24 Jan 2024
10 mins read
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Artificial Intelligence is here to stay. It can be an incredibly powerful tool when used properly and can drastically speed up a variety of workflows. With a games industry under pressure, finding ways to speed up production is a tantalising prospect. But what are the risks, and how can you mitigate them? This is a list of some of the most exciting potential applications for AI in the world of game development, and we will address the potential risks and how to mitigate these if you wanted to go ahead with any.

 

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This is the one that most people think of first when considering AI. Using it to generate and assist in your content for you, as this can save a huge amount of time.

 

The risk here lies predominantly in IP infringement, and ownership.

 

If you get AI to create content (this could be artwork, code, audio, lore, the list goes on…) you run the risk of the AI creating something that could be accused of infringing on the IP rights of another party. It is difficult to determine where many of the AI tools are getting their data from, and they could be regurgitating content from anywhere. The below example is fairly obvious, and these are getting harder to detect, but any work you produce (whether you got it from AI or not) will still be subject to intellectual property scrutiny, and you may find yourself having to defend that you were the original creator, which in the case of AI you were not.

 

Image Credit: Hackaday

 

Getty Images Is Suing An AI Image Generator For Using Its Images:

 

https://hackaday.com/2023/02/09/getty-images-is-suing-an-ai-image-generator-for-using-its-images/

 

The other big issue is around ownership.

 

This is a fairly big topic to unpack and is a developing legal landscape, but broadly the USA requires “human authorship”, and you may find yourself not actually owning copyright on key elements of your game if you used AI to assist. This can make it difficult to enforce protection from copycats, plus if you were considering selling the IP or the business, it could make a sale difficult if you couldn’t prove complete ownership of the work(s) you were selling.

 

Several countries, such as Australia, Germany, Brazil, Colombia, Mexico, and Spain, adopt a similar stance to the United States, mandating human authorship for copyright protection.

 

However, other jurisdictions like the UK, Ireland, Hong Kong, India, New Zealand, and South Africa explicitly acknowledge copyright protection for computer-generated works through statutory provisions.

 

 

☝ Prompt: “create an image of someone creating something using an AI system, but not actually owning the copyright, and they are therefore sad because they can’t sell it”

 

How to mitigate the risks:

 

 
  • You can use AI as a starting point, or for concept art and storyboarding, but if you want to put it intro production you should add your own touches to it as much as possible.
  • Save your original editor files and show the journey to a transformative work to prove authorship and therefore ownership.
  • Get a lawyer to run a trademark search before releasing anything (this can add cost).
  • Consider getting insurance that includes IP infringement defence.
  • If you outsource any of these functions, consider including in the contract a warranty that AI was not used to deliver content to you.
  • Check whether your country recognises ownership from AI (bear in mind even if you owned the work you would still liable for copyright infringement if the AI spits out something infringing).

Data collection and player analysis and Quality Assurance

 

AI can automate the collection of player data from diverse sources like in-game interactions, social media, and forums. It can also analyse data to uncover valuable insights, from player behaviour patterns to trends that inform game design, marketing tactics, and monetization strategies.

 

There are a couple of inherent risks to this approach.

 

AI-based testing tools may produce false positives and AI-generated test results would need some sort of validation refinement. AI testing tools also may have limitations in detecting certain types of defects or assessing subjective aspects of gameplay quality. For many things a qualified human QA is simply better.

 

Furthermore, there are potentially Data Privacy Concerns.

 

Collecting and analyzing player data, particularly with regard to personally identifiable information (PII) could cause issues. Companies must adhere to data protection regulations and implement robust security measures to safeguard player data, which could be further complicated if the data goes “offsite” to a 3rd party AI tool. This can be a complicated area of law (especially across multiple jurisdictions), but there are heavy penalties for getting it wrong.

 

Fortnite Video Game Maker Epic Games to Pay More Than Half a Billion Dollars over FTC Allegations of Privacy Violations and Unwanted Charges:

 

https://www.ftc.gov/news-events/news/press-releases/2022/12/fortnite-video-game-maker-epic-games-pay-more-half-billion-dollars-over-ftc-allegations

 

 

☝ Prompt: “a robot testing a video game, and collecting personal information without people’s knowledge”

 

How to mitigate the risks:

 
  • Supplement automated testing with manual testing and user feedback to ensure more comprehensive QA coverage.
  • Ensure transparency, obtaining informed consent, and avoid discriminatory practices wherever possible.
  • Familiarise yourself with the data privacy laws where you operate and engage with a lawyer who understands data privacy to help you get it right (it can be complicated!).
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