How accurate are artificial intelligence models like ChatGPT, Grok, and Bard in describing intelligent design theory? Can large language models go beyond the biases in sources like Wikipedia to help build a more balanced discussion around intelligent design theory? In a new episode of ID the Future, I had a conversation with Dr. William Dembski, a mathematician and philosopher, exploring the relationship between artificial intelligence and intelligent design (ID). In recent years, Dr. Dembski has tested large language models (LLMs) to determine if these models can accurately and fairly discuss and present the arguments and concepts of intelligent design theory. Here, he shares his findings from investigating these complex algorithms through various methods.
In the first part, Dembski first talks about his educational background in mathematics and philosophy, and how these disciplines laid the foundation for his research on artificial intelligence. “I’ve been interested in artificial intelligence since at least the early 1980s,” he mentions, recalling the history of the field that first sparked his curiosity. When talking about today’s models, he is both impressed and cautious: “They can do some amazing things, but I think they also have their shortcomings.”
Sharp and In-depth Questions
So, how do artificial intelligence systems perform when a mathematician and philosopher asks sharp, persistent questions and doesn’t easily let go? Dembski explains that in one conversation, he first asked the AI about the Search for Extraterrestrial Intelligence (SETI) program. SETI is a long-running project that has similarities to intelligent design theory in its search for signs of intelligence in nature. He wanted to see if the AI would draw a connection between SETI and intelligent design theory, and acknowledge the scientific credibility of intelligent design reasoning. After explicitly establishing “technological features” as a criterion in SETI research, would the AI extend this logic to suggest that such technological features might also exist in life? Dembski provides the answer.
Dembski believes that these AI models can be most valuable when we act as diligent researchers and qualified conversation partners. This means carefully crafting prompts and patiently seeing the dialogue through to the end. “From my experience with these large language models, they do ‘listen’ to you,” he says. “When you frame a question, they take it into account.” The tokens generated by our prompts influence the AI’s responses, so carefully constructing the path of dialogue with AI can lead to promising results. But in an era of instant information, do we have the patience to adopt this approach? On this point, Dembski remains optimistic, believing that through conscious engagement, AI has the potential to become a more nuanced tool for exploring complex ideas like intelligent design theory.
It should be noted that intelligent design theory is not a scientifically recognized theory by the mainstream scientific community; the mainstream scientific community generally holds that the theory of evolution by natural selection is the scientific theory explaining the diversity of life. The above translation is only a linguistic conversion and does not represent approval of the content.
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