“What does that mean? Well, computers haven’t changed much in 40 or 50 years. They’re smaller and faster, but they’re still boxes with processors that run instructions from humans. AI changes that on at least three fronts: how computers are made, how they’re programmed, and how they’re used. Ultimately, it will change what they are for.
“The core of computing is changing from number-crunching to decision-making,” says Pradeep Dubey, director of the parallel computing lab at Intel. Or, as MIT CSAIL director Daniela Rus puts it, AI is freeing computers from their boxes…
…AI is even helping to design its own computing infrastructure. In 2020, Google used a reinforcement-learning algorithm—a type of AI that learns how to solve a task through trial and error—to design the layout of a new TPU. The AI eventually came up with strange new designs that no human would think of—but they worked. This kind of AI could one day develop better, more efficient chips.”—Will Douglas Heaven, “How AI is reinventing what computers are.” MIT Technology Review. October 22, 2021.
Open Question: As artificial intelligence becomes more pervasive, what limits should we impose as a society and on ourselves on how we use this technology, so it minimizes its negative impact?
The key changes described in this article:
- Volume, less precise calculations carried out in parallel
- Defining success by outcomes rather than defining processes
- Machine autonomy, i.e., artificial intelligence prompts people, acting as surrogate and agent
All to the good. But, there are negative social implications as this technology reaches critical mass among populations, a significant portion of people will off-load a subset of decisions to machines, which may be a net positive. However, easy to imagine that it undermines people’s ability to think for themselves, that the subset creeps into classes of decisions where it shouldn’t, e.g., prison sentences for people, and within the areas where it is commonly used, it will create a decision-making monoculture that crowds out alternative values. For example, if a dominate flavor of A.I. decides that Zojorishi makes the best automated rice cookers, which they do, and only makes that recommendation. Some large percentage of people, only buy Zojorishi. Then, the natural result is it will push other rice cooking options out of the market and make it difficult for new, possibly better, companies to emerge.
Lots of strange network effects that will happen due to this trend that should be given careful consideration. Even on a personal level, it would be good to have a clear idea of what exactly you’d like to use A.I. for, so you don’t undermine your own autonomy, as has happened in other computing eras, such as Microsoft dominating the desktop market.