WIPO - generative-ai-navigating-intellectual-property.pdf

https://www.wipo.int/edocs/pubdocs/en/wipo-pub-rn2024-8-en-generative-ai-navigating-intellectual-property.pdf

<aside> 💡 AI Generated Summary

The development of generative AI can be an extremely costly endeavor, often reaching tens of millions of US dollars. Most businesses and organizations are opting to adopt third-party generative AI tools or fine-tuning such models using their own data. However, there are several general issues and business risks to consider.

Firstly, determining the optimal use cases for generative AI can be challenging as this technology is capable of performing many tasks, and the best uses are still evolving and will vary across different businesses and organizations. Secondly, there can be considerable differences in the contractual terms on which developers are licensing their AI tools. This includes approaches to trade secrets and other confidential information, the ownership of outputs, the availability of indemnities, and obligations on users to mitigate risks through the implementation of staff monitoring and training.

Training data presents another issue. Some generative AI tools have been trained using materials scraped from the internet, including copyright works, personal information, biometric data, and harmful and illegal content. There is ongoing litigation over whether the scraping, downloading, and processing of materials, the trained AI models, and their outputs involve breaches of IP, privacy, and contract.

Output issues are also a risk. Generative AI may produce inappropriate or illegal outputs, including incorrect information, IP infringements, deepfakes, personal information, defamatory allegations, and discriminatory, biased, and harmful content.

Generative AI has many IP touch points and uncertainties. While complete mitigation of these IP risks is impossible, the following considerations may be useful for businesses and organizations navigating IP considerations in this evolving technical field.

Businesses and organizations using generative AI tools may inadvertently give away trade secrets or waive confidentiality in commercially sensitive information if such information is used for training or prompting AI tools. They should consider putting in place a combination of technical, legal, and practical safeguards to prevent this.

The regulatory landscape is also changing, with governments and regulators considering new laws, regulations, policies, and guidelines for generative AI. These may impose requirements on businesses and organizations using generative AI.

Many generative AI tools are trained on enormous quantities of items protected by IP, leading to legal disputes alleging that the scraping and use of these works to train AI, the trained AI models, and their outputs are IP infringements. Businesses and organizations should consider mitigating the risk by using IP compliant tools, seeking indemnities where possible, vetting datasets, and implementing technical and practical measures to reduce the likelihood of infringement.

Open-source obligations are another potential risk. Code generated by AI might be subject to open-source obligations, which grant certain rights and freedoms to use, modify, and distribute the software, but also come with obligations that users must adhere to.

Generative AI also has the potential to mimic the likeness or voice of specific people, with some tools explicitly designed for this purpose. Unauthorized use or imitation of someone’s voice or likeness may result in infringement of IP or other rights.

The existence and ownership of IP rights in generative AI outputs is unclear. Businesses and organizations should seek contractual clarity over ownership and consider using generative AI only in cases where IP ownership in the outputs is not crucial for their business model.

In conclusion, there are many measures that businesses and organizations can use to foster responsible and legally compliant use of generative AI. These include implementing staff policies and training, monitoring case law and regulations for changes, maintaining records, reviewing terms and conditions and settings on externally procured tools, and vetting datasets when training AI.

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Generative artificial intelligence (AI) tools are rapidly being adopted

by many businesses and organizations for the purpose of content

generation. Such tools represent both a substantial opportunity to

assist business operations and a significant legal risk due to current

uncertainties, including intellectual property (IP) questions.

Many organizations are seeking to put guidance in place to help their

employees mitigate these risks. While each business situation and legal

context will be unique, the following Guiding Principles and Checklist are

intended to assist organizations in understanding the IP risks, asking the

right questions, and considering potential safeguards.

Generative AI introduces numerous risks and questions. Businesses

and organizations should contemplate implementing suitable

policies and providing training to employees regarding the