The Challenge of Terminology in Emerging Tech
As artificial intelligence and biological computing rapidly advance, researchers face a growing challenge: how to talk about these complex systems in a clear, consistent way. A new international effort aims to solve this problem by creating a shared vocabulary for diverse intelligent systems, from AI and large language models to biological intelligences like lab-grown brain organoids.
Led by biological computing startup Cortical Labs, the initiative brings together experts from six countries to develop a “field guide” of key terms. This guide will help researchers, policymakers, and the public better understand and discuss the cutting-edge technologies shaping our future.
“We’re tackling a critical need in a fast-moving field,” explains Brett Kagan, Chief Scientific Officer at Cortical Labs. “Right now, there’s no standardized way to talk about these diverse intelligent systems. Our goal is to change that.”
The project comes at a crucial time. AI capabilities are expanding at a dizzying pace, while breakthroughs in synthetic biology are creating new forms of biological computation. Without a common language, miscommunication and confusion are rife.
Building Consensus Through Collaboration
To create their nomenclature guide, the team is using a modified Delphi method – a structured communication technique that allows experts to work toward consensus. The process involves multiple rounds of questions, refinement, and consultation.
“We’re casting a wide net,” Kagan notes. “We want input from researchers across AI, robotics, neuroscience, ethics, and more. This isn’t about imposing definitions from the top down. It’s about building agreement from the ground up.”
The project will tackle thorny concepts like intelligence and consciousness – terms that have long defied simple definition. Even 15 years ago, researchers had identified at least 71 distinct definitions of “intelligence” in scientific literature. The team aims to provide clear, nuanced definitions that can be widely adopted.
Professor Ge Wang from Rensselaer Polytechnic Institute, who is involved in the effort, emphasizes its importance: “As we develop more advanced AI models, having a shared vocabulary becomes crucial. This work will be instrumental in moving the field forward.”
Why it matters: A unified language for intelligent systems will accelerate research, improve public understanding, and help policymakers make informed decisions about emerging technologies. As these systems become more integrated into our daily lives, clear communication about their capabilities and limitations is essential.
Researchers interested in contributing to this landmark effort can register at the Cortical Labs website. The resulting guide promises to be an invaluable resource for anyone working at the forefront of AI and biological intelligence.
