How Gaming Can Change the Data Science Industry
By: Ej Ozyazgan
Tags: Gaming, Next Generation, Data Science, AI

How Gaming Can Change the Data Science Industry

How gaming is becoming the benchmark for data science and AI development

AI AT PLAY — Walter Newton

The spread of Data Science

Over the past few years, data science has become popularized and more and more ingrained in every aspect of our lives. From mass marketing campaigns on Amazon to the recommendations tab on YouTube, data science has become the tool to track and analyze daily decisions. Even if you don’t realize it at first, data science dictates a lot of different aspects of our lives. This versatility has led it to become one of the most sought out job positions and college majors. The ability to analyze data has become an important aspect of any job.

Data science has spread to almost every industry, but there are still a few where it has just hit the surface of, one of which is the gaming industry. Historically, gaming is an industry that has mainly been human-oriented. Games are generally made by humans for humans to play. But recently, this has begun to change with the creation of AI bots designed to play even the most complex game from online poker to huge multiplayer games like Dota 2 and Starcraft 2. This introduction of AI into the gaming industry has opened up the possibility for a whole new avenue of data science and the merger of these two industries.

Data in Gaming

When thinking about games, data, is usually not what first comes to mind. You may think about the rules, the strategies, or even the lore behind the game. But a key feature of all types of games is data. While playing a game you are constantly collecting data, knowingly or not, on the current game state and making predictions and decisions based on this data. Making predictions and decisions based on data, that is what data science is all about! Not only are games loaded with data, but the data itself is more accessible and useful than public data sets. Game data can also be collected by individuals and does not require excessive time and resources. Gaming is an amazing way for data scientists to get hands-on with diverse sets of data, as well as a great way for AI developers to have an avenue for testing new algorithms and theories.

Data-Oriented Gaming

Modern multiplayer games like Data 2 and Starcraft 2 are great games for bringing data science and gaming closer together and making them more accessible. Games like Dota 2 and Starcraft 2 have tremendous amounts of data to be utilized, however, a lot of this data is hidden from the player. For example, in Dota 2 you do not always know where your appointments are or what portions of the map they are able to see. In Starcraft 2 the map is also hidden as well as your opponents base and resources. This imperfect information is where data science comes in. Using data science, and game history you could predict what your opponent is doing. This is also why these games have become the new benchmark for training AI. With so much imperfect information, AI-driven bots need to actually learn the game and understand more complex game mechanics such as resource management, patience, and long term strategy development. This is why these games are such a great opportunity for data scientists to get large amounts of data to analyze and play with. These games are also some of the most globally played and known games, thus making them a great launchpad for bringing gaming and data science together.

New Generation of Gaming

With all this data available, why not make games that take advantage of it? By creating a gaming framework oriented around the use of data would be the first step in creating an environment for innovating data science, machine learning, and gaming. This new gaming framework would bring all three industries together, data science, AI, and gaming, and would give people the opportunity to experience and get involved in AI development and data science in a whole new way. With such a great need for data scientists, creating a fun interactive way for those interested in and actively involved in the field would be tremendous in propelling data science and AI development forward. Another benefit of easily accessible data is the time saved. By not spending as much time and energy collecting data, data scientists can spend more time innovating and trying out new theories.