It is 2025. Human intelligence has largely been outsourced to machines. A select few corporations and financial institutions extract incalculable value from the unceasing data flow, taking advantage of relentless digital efficiencies at global scale. Labor has evolved from production and distribution to the specialized maintenance of increasingly autonomous networks. A flash of explosive economic growth briefly accompanies this transition, followed by a persistent hobbling of human productivity. Those employed to serve the network are fairly well rewarded; the rest eke out a living on the margins in a stupor of digital subordination.
It isn’t Skynet exactly, but this vision of the near-future would still seem dystopian to many.
In our efforts to comprehend technological transformations, there are a great many questions that are raised. Some center on social, civic and ethical concerns; others have to do with economics. Paul Krugman‘s recent New York Times editorial, “Is Growth Over?” explores the latter.
Krugman’s piece is itself a response to Robert Gordon of Northwestern University, who asserts that economic growth is likely to slow — a view that counters projections by those who hold fast to the idea that technological efficiencies always result in expansion. The latter is only partially true: with any major technological shift there are winners and losers. Some sectors experience growth, while others struggle and stagnate. We are now in uncharted territory in which history may not provide a reliable benchmark for future developments. We have no way, for example, to predict how the rise of “smart machines” or the “Internet of things” will impact productivity. My guess is exponentially, and not in the direction many of us would prefer.
Gordon points to three distinct epochs of productivity, or Industrial Revolutions:
- IR #1 (steam, railroads) from 1750 to 1830;
- IR #2 (electricity, internal combustion engine, running water, indoor toilets, communications, entertainment, chemicals, petroleum) from 1870 to 1900; and
- IR #3 (computers, the web, mobile phones) from 1960 to present.
… IR #2 was more important than the others and was largely responsible for 80 years of relatively rapid productivity growth between 1890 and 1972.
Once the spin-off inventions from IR #2 (airplanes, air conditioning, interstate highways) had run their course, productivity growth during 1972-96 was much slower than before. In contrast, IR #3 created only a short-lived growth revival between 1996 and 2004. Many of the original and spin-off inventions of IR #2 could happen only once – urbanisation, transportation speed, the freedom of women from the drudgery of carrying tons of water per year, and the role of central heating and air conditioning in achieving a year-round constant temperature.
Is this the end of the line for growth? That likely depends on how you define it.
Krugman is probably right when he counters that growth has not yet reached its plateau. He even acknowledges that this expansion may not benefit the broader swath of his countrymen: “Unfortunately, it’s all too easy to make the case that most Americans will be left behind, because smart machines will end up devaluing the contribution of workers, including highly skilled workers whose skills suddenly become redundant.”
The latter point is deserving of further consideration. Current debates around privacy and cybersecurity are illustrative of the challenges in a networked world where private corporations, courts and governments hold tremendous sway over our most fundamental rights. But this is hardly even the whole picture. In our relentless pursuit of efficiency and economic expansion, we may end up writing human productivity right out of the script.
Efficiencies scale. So do problems.
There may, in fact, be a limit to how well economies can function past a certain level of networked integration. Furthermore, there may be a finite set of beneficiaries within these efficiencies. Think of it as a kind of natural law, an economic entropy hastened by the arrival of machine intelligence and large-scale data extrapolation. For whom do these systems work? What are the real-world impacts for those outside of the narrow areas of productivity afforded to actual people? How can a hyper-efficient non-scarcity economy exist within a world of finite resources and real human need?
This is the dark side of the Singularity, in which our species ceases to play a meaningful role in its own destiny. Where the vast majority of humanity does not experience “uplift,” but rather stagnates as a handful of elites reap the benefits of globally-networked capital exploitation. Human ingenuity is flattened in a tsunami of information, even as machines make exponential leaps in efficiency by absorbing and reconfiguring impossibly large data sets. Patterning and prediction is the sole province of the network. Inspiration is an archaic conceit. Digital replication of our “selves” is possible, but provides no spiritual succor. We are bereft of meaning; asleep.
I’m not ready to say that resistance is futile, but it’s probably highly unlikely. If we cannot enshrine basic human values into existing socio-economic structures, we have very little hope that our digital progeny will respect the boundaries between expansion and exploitation.
Today is December 28, 2012.
