The future and its challenges

Terry Benzschawel

In this chapter, we examine applications of machine learning as they affect people and institutions. In addition, potential policy actions are suggested to control personal identity theft, deter commercial fraud and monitor suspected criminal activity. Equally important are governmental and business responses to increasing income inequality and climate change. Before considering the control of machines and risks to public safety, we consider the advances that have been made in machine learning and their challenges, along with artificial-intelligence-related (AI-related) economic activity. The chapter is concerned with how machine learning and AI will affect the economy, medicine, geopolitical conflicts and education, along with issues of personal freedom and safety. The chapter concludes by describing the emergence of personal robotics and how it might change the nature of human–machine and human-human interactions and attachments.

17.1 COMMON PROBLEMS

The creation and operation of the Internet has had little dependence on machine learning. However, the Internet hosts a large array of useful and malicious software driven by machine learning algorithms. A survey of US adults conducted