Overview
During this webinar, Shawn Helms and Jason Krieser explored the rapidly evolving world of artificial intelligence (AI)—its transformative power, notable implications for businesses and likely challenges for those seeking to harness its potential.
Top takeaways included:
1. The Rise of Generative AI: Unlike traditional AI, which relies on predefined rules, generative AI learns patterns and generates outputs based on models and training data. This shift in methodology enables machines to create high-quality text, images and other content without specific programming. It also enhances efficiency and consistency in various fields, such as pathology, where AI can quickly review thousands of slides and provide pathologists with faster results and higher diagnostic accuracy.
2. The Evolution of AI Technology: AI is constantly evolving, and many tech giants are investing heavily in AI research and development. A current trend? Companies with large datasets are partnering with providers of AI models to analyze the datasets and make predictions based on said data. Companies that embrace AI technology can gain a compettive edge.
3. Generative AI Risks: Generative AI introduces specific risks, including:
- Incorrect results due to small sample sizes, discrimination based on irrelevant factors and data manipulated by hackers
- Disclosure of confidential information if employees inadvertently provide software source code or marketing research to generative AI products
- Hallucinations, where generative AI provides confident but wrong answers. For example, when Shawn asked ChatGPT to name famous William Jewell College alumni, it named Walt Disney, Robert Gates and Harry Truman. None of them went to school there.
4. How to Manage Generative AI: Although AI presents risks, don’t prevent your business from using it. To balance AI’s potential with safeguarding against negative outcomes, implement generative AI use policies, governance frameworks and standard practices for third-party contracts.
5. The IP and AI Crossover: The question of IP ownership in AI is complex and evolving. Courts have recently ruled that AI output cannot be protected by copyrights or patents unless it involves significant human interaction. Whether a particular level of human interaction is enough has yet to be determined. In agreements involving AI, setting rules for ownership of various IP categories is crucial, especially when it comes to customer data, AI output and improvements to the AI engine. Clearly allocating IP ownership and protection—when available—prevents disputes, fosters innovation and protects business outcomes.
To register for upcoming webinars in the AI and the Next Frontier series, visit the AI Law Center.
