected data from sensors and the cloud; then, the computer (also called the “brain”) of the autonomous car had to process high-volume data and make high-velocity decisions in milliseconds to control the car. Compared to the previous applications in enterprises, the role of IT in the autonomous car is not only purely automated or supportive; a better ability to learn and determine was significant for autonomous driving.
1.2 Research Motivation
From the case studies of the autonomous car, we found that IT played a new role during autonomous driving. Not only is the role of IT in the autonomous car different from previous roles, there were also differences in this role between companies developing the autonomous car.
In terms of research and development, we find that Google’s policy was different from that of other car manufacturers such as Tesla, BMW, and Toyota. Most car manufacturers reserved a steering wheel so that drivers could switch the driving mode from automated to manual at any time. However, Google’s autonomous car aborted the steering wheel, which meant that the Google autonomous car totally excluded humans from the driving decision-making process.
Therefore, we started thinking. When artificial intelligence and other IT become more advanced, how does the role of “human” and “IT” transform during the decision-making process? With the progress of artificial intelligence, would the role of humans be completely replaced by IT?
Through the case of the autonomous car and the development of advanced driver assistance systems (ADAS), we hoped to explore the possible new role IT played, and the impact that big data and artificial intelligence (AI) technology had on businesses.
3
1.3 Research Objectives and Questions
The objective of this research was to understand the new roles played by IT in the autonomous car. We focused on the various IT roles in existing cases and the autonomous car and its impact on the decision process, and how we choose the appropriate information system to help make a quick decision.
The key questions are as follows:
• How does Information Technology impact decision-making in the autonomous car?
• What roles do Information Technology and humans play during the decision-making process?
1.4 Research Plan and Flow
To understand the new roles played by IT in the autonomous car, we intended to build a framework to help deconstruct the IT decision-making process, apply it to actual cases and discuss the diverse IT roles. The research plan and flow are shown in Figure 1.
4
Figure 1. Research Plan and Flow
5