What Makes Us Human?
By Charles T. Rubin, Public Discourse:
At the moment, large language models are nothing like us, however easy it is for us to anthropomorphize their outputs. But as AIs develop, it will become increasingly necessary to ask: How much do we want them to become like us? Answering that question will certainly require human wisdom.
In What Makes Us Human, the artificial intelligence program GPT-3, along with Iain Thomas and Jasmine Wang, has written a fascinating book at the somewhat fluid intersection of self-help and wisdom literature. Given the capacity of computers today and the cleverness of their programmers, I don’t think we have to be surprised that such a book is possible; I will return to this point shortly. But I would also suggest that the book’s subtitle, An Artificial Intelligence Answers Life’s Biggest Questions, does not tell the whole story. It is not hard to answer the biggest questions. It is hard to provide good answers to the biggest questions. To evaluate the quality of the answers provided by GPT-3, it is useful to have a sense of where they came from.
An AI “Written” Text
GPT-3 is a large language model form of artificial intelligence, which means (more or less) that it consumes vast quantities of text data and derives from it multi-dimensional statistical associations among words. For instance, when asked to complete the phrase “Merry . . .” Gpt-3 replies “Merry Christmas,” not because it knows anything of Christmas or merriment, but simply because those words stand in a close statistical relationship in its database. When asked to complete the phrase without using the word Christmas, it comes up with “Merry holidays” and then “Merry festivities.” One of the key features of this kind of program is that its internal operations are almost entirely opaque; it is extremely difficult to determine how the program reaches the decisions that produce the outputs that it does.
What Makes Us Human was produced by a GPT-3 that had been “prompted” “with selected excerpts [elsewhere characterized as “a few select examples”] from major religious and philosophical texts that have formed the basis of human belief and philosophy, such as the Bible, the Torah [sic], the Tao Te Ching, Meditations by Marcus Aurelius, the Koran, the Egyptian Book of the Dead, Man’s Search for Meaning by Victor Frankl, the poetry of Rumi, the lyrics of Leonard Cohen, and more.” (A bibliography would have been useful.) Then the two humans would ask some big question (“What is love?” “What is true power?”) and subsequently ask the model to “elaborate or build on” “the most profound responses.” The book is the result of “continuing to ask questions after first prompting GPT-3 with a pattern of questions and answers based on and inspired by existing historical texts” representing “the amalgamation of some of mankind’s greatest philosophical and spiritual works.”
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