Tag: economics

Future of the Economy Part 5 – Lateral Productivity Growth

George LondonLeave a comment

Back in the sky, back at the keyboard. Last time in this series, I made two claims:

1) The only way to consistently improve human well-being is to foster productivity growth.

2) Productivity only grows when people invent better methods of production (i.e better technology).

The economy is just a machine that turns raw commodities (e.g. iron) into
consumable products (e.g. corn flakes). The output of any given machine is
limited by how fast the machine can operate; a miner can only dig so fast and a
CPU can only cycle so fast. Machines tend to be made faster over time, but
usually at pretty slow and steady rate.

Productivity Growth is Steady
(Source)

And consequently annual productivity growth over the last 100 years has been remarkable consistent at around 1-2%.
If we want productivity to grow faster than that, we can’t just speed up existing
processes. We have to implement completely new ones. Instead of getting faster
at harvesting bat guano, we need to invent synthetic fertilizer.

So…how do we do that? That’s the key question in this whole series.

Well, the way that humans do it through a specific type of intelligence commonly
called “lateral reasoning” (or sometimes just “creativity”.) Everyone has an
intuitive idea of what creative intelligence is: in a classic test, a child is
given a paperclip and asked to write down as many ways of using the paperclip as
she can. And from there it’s a pretty short leap to “how can I build a CO2
filter out of duct tape and a flight manual?”

Unlike its close cousin linear reasoning (i.e. 1+1=?), lateral reasoning is
rather poorly understood. So much so that it’s often treated with a sort of
mystic reverence
(cf. “a flash of inspiration”). And
it’s the last unironic refuge of the word “genius” in popular discourse (cf. “the creative
genius Steve Jobs”). And while computers have come to dominate humans at classical
intelligence tests like
Chess
and
trivia
the most advanced computer in the world can’t figure out how to fix a toaster [2].

But lateral reasoning is not magic. It actually works pretty much the same way as linear reasoning.

Consider a Chess game:

  1. Start in some situation, e.g. in check, down a knight.
  2. Using your knowledge of the rules, consider all legal moves (or use heuristics to only consider a subset).
  3. Imagine the sequence of potential consequences of each action and calculate the most promising path.

Now consider a lateral problem:

  1. Start in some situation, e.g. on a desert island with a can of beans and a rock.
  2. Using your knowledge of how the world works, figure out potential “moves” you can make, e.g. “smash the can with a rock”.
  3. Consider the consequences of your options and choose the best action.

The only difference is that linear problems tend to involve relatively
simple, clearly specified situations, a small numbers of simple rules, and a potentially enormous sequence of steps to solve. Whereas lateral
problems can often be solved in just a few steps but involve complex, nebulous situations
and an enormous number of complicated, underspecified rules.

Computers, at present, are fantastically adapted for the former type of problem
and terribly adapted for the later. But that’s going to change fast (even if I
have to change it myself.) Over the coming decades, we’re going to see an
explosion of computers designed to extend human lateral intelligence. And that’s
going to produce productivity gains unlike anything we’ve seen before.

Next time, I’ll tell you how it’s all going to happen.

[1] Even semi-exceptions like Moore’s law tend to be steady even if they aren’t slow.

[2] Unless Google can find an exact recipe some human wrote down.

Everything you need to know about economics in 400 words, Part 3

George LondonLeave a comment

It seems I only write on this topic while flying. So I guess you can expect this series to wrap up sometime in 2015.

But to recap, last time I told you that productivity is prosperity. So all increases in per capita wealth come from increases in the amount of economic goods a single worker can produce in an hour.[1]

So how does productivity increase? Let’s start with the obvious. We get the stuff we have by making complicated stuff out of simpler stuff. We start with iron and chemicals, apply some process over a period of time, and end up with steel. Visually:

(1 unit of Time + 1 unit of Iron + 1 unit of Chemicals) => 1 unit Steel

The productivity of this process is simply the ratio of inputs to outputs. If we rejiggered the above process to produce 2 units of steel from the same input, we would have doubled productivity.  Ditto if we halved the amount of time.

Physical productive processes are closely analogous to computer algorithms. We could just as easily talk about the “productivity” of a bitcoin mining operation in terms of how many BC a computer can generate per hour.

So how do we get more productivity out of our processes (which, to reiterate, is the only way we get richer overall)? Well, just like with computer algorithms we have two options:

Do the same thing faster (e.g. get a faster CPU)

Swap in a better algorithm (e.g. use quick sort instead of bubble sort)

“Do more faster” is an appealing tagline, but unfortunately human land-speed doesn’t follow Moore’s law. So our best option is to find better algorithms for our productive processes.

So transitively, the best way for society to get richer is to devise and select better processes. By and large, we call process improvements technology. The cotton gin and the Bessemer process were technologies that allowed radically more efficient transformation of a raw commodity into a finished product.

One of the most important stories of the last 30 years has been the way that computers have inserted themselves deeply into our economy’s various productive processes. But most of what we’ve seen so far are “do the same thing faster” improvements. The real productivity revolution will come once computers consistently help us choose better algorithms for our processes and for our lives.

 

[1] Okay, all increases except one-off “gold strikes” that shower us with random natural riches.

Future of the Economy #1 – What is An Economy?

George LondonLeave a comment

Last time, I laid out my roadmap for describing my vision for the future of the economy. Now, again awaiting an algorithm’s end, I take the first step.

Today’s topic is simple – “what is an economy?”

Whether you’ve studied economics or not, (and I never have in any academic setting), that is a tricky question.

To some, the economy is “the intersection of supply and demand.” To others, it’s what falls out of comically complex equation like these. To the dictionary, it’s:

3. the management of the resources of a community, country, etc., especially with a view to its productivity.

4. the prosperity or earnings of a place.

My more modest proposal – “the economy is everything.”

Or, less dramatically, everything (even potentially) useful to human life collectively constitutes “the economy.”

Some examples, in order of increasing controversy:

Economy:

Gold coins

Bread

Rapper Mansions

Fighter Jets

Yellowstone National Park

Cats

DNA

Human Life

Not Economy:

Crab Nebula

As I’ll explain more clearly in subsequent posts, it’s significantly more cogent to include immaterial “objects” like interpersonal relationships, human knowledge, or natural beauty in our definition of “economy”.

Every useful thing, whether material or immaterial, can then be labeled a “resource”. The economy is merely the sum of all resources.

A brief aside – taking a broad view of the economy can be a dangerous game, and there are many very powerful ethical arguments to be made against viewing human relationships etc. through an economic lens. The core fear is that we will start treating human relationships with the sort of “non-ethical, anything-for-a-dollar” ethos that permeates the phrase “it’s not personal; it’s just business.” Instead, I am hopeful that we will instead do the reverse and allow human decency to seep back into traditional economics.

Now, one more step. The size of the whole economy is much less important than prosperity, which is the sum of all resources divided by the number of people utilizing those resources (i.e. Sweden is a very prosperous country, but if we divided the wealth of Sweden across the population of India, the resulting country would not be very rich at all.)

Good economic policy should have a single-minded focus on increasing prosperity (properly conceived, so that we aren’t bulldozing geysers to build factories.)

But how exactly do we increase prosperity? Tune in next time…

P.S. It makes me smile that “bulldozing geysers” formerly had no Google hits.