The content discusses the importance of making high-level AI design decisions explicit using a binary stream system-designation approach. It emphasizes the need to consider factors beyond traditional choices like training data sets and methods, focusing on how AI interacts with the world. The author presents ten essential factors influencing AI design, such as relationship with humans, locus of control, and cross-AI learning. By examining implicit assumptions and specifying systems based on these factors, innovative AI models can be developed to solve diverse problems. The article introduces a novel taxonomy for categorizing different types of AI systems based on binary choices for each factor, resulting in 1024 possible unique systems. Examples are provided to illustrate how specific system designations are derived from these binary choices, showcasing the diversity in potential AI models that can be created. The content concludes by highlighting the importance of transparent and thoughtful decision-making in designing AI systems to maximize positive impacts on humanity and planetary health.
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by Julia Mossbr... at arxiv.org 03-15-2024
https://arxiv.org/pdf/2403.08832.pdfDeeper Inquiries