I’d be stunned if Andreessen’s extremely educated viewers really believes the lump of labor fallacy, however he goes forward and dismantles it anyway, introducing—as if it have been new to his readers—the idea of productiveness progress. He argues that when know-how makes firms extra productive, they move the financial savings on to their clients within the type of decrease costs, which leaves folks with more cash to purchase extra issues, which will increase demand, which will increase manufacturing, in a wonderful self-sustaining virtuous cycle of progress. Better nonetheless, as a result of know-how makes employees extra productive, their employers pay them extra, so that they have much more to spend, so progress will get double-juiced.  

There are many issues fallacious with this argument. When firms change into extra productive, they don’t move financial savings on to clients except they’re compelled to by competitors or regulation. Competition and regulation are weak in lots of locations and lots of industries, particularly the place firms are rising bigger and extra dominant—suppose big-box shops in cities the place native shops are shutting down. (And it’s not like Andreessen is unaware of this. His “It’s time to build” submit rails in opposition to “forces that hold back market-based competition” corresponding to oligopolies and regulatory seize.) 

Moreover, massive firms are extra doubtless than smaller ones each to have the technical sources to implement AI and to see a significant profit from doing so—AI, in any case, is most helpful when there are massive quantities of information for it to crunch. So AI could even scale back competitors, and enrich the house owners of the businesses that use it with out lowering costs for his or her clients.

Then, whereas know-how could make firms extra productive, it solely generally makes particular person employees extra productive (so-called marginal productiveness). Other instances, it simply permits firms to automate a part of the work and make use of fewer folks. Daron Acemoglu and Simon Johnson’s e book Power and Progress, a protracted however invaluable information to understanding precisely how know-how has traditionally affected jobs, calls this “so-so automation.”

For instance, take grocery store self-checkout kiosks. These don’t make the remaining checkout workers extra productive, nor do they assist the grocery store get extra consumers or promote extra items. They merely permit it to let go of some workers. Plenty of technological advances can enhance marginal productiveness, however—the e book argues—whether or not they do depends upon how firms select to implement them. Some makes use of enhance employees’ capabilities; others, like so-so automation, solely enhance the general backside line. And an organization typically chooses the previous provided that its employees, or the legislation, pressure it to. (Hear Acemoglu talk about this with me on our podcast Have a Nice Future.)

The actual concern about AI and jobs, which Andreessen solely ignores, is that whereas lots of people will lose work shortly, new sorts of jobs—in new industries and markets created by AI—will take longer to emerge, and for a lot of employees, reskilling can be exhausting or out of attain. And this, too, has occurred with each main technological upheaval up to now.

When the Rich Get Richer

Another factor Andreessen would really like you to imagine is that AI gained’t result in “crippling inequality.” Once once more, that is one thing of a straw man—inequality doesn’t need to be crippling to be worse than it’s immediately. Oddly, Andreessen kinda shoots down his personal argument right here. He says that know-how doesn’t result in inequality as a result of the inventor of a know-how has an incentive to make it accessible to as many individuals as attainable. As the “classic example” he cites Elon Musk’s scheme for turning Teslas from a luxurious marque right into a mass-market automobile—which, he notes, made Musk “the richest man in the world.”  

Yet as Musk was changing into the richest man on this planet by taking the Tesla to the plenty, and lots of different applied sciences have additionally gone mainstream, the previous 30 years have seen a slow but steady rise in revenue inequality within the US. Somehow, this doesn’t seem to be an argument in opposition to know-how fomenting inequality. 

The Good Stuff

We now come to the wise issues in Andreessen’s opus. Andreessen is right when he dismisses the notion {that a} superintelligent AI will destroy humanity. He identifies this as simply the newest iteration of a long-lived cultural meme about human creations run amok (Prometheus, the golem, Frankenstein), and he factors out that the concept that AI might even determine to kill us all is a “category error”—it assumes AI has a thoughts of its personal. Rather, he says, AI “is math—code—computers, built by people, owned by people, used by people, controlled by people.”

This is totally true, a welcome antidote to the apocalyptic warnings of the likes of Eliezer Yudkowsky—and completely at odds with Andreessen’s aforementioned declare that giving everybody an “AI coach” will make the world robotically higher. As I’ve already stated: If folks construct, personal, use, and management AI, they’ll do with it precisely what they wish to do, and that would embody frying the planet to a crisp.