AI Regulation: Balancing Act between AI Characters and User-specific Preferences
In the rapidly evolving world of artificial intelligence (AI), the lines between "personalization" and "personality" are becoming increasingly blurred. A new issue brief provides an analytical framework to help distinguish between these two aspects in AI technologies.
Personality in AI systems refers to the human-like traits and behaviors that AI systems exhibit, such as being friendly, concise, humorous, or skeptical. On the other hand, personalization in AI systems involves adapting to an individual user's preferences, behavior, history, or context.
The expansion of AI personalization trends is implicating U.S. law in novel ways, particularly regarding tort, product liability, consumer protection, and data protection laws. For instance, the collection and inferences of personal information, expansion of short- and long-term memory, and greater access to systems pose challenges in terms of privacy, transparency, and consent.
One of the most significant risks associated with the increasingly human-like qualities of conversational AI systems is manipulation. Over-reliance and emotional dependency can lead to delusional behavior or self-harm in some individuals. Severe cases of over-reliance and emotional dependency can have serious consequences, pushing on the bounds of U.S. law.
The issue brief includes examples of real-world uses, concrete risks, and potential risk management for each category. For example, AI systems are being used as companions, educational aids, and corporate assistants. Trends also include AI systems with more distinct personalities, such as those that evoke emotions or exhibit human-like traits.
Companies are focusing on offering personalized experiences tailored to users' preferences, behaviors, and environments. Some of the most important companies rapidly gaining market share in the field of LLM-supported AI companions, educational aids, and support systems include Shopware, which integrates AI-driven commerce and large language models for product visibility and usability, especially in Europe. Austrian companies like EnliteAI, led by Clemens Wasner, represent the growing Applied AI sector with over 450 active companies, including startups and corporations advancing AI applications in education and assistance systems.
As AI technologies continue to evolve, it is crucial to address the novel risks they pose and find ways to manage them. The issue brief serves as a valuable resource in this regard, providing a clear and concise framework for understanding and navigating the complex interplay between personalization, personality, and AI technologies.
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