This week’s catch is the 1994 (non-peer-reviewed) article by William Nordhaus: “Do Real Output and Real Wage Measures Capture Reality? The History of Lighting Suggests Not.” Bill Nordhaus is the Sterling Professor of Economics at Yale University and although the paper is almost 23 years old, the ideas are still original and very relevant today.
Real wages in economics are measured by comparing the average amount of money a worker in a society gets paid to how expensive the cost of living is. For example, people in the Bay Area get paid better for comparable work than someone in Durham, but it is much more expensive to live in San Francisco than in Durham. It is useful to know whether and how real wages change with time, but as Nordhaus points out, this is not straightforward because technologies are rapidly changing. His idea is to measure the luminosity of the most efficient light source available at a given time and calculate for how long the average person must have to work to afford that luminosity. He goes through the eye, open fires, lamps, candles, gas, petroleum, and electricity. Twenty pounds of wood produce about 1000 lumen-hours of light and would have taken an individual in the stone age about 60 hours to gather and chop the wood. George Washington calculated that burning a candle for 5 hours every night would cost him about $1200 for the whole year. The equivalent modern LED “candles” would “burn” for 52 years for that amount of money.
While the article is about lighting technology, the idea can easily be applied to other technologies, such as computation (Moore’s Law), data storage or analytics capabilities. In terms of finding patterns in data, we’ve had only our brain for most of history but we are at a point in which artificial intelligence, particularly neural networks, are able to (painfully) find patterns that might be too complex for the human brain alone to pick up. That is to say, our current artificial intelligence technology is to the brain as open fires were to our ancestors’ eyes. We have to gather and chop pounds of silicon to get modest results, but it is still an augmentation of the ability of our human brain. I am looking forward to when the technology will be cheap enough for individuals to afford and to see what they do with that. Scary and exciting.
Non-technical BBC article about the article: http://www.bbc.com/news/business-38650976