Artificial intelligence and global security: future trends, threats and considerations

2021 ◽  
Vol 97 (6) ◽  
pp. 1998-1999
Author(s):  
Kai Chen
Author(s):  
Meghna Babubhai Patel ◽  
Jagruti N. Patel ◽  
Upasana M. Bhilota

ANN can work the way the human brain works and can learn the way we learn. The neural network is this kind of technology that is not an algorithm; it is a network that has weights on it, and you can adjust the weights so that it learns. You teach it through trials. It is a fact that the neural network can operate and improve its performance after “teaching” it, but it needs to undergo some process of learning to acquire information and be familiar with them. Nowadays, the age of smart devices dominates the technological world, and no one can deny their great value and contributions to mankind. A dramatic rise in the platforms, tools, and applications based on machine learning and artificial intelligence has been seen. These technologies not only impacted software and the internet industry but also other verticals such as healthcare, legal, manufacturing, automobile, and agriculture. The chapter shows the importance of latest technology used in ANN and future trends in ANN.


2019 ◽  
pp. 231-247 ◽  
Author(s):  
Henri Arslanian ◽  
Fabrice Fischer

Author(s):  
Sailesh Suryanarayan Iyer ◽  
Sridaran Rajagopal

Knowledge revolution is transforming the globe from traditional society to a technology-driven society. Online transactions have compounded, exposing the world to a new demon called cybercrime. Human beings are being replaced by devices and robots, leading to artificial intelligence. Robotics, image processing, machine vision, and machine learning are changing the lifestyle of citizens. Machine learning contains algorithms which are capable of learning from historical occurrences. This chapter discusses the concept of machine learning, cyber security, cybercrime, and applications of machine learning in cyber security domain. Malware detection and network intrusion are a few areas where machine learning and deep learning can be applied. The authors have also elaborated on the research advancements and challenges in machine learning related to cyber security. The last section of this chapter lists the future trends and directions in machine learning and cyber security.


Author(s):  
Kunz Martina ◽  
Héigeartaigh Seán Ó

This chapter provides an overview of international law governing the applications of artificial intelligence (AI) and robotics that affect global security, highlighting challenges arising from technological developments and how international regulators are responding to them. Much of the international law literature thus far has focused on the implications of increasingly autonomous weapons systems. The chapter seeks to cover a broader range of global security risks resulting from large-scale diffuse or concentrated, gradual or sudden, direct or indirect, intentional or unintentional, AI- or robotics-caused harm. Applications of these technologies permeate almost every domain of human activity and thus unsurprisingly have an equally wide range of risk profiles, from a discriminatory algorithmic decision causing financial distress to an AI-sparked nuclear war collapsing global civilization. Hence it is only natural that much of the international regulatory activity takes place in domain-specific fora. Many of these fora coordinate with each other, both within and beyond the United Nations system, spreading insights and best practices on how to deal with common concerns such as cybersecurity, monitoring, and reliability, so as to prevent accidents and misuse.


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