This paper reminds me of early nuclear energy “control” advocacy. In fact, the discovery of uranium, and specifically the widespread global knowledge of a significant inventive process that allows the release of a huge amount of energy from a tiny mass (that is, uranium enrichment), induced a viral international wave that only focused on negative applications (for example, the atomic bomb). However, a derailment was initiated in the scientific community that contradicted this endeavor. For instance, scientists like Julius Robert Oppenheimer (“father of the atomic bomb”) and Albert Einstein tried to deviate the course of nuclear energy applications toward objectively virtuous endeavors.

Following such contemplation, and in order to avoid rewriting history, this paper, which is Gill’s introduction to his edited book, opens the door to an understanding of the correct and good use of artificial intelligence (AI). For instance, AI is being exploited for bad, like stealing personal information and demographics to manipulate online media and ads. This is just one possible exploitation. This editorial takes on essential topics related to a new paradigm of good AI applications.

First, Gill debates the subject and then gives a summary of each and every author’s work included in his book. For example, Mulgan addresses combining AI and human intelligence (HI) in order to solve complex social problems, like sociopolitical reasoning and the simulation of different citizen engagement scenarios. On the other side, Bousseta et al. highlight the importance of robotics and brain-machine interfaces (BMI) to enhance the lives of people with disabilities. Furthermore, Maša Jazbec et al. point out that personal feedback from art projects and interactive art systems like idMirror could be used to analyze differences in cultural backgrounds and to provide insight into our critical perception of the current world we live in. Many other important topics are summarized in the paper, including ethical AI, decision-making, Deep Blue (a chess-playing computer system), Watson (a question answering (QA) computer system), neuromorphic engineering, big data, attention economy, machine-self awareness, and the limits of deep learning (its endeavors to reproduce, replicate, or mimic HI, since the latter is fundamentally based on natural human evolutionary processes).

Finally, to quote John le Carré: “When the world is destroyed, it will be destroyed not by its madmen but by the sanity of its experts and the superior ignorance of its bureaucrats” [1]. Thus, in my opinion, Gill’s work helps to build a bridge between experts and bureaucrats, by orienting the former toward the good use of AI and by enlightening the latter about the sensitivity involved. Thus, both sides can avoid the drastic application of the diverse capabilities of AI and in return will help drive the superior conscience of the human mind across its rightful track. After reading this paper, you will learn something new, your vision will be expanded, and your conversations with regard to AI will be altered in a positive sense. I encourage you to read Gill’s work and either share the information or contribute to the discussion, so that you, like Gill, can help steer AI in the right direction.