Long before artificial intelligence was a glimmer in the eye of the financial, transportation or healthcare industries, it was being developed and tested in the gaming community. In fact, the earliest instance of artificial intelligence in games was in 1952, when a UK graduate student created an AI that could play a perfect game of tic-tac-toe. Gaming has driven a lot of the artificial intelligence innovations and served as a proving ground for constructed environments and realism tests that are applicable in other industries. Today, AI developers are figuring out ways to make machines think, learn and develop their own personalities, innovations that will not only change gameplay but will impact our everyday lives. In fact, artificial intelligence and gaming are intertwined in a symbiotic relationship.
What if a game could alter strategy or tactics based on the skill level of the player? That’s precisely the direction some gaming companies are heading. Reinforcement learning is a type of machine learning that allows the machine to learn its behaviour based on feedback from the environment. There is great potential for advanced learning in games, but it must be used carefully to avoid common problems such as mimicking stupidity, set behaviour and more.
With today’s accelerating pace of machine learning enhancements, the first challenges to be tackled will be in support of game development and design, but teams are also tackling more advanced concerns such as personalisation of the gaming experience based on each individual player’s behavioural data. Above all, gaming companies are trying to find that sweet spot where AI provides more realism and natural interaction between players and environments and becomes sophisticated enough to respond realistically to live input rather than scripted plots. There are also intriguing marketing applications that AI can support but only if a quality user experience is preserved.
As Google’s AlphaGo programme proved, given enough data to analyse—in this case millions of played Go games—a machine can develop a competitive advantage by developing strategies that no human would be able to consider. But, analysing data is quite different than analysing human emotion and relations. The gaming industry is now trying to tackle how to create emotional AI that more closely resembles human relationships. This would provide a better player experience, but this technology would be beneficial outside the gaming world as well. As it has done in the past, video games can provide the “testing ground” to vet more elaborate AI so that those learning experiences can then be applied to other industries from banking, scientific research and more. The reality is video game developers spurred the innovation that powers much of the AI progress that impacts other industries.
Humans and AI, the need for both
With a recent experiment out of the Georgia Institute of Technology where AI recreated a game engine simply by watching gameplay, questions arose about the potential impact to human employment as is often the case with any example of a machine taking over a task that had historically been done by people. Researchers in this case responded that AI would “aid in development” and will help novice game developers reach levels of development that would have been out of their reach without AI assisting. Video games are made for the enjoyment of humans, and there’s only one sure-fire way to determine if a game keeps humans entertained and that’s having a human test it.
The gaming industry is realising the monetisation opportunities when blending the gaming industry with real-world experiences such as at amusement parks on rides inspired or made to act like popular video games, movies and merchandising. There is a heightened attraction by venture capital firms to invest in AI that contributes to the gaming business and not just the gaming experience.
I will be keeping a close eye on the gaming industry to see what might be coming down the pipe in terms of AI evolution and innovation. The gaming industry has proven time and time again that that it is fertile testing ground for the technology that will ultimately impact our everyday lives.
Where to go from here
If you would like to know more about AI and machine learning, cheque out my articles on:
Or browse the Artificial Intelligence & Machine Learning section or AI use case library of this site to find more articles and many practical examples.