作者

Erik Steiner

高级律师

Read More
作者

Erik Steiner

高级律师

Read More

2023年5月9日

AI and games – 1 / 6 观点

AI and video games: getting the balance right

  • Briefing

The video games industry has been using artificial intelligence for decades. The first chess machines capable of playing chess or simplified chess-like games entered the market as far back as the 1950s in the tube computer age.  By 1997, chess engines running on super-computers or specialised hardware were capable of defeating even the best human players. Although the use of AI is not new to the video games industry, the recent rise of new technologies like Chat GPT or Stable Diffusion, may change the way games are designed, developed, and experienced.

The low entry barrier makes generative AI models like Chat GPT easily accessible, as with simple prompts, pictures and even computer code can be drafted within seconds. But as we all know “with great power comes great responsibility” or at least a lot of associated legal issues.

What is generative AI?

Generative AI works by learning patterns and structures from a huge volume of data sets/content. This data typically consists of text, images, or other forms of media such as music or computer code. The training data for an AI model can be obtained from various sources, such as publicly available datasets like Common Crawl, by scraping the web or mining open source repositories. Once the AI tool is trained to recognise certain patterns it can generate output based on a text input (prompt). In the video games industry, there are many potential use cases, reaching from art, music, and computer code to level design, pitches and marketing materials.

Generative AI can improve in-game player experience by creating lifelike situations and offering a more immersive experience.   It's already being used in a wide range of areas including:

  • Non-player characters (NPCs): in connection with NPCs, game AI has been used since the early days of video games. NPCs are characters in the game who act intelligently as if they were controlled by human players. These behaviours are typically determined by algorithms. With generative AI, the character can interact with players in a more realistic and dynamic way, adding immersion or challenge to the game.
  • Content generation: AI can figure out the ability and emotional state of the player and tailor the game accordingly. This could even involve dynamic game difficulty balancing in which the game is adjusted in real-time, or generation of new content such as enemies, items and levels.
  • Accessibility: by creating virtual assistants or automatically creating personalised elements for individual players’ needs, video games can be more inclusive for players from different linguistic backgrounds or for gamers with disabilities. 
  • Fraud detection: AI can be used to detect cheating or hacking. This can help maintain a fair and enjoyable experience for the player base. 

With the rise of use-cases come a variety of legal issues. These are made all the more complicated as video games are multi-jurisdictional products and each jurisdiction has its own laws and courts. Here are some key issues (mostly from an Austrian and EU perspective). These are discussed in more detail in our Interface edition focusing on AI and video games.

Legal issues with generative AI

  • Can you use training data for your AI model?
    When using data sets for training the AI model, the content is often copyrighted material like game art, characters, computer code, music, etc. The risk is that the use could constitute a copyright infringement. Read more.
  • What if the AI uses open source? 
    Using training data that is pulled from open source software or data repositories could lead to legal problems. A challenge with open source content is that even though the materials are usable without royalties, they are typically subject to licence terms. In certain cases, any derivative must retain the copyright notice, attribution to the author or identifying modifications. Currently, hardly any AI tools comply with these requirements. Read more.
  • Is the output copyrightable?
    Under the Austrian Copyright Act, as in many other jurisdictions, copyrightable work must be an intellectual creation of human beings. Is the creation of a prompt sufficient to satisfy this condition? If a developer uses an AI tool but also exercises substantial human involvement in the creative process, it will likely be protectable by copyright. However, it is not clear where this line would be drawn. Read more.
  • Who is liable for infringing copyright created by AI?
    Where AI models are trained on copyrightable works, the AI-created work may be so similar to the training materials that it constitutes a derivative work or even a copy. The providers of AI tools tend to try and draft their terms of service in such a way that they shift any liability regarding the generated output to users. 
  • Is there a problem with data protection? 
    AI tools can also raise privacy concerns. Where personal data is used to train the model, or where a model generates personal data (for example an AI tool which tracks player movement), privacy issues may arise, certainly in the EU and UK where the GDPR and UK GDPR respectively will apply. Read more.
  • Is it possible to infringe competition law and consumer protection laws through AI tools? 
    As AI-driven games become more prevalent, issues such as misleading or aggressive business practices and in-game advertising, as well as unauthorised use of third-party intellectual property may create competition and/or consumer protection issues.

The potential legal consequences of infringement in addition to the typical fines for violations of data protection laws are far reaching. The affected parties can potentially claim a range of remedies, including 'cease and desist' orders, removal of the video game from the stores and damages. This is in addition to reputational damage.

Keeping on top of developments

Games developers and publishers looking to use AI-driven tools in their games need to consider a wide range of legal issues which may not always have clear answers given the disruptive nature of the technology. The lack of clarity is exacerbated by the fact that the EU and other countries are working on how best to regulate AI but there is a lack of global consensus. While AI models can be used to enhance gameplay and user experience, they should always be used carefully.

Read more about AI and video games in our Interface edition.

本系列内容

游戏业务团队

AI and video games: getting the balance right

Erik Steiner looks at the opportunities in the games industry offered by AI, and at how to manage the associated legal risks.

2023年5月9日

作者 Erik Steiner

技术、媒体与通信 (TMC)

A practical guide to AI ethics and accountability in video games

Desideria-Alexia Pohl looks at how to help ensure ethical use of AI in games.

2023年7月31日

技术、媒体与通信 (TMC)

What games businesses need to consider when drafting a generative AI acceptable use policy

Martijn Loth highlights the top ten considerations to help games businesses mitigate risks associated with using generative AI when developing video games.

2023年7月31日

作者 Martijn Loth

技术、媒体与通信 (TMC)

Generative AI in gaming: immense potential… with some unanswered legal questions

Our international team looks at copyright issues around the use of generative AI in video games.

2023年7月31日

作者 作者

技术、媒体与通信 (TMC)

AI, data and gaming

Laura Craig and Miles Harmsworth look at the use of personal data in AI tools used by the video games sector, and at the evolving regulatory framework.

2023年7月31日

作者 Laura Craig, Miles Harmsworth

技术、媒体与通信 (TMC)

Open source generative AI in games

Marie Keup and Lucas de Groot look at how games developers and publishers can ensure they don't run into issues when using open source generative AI in their games.

2023年7月31日

作者 Marie Keup, Lucas de Groot

Call To Action Arrow Image

Latest insights in your inbox

Subscribe to newsletters on topics relevant to you.

Subscribe
Subscribe