Kevin Drum has an article in Mother Jones about AI and Moore's Law:

THIS IS A STORY ABOUT THE FUTURE. Not the unhappy future, the one where climate change turns the planet into a cinder or we all die in a global nuclear war. This is the happy version. It's the one where computers keep getting smarter and smarter, and clever engineers keep building better and better robots. By 2040, computers the size of a softball are as smart as human beings. Smarter, in fact. Plus they're computers: They never get tired, they're never ill-tempered, they never make mistakes, and they have instant access to all of human knowledge.

The result is paradise. Global warming is a problem of the past because computers have figured out how to generate limitless amounts of green energy and intelligent robots have tirelessly built the infrastructure to deliver it to our homes. No one needs to work anymore. Robots can do everything humans can do, and they do it uncomplainingly, 24 hours a day. Some things remain scarce—beachfront property in Malibu, original Rembrandts—but thanks to super-efficient use of natural resources and massive recycling, scarcity of ordinary consumer goods is a thing of the past. Our days are spent however we please, perhaps in study, perhaps playing video games. It's up to us.

Although he only mentions consumer goods, Drum presumably means that scarcity will end for services and consumer goods. If scarcity only ended for consumer goods, people would still have to work (most jobs are currently in the services economy). 

Drum explains that our linear-thinking brains don't intuitively grasp exponential systems like Moore's law. 

Suppose it's 1940 and Lake Michigan has (somehow) been emptied. Your job is to fill it up using the following rule: To start off, you can add one fluid ounce of water to the lake bed. Eighteen months later, you can add two. In another 18 months, you can add four ounces. And so on. Obviously this is going to take a while.

By 1950, you have added around a gallon of water. But you keep soldiering on. By 1960, you have a bit more than 150 gallons. By 1970, you have 16,000 gallons, about as much as an average suburban swimming pool.

At this point it's been 30 years, and even though 16,000 gallons is a fair amount of water, it's nothing compared to the size of Lake Michigan. To the naked eye you've made no progress at all.

So let's skip all the way ahead to 2000. Still nothing. You have—maybe—a slight sheen on the lake floor. How about 2010? You have a few inches of water here and there. This is ridiculous. It's now been 70 years and you still don't have enough water to float a goldfish. Surely this task is futile?

But wait. Just as you're about to give up, things suddenly change. By 2020, you have about 40 feet of water. And by 2025 you're done. After 70 years you had nothing. Fifteen years later, the job was finished.

He also includes this nice animated .gif which illustrates the principle very clearly. 

Drum continues by talking about possible economic ramifications.

Until a decade ago, the share of total national income going to workers was pretty stable at around 70 percent, while the share going to capital—mainly corporate profits and returns on financial investments—made up the other 30 percent. More recently, though, those shares have started to change. Slowly but steadily, labor's share of total national income has gone down, while the share going to capital owners has gone up. The most obvious effect of this is the skyrocketing wealth of the top 1 percent, due mostly to huge increases in capital gains and investment income.

Drum says the share of (US) national income going to workers was stable until about a decade ago. I think the graph he links to shows the worker's share has been declining since approximately the late 1960s/early 1970s. This is about the time US immigration levels started increasing (which raises returns to capital and lowers native worker wages). 

The rest of Drum's piece isn't terribly interesting, but it is good to see mainstream pundits talking about these topics.

I was reading a post on the economy from the political statistics blog FiveThirtyEight, and the following graph shocked me:

This, according to Nate Silver, is a log-scaled graph of the GDP of the United States since the Civil War, adjusted for inflation. What amazes me is how nearly perfect the linear approximation is (representing exponential growth of approximately 3.5% per year), despite all the technological and geopolitical changes of the past 134 years. (The Great Depression knocks it off pace, but WWII and the postwar recovery set it neatly back on track.) I would have expected a much more meandering rate of growth.

It reminds me of Moore's Law, which would be amazing enough as a predicted exponential lower bound of technological advance, but is staggering as an actual approximation:

I don't want to sound like Kurzweil here, but something demands explanation: is there a good reason why processes like these, with so many changing exogenous variables, seem to keep right on a particular pace of exponential growth, as opposed to wandering between phases with different exponents?

EDIT: As I commented below, not all graphs of exponentially growing quantities exhibit this phenomenon- there still seems to be something rather special about these two graphs.