AI can write so you and I must return to language
As writers we can now focus on craft and accumulated meaning, and leave the busywork to the machines.
Making meaning from feelings exists to examine what lies at the intersection of people, technology, and culture. And here we are amid, presumably, a generative AI-induced tectonic shift on all three planes. A tsunami of questions rushes towards us, so let us not run but turn and face the tide with our chin up and chest puffed. If generative AI can write, what is it to write?
The Western canon, which has opened itself up to writers from Asia and Africa, comprises of a literary canon, philosophy, music, and works of art. These cultural products are the bedrock of Western civilization. In Asia there are such canonical texts, naturally less cohesive or formalized, a few examples being the Bhagavadgītā, Quran, and writings by Confucius. To write well is to tell truths about society, for society. It is to critically examine the conditions of life, for the majority, and produce new human knowledge. This task is a complex, decentralized responsibility that I am not sure can or should ever be automated (at The Wikimedia Foundation we have begun to talk about machine-enabled knowledge documentation, and I am quite curious about this effort and eager to follow its progress).
And therein lies the new beginning. Artificial intelligence has no consciousness, intention, or emotion. It cannot produce knowledge, it simulates knowledge.1 It generates text when given a query, and is moreso the next evolution of the search engine than a replacement for human creativity. We humans journal, story-tell, sing, and blog. We pen speeches and policies, news articles and slogans. We scribe religious texts and philosophical treatise, textbooks and research papers. We publish novels and books of poems. We send letters, emails, and text messages. We have written for thousands of years, and we will continue to write. To write is to make meaning from feelings (this is not to negate the importance of oral tradition, a practice that is alive and well in my family. What I am calling “writing” is a reference to words, written or spoken).
What differentiates us from machines is our capacity to know through inquiry. We gain knowledge in layers. We learn the fundamentals of a subject as a first layer, on top of which we layer understanding. The continual loop of testing theories and learning from experiments becomes knowledge in time. This sustained, in-depth interrogation of information is digested while writing.
As writers we can now focus on craft and accumulated meaning, and leave the busywork to the machines. Let us revisit our fundamentals and find where language bends. Let us invent new language! Now is the time to develop organic creative processes. To absorb many worlds and spin new ones. To write from the heart, about the heart. We will continue to try and understand people as they are today and fill gaps in society with emotion and color. We are here to evoke sensation, and what a worthy quest we have found!
This bit of writing is inspired by my colleague Robin who shared an article with me by iA called “The end of writing”.
*I am aware that my essay is largely ahistorical, but I wanted to publish some early thoughts on the subject. I will, however, be doing some research and sharing a historicized critique of generative AI.
I love the idea of a writer dealing with “accumulated meaning,” it makes so much sense, I’ve never thought about it like that! Thank you for reminding me why I love to write so much!
It's becoming clear that with all the brain and consciousness theories out there, the proof will be in the pudding. By this I mean, can any particular theory be used to create a human adult level conscious machine. My bet is on the late Gerald Edelman's Extended Theory of Neuronal Group Selection. The lead group in robotics based on this theory is the Neurorobotics Lab at UC at Irvine. Dr. Edelman distinguished between primary consciousness, which came first in evolution, and that humans share with other conscious animals, and higher order consciousness, which came to only humans with the acquisition of language. A machine with primary consciousness will probably have to come first.
What I find special about the TNGS is the Darwin series of automata created at the Neurosciences Institute by Dr. Edelman and his colleagues in the 1990's and 2000's. These machines perform in the real world, not in a restricted simulated world, and display convincing physical behavior indicative of higher psychological functions necessary for consciousness, such as perceptual categorization, memory, and learning. They are based on realistic models of the parts of the biological brain that the theory claims subserve these functions. The extended TNGS allows for the emergence of consciousness based only on further evolutionary development of the brain areas responsible for these functions, in a parsimonious way. No other research I've encountered is anywhere near as convincing.
I post because on almost every video and article about the brain and consciousness that I encounter, the attitude seems to be that we still know next to nothing about how the brain and consciousness work; that there's lots of data but no unifying theory. I believe the extended TNGS is that theory. My motivation is to keep that theory in front of the public. And obviously, I consider it the route to a truly conscious machine, primary and higher-order.
My advice to people who want to create a conscious machine is to seriously ground themselves in the extended TNGS and the Darwin automata first, and proceed from there, by applying to Jeff Krichmar's lab at UC Irvine, possibly. Dr. Edelman's roadmap to a conscious machine is at https://arxiv.org/abs/2105.10461