When deploying highly impactful large AI models, such as generative models, in organizations, a critical success factor is the quality of training datasets. The availability of, or access to, domain-specific data to train specialized models is hampered by data privacy and security concerns and accompanying regulations.

Techniques like federated learning, deployed in concert with encryption technologies, are already enabling models to be trained from differing data sources without revealing data points or exposing data to risk. This session will discuss what privacy issues exist for generative AI, and how PETs can enable the conditions that fully unleash the true potential of AI in enterprises. For the first time, data scientists who want to train models with industry- or company-specific data, will be able to share data with customers, peers, and even competitors – the next step for generative AI is data partnerships.

Collaborating and exchanging data can optimize productivity and reveal unexplored prospects. However, information is often isolated and siloed with limited access to protect it from compromise and to comply with differing regulatory requirements. Experts will share how they have increased both internal and external data collaboration, the lessons they’ve learned, and the partnership opportunities being enabled by PETs.

A gathering of leading industry IP, HR, General Counsel and Private Practice will run through internal jurisdictional scenarios to give practical insights into how to protect trade secrets across international jurisdictions.

Scenarios include:

• The interplay between the jurisdictional challenge in trade secrets. Examine legal risks associated with onboarding/offboarding employees
• Due diligence requirement for vendors and employees
• Co-workers sharing sensitive information? Internal procedures?
• What is your first reaction if you found out trade secret has been leaked.

Internationally renowned defence counsel provides practical insights into trade secret IP issues when facing threats of litigation. Focusing on successful strategy and avoiding costly litigation costs.

• The role of defence counsel in trade secret litigation
• Legal framework surrounding trade secret litigation
• Strategies that a defence counsel can use to protect trade secrets, such as conducting thorough investigations and developing strong legal arguments
• The types of damages that may be awarded in trade secret litigation and how to minimize their impact

The two biggest questions you need to ask yourself concerning prosecution are how does a trade secret case start? And what are the practical aspects of the law that need to be considered? In the following session, explore discussions into the consideration of practical aspects of the current European and US Legal Framework for trade secrets.

• Established cost-efficient strategy for pursuing trade secret litigation: Local vs International Court
• Understand when motions for dismissal can occur?
• Determine grounds for preliminary injunction relief
• Depositions requirements
• When does criminal prosecution start in trial?
• Analyse requirements for ex-parte discovery & ex-parte evidence
• How to conduct the right form of due diligence and risk mitigation before ending in litigation
• Determine investigation potential for DOJ involvement and extension of crossborder
enforcement
• Examine the pros/cons of out of court settlement

The use of AI, including machine learning (ML), is turbo-charging the need for active and effective trade secrets management. The situation is highly nuanced, but traditional IP rights, including patents and copyright, were not designed for data or AI techniques and outputs, especially ML. Trade secrets have emerged as the default de facto protection.

• Examine the contribution of trade secret protection towards the protection of data
• Determine how far can trade secret protection contribute towards AI/ML techniques
• Analyse whether trade secret is an enhanced form of IP protection

A) Automotive: Pascal van Troost, Global Intellectual Property Leader, Punch Powertrain

B) Life Sciences: Bart Goddyn, General Counsel & Company Secretary, Mnemo Therapeutics

C) Consumer 

D) AI and Technology 

E) Energy/Green Energy: Preben Kjær Kristensen, Senior Lead IPR Specialist, Ørsted

F) Manufacturing: Mark Chadwick, Head of IP, Meatable