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Author Vauhini Vara could write about anything. Except the death of her sister.
It was the “one big event in [her] life for which [she] could never find words.”
But then Vara heard about OpenAI’s early artificial intelligence efforts. She seemed to have found an alluring potential solution. Could generative AI help her overcome her mental obstacles? Could AI help her to express something so personal?
Months later, in partnership with AI, Vara at last crafted an essay about her sister’s cancer. The end product was “nuanced and profound.” In fact, GPT-3 produced lines like this:
“We were driving home from Clarke Beach, and we were stopped at a red light, and she took my hand and held it. This is the hand she held: the hand I write with, the hand I am writing this with.”
This essay, Vara marvels, “was better received, by far, than anything else I’d ever written.” Best American Essays included her piece in its 2022 edition. And This American Life adapted her story for their podcast.
Then AI evolved.
Joan Didion once said, “I write entirely to find out what I’m thinking, what I’m looking at, what I see and what it means. What I want and what I fear.”
Likewise, Vauhini Vara views writing as an attempt to clarify what the world is like from where she stands in it.
But she also had become comfortable working with AI as part of this process. She was willing, when necessary, to outsource “the most essential labor of a writer.” She was willing to ask for help “coming up with the right words.”
In later writing projects, though, AI struggled to generate expressive sentences for her. And other writers had similar experiences. New York Times book critic Dwight Garner, for example, described an AI-generated novel, Death of an Author, as having “the crabwise gait of a Wikipedia entry.”
Was generative AI no longer a bridge to better self-expression?
Sil Hamilton is an AI researcher at McGill University in Montreal. He doesn’t believe that OpenAI ever set such a goal. Instead, OpenAI wants “the [AI] model to sound very corporate, very safe, very AP English.” Joanne Jang, an OpenAI project manager seems to agree. An effective chatbot’s purpose, she notes, is “to follow instructions.”
As a result, Vara’s opinion of AI now looks different. She explains:
My “definition of writing couldn’t be more different from the way AI produces language: by sucking up billions of words from the internet and spitting out an imitation. Nothing about that process reflects an attempt at articulating an individual perspective. And while people sometimes romantically describe AI as containing the entirety of human consciousness because of the quantity of text it inhales, even that isn’t true; the text used to train AI represents only a narrow slice of the internet…”
Generative AI may have had a brief run as a tool for communicating what we think, feel, and desire. But at this point, Vara argues, a much more limited resource has emerged. One that has become failingly polite, predictable, and inoffensive.
Writing has a lot in common with the role that money plays in our lives.
Through many of our financial decisions, we “find out what we’re thinking, looking at, what we see and what it means. What we want and what we fear.”
But we rarely acknowledge this dynamic. It’s a daunting thought, right?
Companies will increasingly add generative AI to the personal finance software we use. And that may feel like a benefit, an alluring solution to our financial challenges.
For example, we may want to outsource the task of evaluating our financial tradeoffs. We may be eager to ask for guidance coming up with the “right” choices.
As Vara learned, though, generative AI ultimately just wants to follow instructions. So we put ourselves at risk for regret and disappointment when we expect more. We put ourselves at risk for living financial lives that are too polite, predictable, and inoffensive.
If companies design AI to “suck up billions of words” from financial websites, then we’ll always hear that we should:
AI output like this would be predictable, inoffensive. And as a result, the advice won’t express anything personal about or unique to us. We may have very valid reasons for wanting to save aggressively for college. Or we may have no interest in the time commitment and stress that comes with owning a rental property.
But AI isn’t designed to express preferences.
It’s hard for anyone to figure out how and when we should actually use the money we’ve saved. Yet, a close partnership with AI may not create the bridge to clarity that we seek. AI will serve as a tremendous resource in other ways. It’s on us, though, to continue trying to articulate our individual perspective on money and the life we want to lead.
“Lately,” Vara writes, “I’ve sometimes turned to ChatGPT for research. But I’ve stopped having it generate prose to stand in for my own.”
“If my writing is an expression of my particular consciousness, I’m the only one capable of it. This applies, to be clear, to GPT-3’s line about holding hands with my sister. In real life, she and I were never so sentimental. That’s precisely why I kept writing over the AI’s words with my own: The essay is equally about what AI promises us and how it falls short.”
Great financial decisions aren’t always polite. They aren’t always predictable. And they aren’t always inoffensive.
We shouldn’t let AI instruct us otherwise.
Hi, I’m Kevin. I’m a financial advisor in Washington, DC. I’m also the founder of Illumint, an independent financial planning company in the District that specializes in financial planning for Millennials like you. I empower our generation with the confidence to invest an inheritance, financial gift, or extra savings. If you’re new to Financially Well, welcome – you now have access to the leading finance podcast for Millennials. I encourage you to read, watch, or listen to the ideas I’ve shared about making your money work for you. And then when you’re ready, please send me your thoughts & questions!
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