These types of AI computers and programs are highly detailed and beyond what most people could afford. More importantly, as far as photography is concerned, if photography begins to incorporate more and more machine learning and deepfake technology, it could leave photography in the hands of those with the most massive budget and most expensive computers. Many photographers worry their current images will be stolen and used as deepfakes. Deepfake photos have the potential to show people in embarrassing situations or saying or doing something they did not. This can involve merging real images flawlessly (think of Face Swap on Snapchat, with greater accuracy) or creating artificially generated people. Deepfake pictures are already happening and occur when images are superimposed onto video or other photos, to mislead the viewer deliberately. They could write “blonde boy on a horse near a lake” and then instantly manufacture faces and images created through machine learning (which is what AI is based on).
When it comes to replacing photographers, all that it might take in the future to produce a highly detailed, realistic image is for someone to type what they need into a computer. Others recommend that humans rely on a type of pay called Universal Basic Income, as traditional jobs become unsustainable. Some people worry that this might lead to chaos, as people will have little work to do and be idle, with a lot of spare time on their hands. Not only is the field of photography at risk, but advancement in technologically advanced machines may also replace most tasks performed by humans – engineering jobs, automotive, transportation, and more. One frightening way that AI can affect photographers is by replacing them.
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One example of modern AI is the facial recognition software found in Apple’s newest iPhones, which can distinguish one face from another, almost instantly.
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This would allow AI to do many things that humans cannot without manual computer use. While those ideas are still pursued, the larger, more important, goal is for machines to become (significantly) more adept than humans are at multiple tasks. From those new renderings of artificial intelligence, the goals have changed, and human-like robots are no longer the primary goal. One triggering event for the increase in AI focus post-1997 was IBM’s robot (Deep Blue) defeating a human in the quiz show “Jeopardy”. Since then, technology and funding have continued in an ebb and flow fashion, with a significant focus on AI occurring since 1997. Funding began again in 1980, primarily because the United States wanted to compete with Japanese scientists’ efforts.
Part of that lack of funding was due to public misconception and concern after adverse reports criticizing the process emerged. This is partly because government funding to the technology was lacking (and almost non-existent) from 1974-1980. While scientists expected more substantial advancements to occur within that generation’s lifetime, they did not.
The future looked bright to the MIT cognitive scientists in attendance at that event, but the reality was more complicated. It was then that the term “ artificial intelligence” was used publicly. What we know of as modern AI has its first roots at a conference in 1956, held at Dartmouth College.
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