It used to be the case that there were a few people one
might call smart. Now, we call phones smart, whiteboards smart, computer
programs smart, learning environments smart, technologies smart, and even
automobiles and cities smart. What has become of the meaning of the descriptive
adjective ‘smart’?
What I really crave is a smart chocolate ice cream cone. I
suppose someone has an answer for that as well … perhaps one that has no sugar,
no calories, and no reason to ask for seconds. I am wondering about the meaning
of ‘smart’ because I was asked about it in a meeting with faculty and graduate
students in the Educational Technology Department in the Institute of Education
at Tsinghua University in Beijing.
Perhaps the location of an educational technology program
within a university reflects or influences how ‘smart’ is conceptualized. One
can find educational technology programs in a college or faculty of education,
or in a college or faculty of information, or information science, and even in
an arts and sciences college or faculty. In an education college or faculty,
one might imagine the emphasis to be on technologies that can be used to make
people smarter. In a college of information or information science, one might imagine
the emphasis to be on devices and technologies that did things that people who
used to be called smart used to do. It would be an interesting exercise for
someone to look at where educational technologies were located within a
university structure, the various emphasizes and perspectives reflected in
those programs, and any patterns or correlations that might emerge from those
data.
My own views are shaped by my experience – first with
philosophy and later with computer science. My philosophy perspective is based
in skepticism (e.g., recognizing the limits of knowledge and the ease with
which we are inclined to believe we know more than we actually know or believe
that the world happens to conform to the limits of our knowledge) while my
computer science perspective is based on artificial intelligence and expert
systems. I have seen the word ‘smart’ used quite differently in both of those
contexts.
I would consider Socrates smart, for example. He would
elicit ideas about such things as justice and virtue from the sophists and show
that their beliefs led to contradictions or absurd conclusions, such as a
virtuous ruler as one who manages to squeeze the most work and highest taxes
from citizens, applying the notion of virtue as that which benefits the stronger
– with the conclusion that what is good for one is not necessarily good for
another. I was fascinated early in life by the logic of such an indirect proof.
I had also seen it used in mathematics, as in the common proof that pi is an
irrational number – assume it is rational and then step by step one arrives at
a contradiction which means the point of departure was not sound. Pi must be
irrational – aren’t we all from time to time?
And then to earn a living, I took up computer science and
became fascinated with expert systems and the representation of human expertise
in software programs. I was attracted to complexity and the notion that somehow
software might be able to extend the ability of people to deal with complexity,
which could be conceived as a way of making those persons smarter – able to
perform more like experts.
One vivid memory I have of my time as a practicing computer
scientist involved being responsible for some 400 plus programs written in
Assembly Language and Fortran running simultaneously on five different
computers, four were 32-bit Perkin-Elmer mini-computers and the fifth was a
30-bit graphics computer. The application was real-time simulations of air
combat training. One task I had was to add software tracking of the sun’s position
along with a number of fighter jets that would simulate firing air-to-air
missiles at enemy aircraft and record probable hits and misses and then debrief
the pilots after the exercise. The task was to show the pilots the location of
the sun in their cockpit views when they fired a heat-seeking missile, as it
would go after the sun and miss the target. Getting that simple change to work
proved a very complex and challenging task. I got stuck trying to make it work
as every time I thought I had it figured out, the software would crash (in
simulated runs rather than in actual exercises – we always made sure the
software would work before using it in live exercises).
After a week of
pondering over the crashes and narrowing the logic failure to a few lines of code
among the thousands of lines involved, my mentor and a senior programmer (Walt
Davis) advised me to make a single random change in those few lines and see
what happens. He also could not see a problem with the logic and agreed the
problem had to be among those lines of code. The change I settled on was to
reload a memory location with the same doubleword that was just loaded in the
previous line of code – yes, that was in Assembly Language. Unbelievably, the
change solved the problem. What I had thought had to be a problem with the logic
proved to be a timing problem. By reloading that register with the same
information, the other programs running in parallel had time to catch up and do
their tasks. Walt was smart. He did not know what was wrong but he knew I
needed to get more information, and making one small change was a way to start
getting more information.
Perhaps a smart computer processing system would have
suggested a similar change, but I have yet to see such a system perform with the
smartness of a Walt Davis. I suppose that might become possible at some point.
Back to my point – what is with all these uses of the word
‘smart’. Is it not hard enough to identify a smart person much less identify
which devices are smart or which are only being called smart so as to improve
sales. Some leaders and leaders to be call themselves smart. The sophists with
whom Socrates interacted called themselves smart. Self-attribution of smartness
seems to be a likely indication of lack of smartness.
At least devices are not yet able to call themselves smart.
Yes, that will probably happen at some point. But then I recall Bob Gagné’s
advice to me while working together at the Air Force Armstrong Laboratory in
San Antonio. He said, “our job is to help people learn – to help them become
smarter … better at solving problems.” Oh yes. We might even be able to use
various devices and techniques in doing that all important job.