The first foundations of AI were built more than 50 years ago, but only in the last few years has the innovation brought by AI spread through the world as a mainstream technology. This new wave of innovation is mainly due to the evolution of deep neural networks in supervised learning systems. However, the most recent breakthrough in artificial intelligence involves reinforcement learning, and most notably, deep reinforcement learning. Results like the ones that were obtained in the game of Go and Dota highlight the impressive quality of RL algorithms that are able to show long-term planning, ability in teamwork, and discover new game strategies that are difficult to comprehend even for humans. 

The remarkable results that were obtained in the simulated environments started a new wave of applications of reinforcement learning in the physical world. We are only at the beginning, but many areas are and will be impacted, bringing with it profound transformations. RL agents that are embedded in our everyday life can enhance the quality of life by automating tedious work, addressing world-level challenges, and discovering new drugs – just to name a few possibilities. However, these systems, which will populate both our world and our lives, need to be safe and reliable. We aren't at this point yet, but we are on the right track.

The ethical use of AI has become a broad concern, such as in the employment of autonomous weapons. With this rapid technological progress, it is hard for the policymakers and the population to be at the forefront of creating open discussions about these issues. Many influential and reputable people also suggest that AI is a potential threat to humanity. But the future is impossible to predict, and the technology has a long way to go before developing agents that can actually show abilities that are comparable to those of humans. We have creativity, emotions, and adaptability that, for now, cannot be emulated by RL.

With careful attention, the near-term benefits brought by RL can dramatically outweigh the negative side. But to embed sophisticated RL agents in the physical environment, we need to work on the RL challenges we outlined previously. These are solvable and, once addressed, reinforcement learning has the potential to decrease social inequalities, improve the quality of our life, and the quality of our planet.