Wall Street Journal    Artificial intelligence has arrived. Today’s computers are discerning
 and sharp. They can sense the environment, untangle knotty problems, 
make subtle judgments and learn from experience. They don’t think the 
way we think—they’re still as mindless as toothpicks—but they can 
replicate many of our most prized intellectual talents. Dazzled by our 
brilliant new machines, we’ve been rushing to hand them all sorts of 
sophisticated jobs that we used to do ourselves.
 
But our growing 
reliance on computer automation may be exacting a high price. Worrisome 
evidence suggests that our own intelligence is withering as we become 
more dependent on the artificial variety. Rather than lifting us up, 
smart software seems to be dumbing us down.[...]
Then, in the 1950s, a Harvard Business School professor named 
        James Bright
       went into the field to study automation’s actual effects on a 
variety of industries, from heavy manufacturing to oil refining to bread
 baking. Factory conditions, he discovered, were anything but uplifting.
 More often than not, the new machines were leaving workers with 
drabber, less demanding jobs. An automated milling machine, for example,
 didn’t transform the metalworker into a more creative artisan; it 
turned him into a pusher of buttons.
Bright concluded that the 
overriding effect of automation was (in the jargon of labor economists) 
to “de-skill” workers rather than to “up-skill” them. “The lesson should
 be increasingly clear,” he wrote in 1966. “Highly complex equipment” 
did not require “skilled operators. The ‘skill’ can be built into the 
machine.”[...]
Late last year, a report from a Federal Aviation Administration task 
force on cockpit technology documented a growing link between crashes 
and an overreliance on automation. Pilots have become “accustomed to 
watching things happen, and reacting, instead of being proactive,” the 
panel warned. The FAA is now urging airlines to get pilots to spend more
 time flying by hand.[...]
The philosopher 
        Hubert Dreyfus
       of the University of California, Berkeley, wrote in 2002 that 
human expertise develops through “experience in a variety of situations,
 all seen from the same perspective but requiring different tactical 
decisions.” In other words, our skills get sharper only through 
practice, when we use them regularly to overcome different sorts of 
difficult challenges.
The goal of modern software, by contrast, 
is to ease our way through such challenges. Arduous, painstaking work is
 exactly what programmers are most eager to automate—after all, that is 
where the immediate efficiency gains tend to lie. In other words, a 
fundamental tension ripples between the interests of the people doing 
the automation and the interests of the people doing the work. [...]
Harvard Medical School professor 
        Beth Lown,
       in a 2012 journal article written with her student 
        Dayron Rodriquez,
       warned that when doctors become “screen-driven,” following a 
computer’s prompts rather than “the patient’s narrative thread,” their 
thinking can become constricted. In the worst cases, they may miss 
important diagnostic signals. [...]
We do not have to resign ourselves to this situation, however. 
Automation needn’t remove challenges from our work and diminish our 
skills. Those losses stem from what ergonomists and other scholars call 
“technology-centered automation,” a design philosophy that has come to 
dominate the thinking of programmers and engineers. [....]
There is an alternative.
 In “human-centered automation,” the 
talents of people take precedence. Systems are designed to keep the 
human operator in what engineers call “the decision loop”—the continuing
 process of action, feedback and judgment-making. That keeps workers 
attentive and engaged and promotes the kind of challenging practice that
 strengthens skills.[...]