Хиймэл оюун ухааныг сэтгүүл зүйн салбарт нэвтрүүлэхдээ технологийн хэт яаруу шийдвэрээс зайлсхийж, хүний хариуцлагыг нэн тэргүүнд тавих нь чухал байна.
Сэтгүүл зүйн байгууллагууд хиймэл оюун ухааныг (AI) агуулга бүтээхэд шууд ашиглах нь алдаа гаргах, хуурамч сэтгүүлчдийг үүсгэх зэрэг эрсдэлийг дагуулж байна. Зарим хэвлэл мэдээллийн хэрэгсэл нийтлэл бичих, хэвлэн нийтлэх үйл явцыг хиймэл оюун ухаанд бүрэн шилжүүлсэн нь оновчгүй шийдвэр болсныг салбарынхан онцолж байна. Сэтгүүл зүйн аливаа бүтээгдэхүүний хариуцлагыг хүн бүрэн хүлээх ёстой бөгөөд хиймэл оюун ухаан нь зөвхөн туслах хэрэгсэл байх ёстой юм.
Технологийг сэтгүүл зүйн үйл ажиллагаанд нэвтрүүлэхдээ яарахгүйгээр, нууцаар туршиж, суралцах нь илүү үр дүнтэй гэж үздэг. Хиймэл оюун ухаан нь их хэмжээний өгөгдлөөс хэв маяг, зүй тогтол болон гаж нөлөөг олж илрүүлэхэд өндөр үр ашигтай байдаг нь сурвалжлагын ажилд ихээхэн тус дэм болж байна. Тухайлбал, санхүүгийн болон судалгааны өгөгдөлд дүн шинжилгээ хийхэд энэхүү технологи нь сэтгүүлчдэд мэдээллийн нарийн төвөгтэй сүлжээг тайлахад тусалдаг.
Чөлөөт ардчилсан нийгэмд бие даасан, найдвартай мэдээлэл нэн чухал бөгөөд сэтгүүл зүй нь энэ үүргийг гүйцэтгэдэг. Тиймээс хиймэл оюун ухааныг ашиглахдаа мэдээллийн үнэн зөв байдлыг хангах, алдааг илрүүлж засах нь сэтгүүлчийн үндсэн үүрэг хэвээр үлдэнэ. Технологийн хөгжил нь сэтгүүл зүйн мөн чанарыг орлох бус, харин сэтгүүл зүйн ажлыг илүү гүнзгийрүүлэх хэрэгсэл болох ёстой.
Дэлгэрэнгүйг эх сурвалжаас харах
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Yes. I would agree with you there.
I am sure, though I’ve never done it, that when I look at all the investigative reporting we’ve done, and this is reporting that takes months, sometimes years of work to produce a single story, that it would be very hard to justify all those expenditures, right?
But I think the public sometimes doesn’t know how much institutions like ours think about the civic good. I really believe, as our Founding Fathers did, and across all their lines of division, the Founding Fathers agreed that a free people need a free press and that a country that aimed to steer itself needed access to independent and reliable information.
Jefferson famously said, given the choice between a government without a press or a press without the government, he wouldn’t hesitate to choose the press. And that’s because this work really does matter to society.
Journalism is quite simply very often how you know what you know. Shifting over to AI, it’s how AI knows what it knows.
Yes, let’s get into that. In the context of AI in journalism, I break it into two buckets. For WIRED, there’s reporting on this technological moment in time, which is really important. And then there’s the separate question, although we cover that as well, of how AI will affect the practice of journalism and the consumption of journalism.
I mean, there are really difficult lines to walk here, and I’m curious about how you think about that at The Times.
I think my philosophy is you very rarely in life need to be first. There is a risk of jumping too quickly into an emerging technology. And there’s probably more risk in that than waiting, watching, learning, studying, experimenting quietly behind the scenes. I think you saw some of those risks, right? Like, think about the news organizations that, in my mind incredibly foolishly, decided to just hand over full responsibility for writing and publishing articles to AI. Mistakes were made.
Mistakes were made. And mistakes were published.
That is right. And not just mistakes were published, but fake journalists were invented. It was a completely foreseeable and unnecessary set of mistakes. Humans are responsible for everything we produce, period. And there’s something about AI that has tricked people into forgetting that it is a tool.
Well, it’s a very good conversation partner.
But when my colleagues say, “Well, what if AI makes a mistake?” I say, “Well, then it’s your job to find that mistake and take it out of your work.” You would never ask that about a computer. What if a computer makes a mistake?
Well, you gotta find it, right? I view this as a reporting tool. So we’re using it much more in reporting than writing, crafting, editing.
I think AI is very good at spotting patterns and anomalies in large data sets. In many ways, that’s a pretty good summation of a big part of reporting. You know, campaign finance reporting is basically what are the patterns, how is the mix of donors to the Republicans and Democrats changing, big donors for small donors, and then anomalies.
