The actual survey result:

Asked whether “scaling up” current AI approaches could lead to achieving artificial general intelligence (AGI), or a general purpose AI that matches or surpasses human cognition, an overwhelming 76 percent of respondents said it was “unlikely” or “very unlikely” to succeed.

So they’re not saying the entire industry is a dead end, or even that the newest phase is. They’re just saying they don’t think this current technology will make AGI when scaled. I think most people agree, including the investors pouring billions into this. They arent betting this will turn to agi, they’re betting that they have some application for the current ai. Are some of those applications dead ends, most definitely, are some of them revolutionary, maybe

Thus would be like asking a researcher in the 90s that if they scaled up the bandwidth and computing power of the average internet user would we see a vastly connected media sharing network, they’d probably say no. It took more than a decade of software, cultural and societal development to discover the applications for the internet.

it will be relatively easy to strip off

How so? If it’s anything like llm text based “water marks” the watermark is an integral part of the output. For an llm it’s about downrating certain words in the output, I’m guessing for photos you could do the same with certain colors, so if this variation of teal shows up more than this variation then it’s made by ai.

I guess the difference with images is that since you’re not doing the “guess the next word” aspect and feeding the output from the previous step into the next one, you can’t generate the red green list from the previous output.