Or, will computer automation do us in?
Timothy B. Lee discusses this topic in his article in The Washington Post this morning.
“Timothy B. Lee covers technology policy, including copyright and patent law, telecom regulation, privacy, and free speech. He also writes about the economics of technology. He has previously written for Ars Technica and Forbes.”
Since covering this beat and topics since the 1980s, it is never dull, and most always inconclusive.
Authors and experts often debate the effect from applying computer automation to the work environment where people are treated as “personnel support subsystems”. That is a term used in the 1970s by AT&T to describe the role of technicians maintaining electronic switching systems.
In the factory at Bendix Automation, machine tool operators making automated test, inspection, and measuring machines were a combination of skilled trades and computer technologists working side by side to build machines that automate testing in automobile manufacturing and aircraft manufacturing companies.
People like Dennis Wisnosky, who became Chief Technology Officer at the DOD and Daniel S. Appleton advocated a process modeling technique that classified people as enablers of work. People and technology are the “mechanisms” for producing work that is defined as process activity which transforms resources into higher yield outcomes that may be products, assets, and performance results. All of that produces a combination of costs and value under constraints of budget and time.
People support machines. Machines support people.
Society is about the business of creating a good life for all citizens within the bounds of government laws and regulations (The American Political System) and the economic model of its choosing. Today, we operate in a mixed capitalistic system for which many believe is not sustainable. So, emphasizing computers versus people trivializes the real issue and that is how to create a good life for all by becoming the best that we humans can be.
This is a great snippet of a story because it may make you think about it.
“No, artificial intelligence isn’t going to take all of our jobs
BY TIMOTHY B. LEE
October 23 at 12:35 pm
Recently, Boston University scholar James Bessen reviewed Tyler Cowen's new book, "Average Is Over," for the Switch. Cowen argues that the rise of ever more sophisticated software will destroy middle-class jobs, leaving us with a world of widening inequality. Bessen argues, to the contrary, that as information technology matures, it is likely to create a growing number of decent-paying jobs for moderately skilled workers.
Kevin Drum, a blogger for Mother Jones, didn't like Bessen's argument, calling it "literally the worst possible case you can make for the continued relevance of the middle class." Ouch. In a tweet, I described Drum's post as "sneering and thoughtless." He pleads guilty to sneering but denies his post was thoughtless. So let me substantiate that charge and then get to the meat of his argument.
Drum started his post with "I haven't read Tyler Cowen's Average Is Over." And that's the problem. "Average Is Over" is not a book about a science-fiction future in which computers can do absolutely everything human workers can. Obviously, that world will be radically different from our own, and it might very well be a bad environment for middle-class workers. Rather, "Average Is Over" is about a medium-term future in which computers are getting steadily better at tasks like driving and operating factories, but there's still significant room for human labor to complement the efforts of the machines.
Drum faults Bessen for not answering the question, "What happens to human labor when machines are smart enough that they need virtually no human guidance at all?" But that's not what "Average Is Over" is about, so it's bizarre to fault Bessen for not addressing it in his review of the book.
But should middle-class workers be worried about machines becoming so smart that they take everyone's jobs? The argument that Drum and other futurists make for this proposition dramatically overestimates the importance of raw intelligence in the labor market.