This is Brad DeLong's Grasping Reality—my attempt to make myself, and all of you out there in SubStackLand, smarter by writing where I have Value Above Replacement and shutting up where I do not… CROSSPOST: Paul Ford: The A.I. Disruption We’ve Been Waiting for Has ArrivedThe New York Times’s subhead: “We’re entering a new renaissance of software development. We should all be excited, despite the uncertainties that lie ahead.” It took a century starting back in 1875...
The New York Times’s subhead: “We’re entering a new renaissance of software development. We should all be excited, despite the uncertainties that lie ahead.” It took a century starting back in 1875 for 20% of the jobs in the economy to be destroyed or completely upended by the technological kernel of the classic industrial revolution: coal-steam-textile-machinery-iron-railroad. Ever since 1875 it has taken not a century but a generation: about four-fifths of the economy sees incremental growth at about one-percent per year while the structures and organizations remain much the same, while one-fifth of the economy gets fully destructed and leveled to rubble and then rebuilt and created in previously unimagined futuristic mode to do five times as much, or more.This generation it is knowledge workers who are in the bullseye of this Schumpeterian creative destruction process…The first foreshock in this category came with radio and its impact on the vaudeville performers of a century ago as communications and computers began to do what computers and communications would do. Since then, the computer-and-communications-and-internet leading sector kernel has gotten rid of rooms-full of of people punching keys on adding machines and typewriters, inserting plugs into switchboards, producing and filing documents—the few secretaries, AAs, and EAs left are now “admins” coordinating and gatekeeping—sorting mail, consulting actuarial tables, calculating ballistics and stresses, hand-tabulating records, manually keeping books and ledgers, calculating payrolls, back-office transaction reconciliation, operating telegraphs, setting and compositing type, pasting-uo pages, operating linotype machines, cutting and splicing films with razor blades, developing images in darkrooms, routine travel bookings, punching keys on cash registers, hand-keying and processing orders, manually counting inventories, controlling transportation signals, writing up index cards, taking dictation, sampling and cross-checking from large paper datasets, manually configuring networks and devices, operating keypunch msachines, coding surveys, answering directory assistance calls, routine translation. Jobs whose core was symbol manipulation, creation, and transformation in physical form or abstract representation under a short set of fixed rules—typing, sorting, adding, routing, filing, simple querying—are the ones computers and networks take first. The work did not disappear; the job structures did. Some share of tasks migrateed “up” into fewer, more highly skilled roles; much migrated “out” to self‑service by end users; some migrated “down” into algorithms and ‘bots. And jobs with a major task component consisting of symbol manipulation under fixed rules were transformed, sometimes utterly. All that happened. But what is happening now is that, as we move into the attention info-bio tech economy proper, the skilled white-collar information-processing jobs move under the bullseye. A surprisingly large number of them now appear to involve lots of tasks that are not manipulating under a short set of fixed rules but rather manipulating in ways that turn out to have surprisingly low Kolmogorov complexity. Those are being utterly transformed even without the coming of anything that anyone other than a grifting hypester would label “Artificial General Intelligence”. And, as those who know how to do them well become 10x as productive and those who can learn barely enough how to do them at all become good enough to cobble along, some of these job categories greatly shrink and those in or planning to be in them need to find other things to do, while others substantially expand in number and create potential gold rushes—all depending on which side of the demand-elasticity Jevons’s-Paradox canyon-gulf they land on.
Now comes the OG blogger Paul Ford <http://ftrain.com> to blog his reactions to being at the center of this:
##crosspost-paul-ford-the-ai-disruption-weve-been-waiting-for-has-arrived |
| ||||||||||
No comments:
Post a Comment