CONCERNS OF CHEATING AND PLAGIARISM
Babcock explained that all GenAI models are producing derivative outputs, meaning their outputs are based on what data they are fed: there will never be any purely original content generated from them. But the outputs are startlingly accurate, realistic and often seen as coming from a human–whether it be a speech, paper assignment or piece of visual design imitating human artwork.
While tools exist to detect AI-generated content that may be submitted as part of class assignments, they are–just like the GenAI producing the content–not infallible. This means that students may be able dodge plagiarism detection by training an AI model with their writing to teach it tone and style that would reflect their own writing; or, a student may simply enter a prompt “write this article as a 10th grade student.”
Still, the concern goes with equal measure of opportunity to make class time more efficient for teachers–and allow students to experiment and use AI as a tool, instead of being seen as a cheating shortcut.
“In the classroom, teachers–just like mine who said we wouldn’t always have a calculator in our pocket to do long division, or to not use Wikipedia as research–educators should consider getting on board to understand how this is part of a working process that students will use in later jobs.”
INDUSTRY DISRUPTION: WILL JOBS BE LOST? WILL ART BECOME DEVALUED?
One of the big areas for mass content evaluation is with law firms. Some are using AI to digest and analyze court cases. “Go in and find historical parallels of this case and tell us how likely we are to win this case,” Babcock offered. But ChatGPT was found to make up cases in briefs that were filed in court. This is an instance of industry disruption that needs tweaking: lawyers can get valuable insight to their own perspectives and presumptions about their case, but probably shouldn’t rely on AI to write their brief that would go before a judge.
As for the large-scale disruption that economists wrestled with before–what about factory workers? Artists? Writers? This was a concern with the rise of automation and robots, and still people work in factories and provide crucial jobs across all industries. The key is moving forward with the technology being used to be productive; not to replace human perspective, expertise or intuition.
The example of vaccine manufacturers using AI to fast-track the development of dozens of vaccines was one of the most compelling examples of the technology being used that would take decades otherwise. Still, the concern for artists and creatives, Babcock said, could be seen as very real concern tempered by the reality that we want and expect human-produced art and writing because it is authentic and resonates in ways that AI-generated content would not; and that artists can use it themselves to touch up their own work without starting over. And not all disruption displaces personal preference for products produced by humans.
“I have four Kindles at home and I still prefer to read a paper book."
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