IEEE Consumer Electronics Magazine - April 2017 - 107

formal grammars. The approach of parsing a sentence into deep structures didn't
make sense to me because it meant
eliminating the essential ambiguity. It
seemed to make more sense to maintain
that ambiguity as long as possible and
then eliminate possibilities that didn't
work. [This works best when words (or
phrases) serve as the brain's internal representation and conversations between
people are similar to our internal dialog.
But that's another topic.]

THINK ABOUT IT
Computers think differently from people. Note that I put think in italics to
distinguish it from the way people typically conflate thinking with self-awareness. I'm just using think in the sense
of cognitive process. This is part of the
confusion caused by using anthropomorphic terminology for dynamic systems. We use such terms because, as
we've seen, the emergent properties
are similar to what we see in other
people. But it makes it all too easy to
slip into projecting human cares on
inanimate objects.
If we accept that these are alien
intelligences, we can start to speak to
them in something akin to a native language. We can designate roads as autosteering friendly. On those roads,
human drivers may see their line gradually disappear and understand they are
supposed to merge while yielding. That
same highway can have Tesla markers
showing the merge path and giving the
merge rules.
Driving the Tesla, I was acutely
aware of the limits of the software and
tested my understanding. My wife
didn't always appreciate those tests or
the Tesla's judgment. It has a tendency
to drive more closely to side obstacles
than people are comfortable with. The
software should be as concerned about
people's comfort zones as it is about
safety. It had difficulty with many situations that are obvious to people, like not
staying in a lane that is disappearing.
Given how intelligent the car seemed
to be, why didn't it deal with traffic
lanes and follow directions to turn?
That's probably coming, but city streets
will remain a challenge, especially for

We need to be wary about
extrapolating our love
affair with these automatons as our devices become
increasingly capable and
intelligent since the
algorithms they are built
on don't really care but
only act as imperfect
and, often, buggy
reflections of what we
teach and show them.
roads that don't have definite lanes and
myriad other such ambiguities and
unstated assumptions.
Having two different intelligences
sharing the same highway can be a
challenge. The onus, to a degree, is on
the aliens, partially because they are
visitors but also because they are, for
now, expecting self-driving cars to be
more responsible and to yield to their
human counterparts' careless behavior.
If I know a car is on autosteering, I might
merge into its lane knowing (sometimes naively) that it will yield.
It's frustrating for the self-driving cars
(or at least their programmers and users)
in that the cars can't take advantage of
their adroitness. Such cars can drive
faster and closer to their design limits
while making tradeoffs for fuel use. They
can also cooperate with other cars on the
road and coordinate along stretches of
roads. A two-lane road for such cars can
have the capacity of a three-lane road.
Even one-lane roads can be bonded similar to the way of network wires.
It's understandable that the current
emphasis is on solving the problem entirely within the car. Once we are able
to get past emulating people, we can
take advantage of the real capabilities of
these alien intelligences. We can also
start to rethink transportation and what
cars can be.
When speaking to someone who
doesn't speak your language, you don't
shout, you try to find a common vocabulary. Instead of treating cars as a best

friend, we need to think in terms of the
new possibilities of our smart devices.
Instead of a driverless car, we might
provide rides using whatever vehicle is
available and appropriate for the task-
self-driving taxis rather than cars.
We need to be wary about extrapolating our love affair with these automatons as our devices become increasingly
capable and intelligent since the algorithms they are built on don't really care
but only act as imperfect and, often,
buggy reflections of what we teach and
show them. But we can't always extrapolate what happens as these systems
evolve. Algorithms that work in the
small may not work in the large, and
algorithms that apply to populations
may be perverse when applied to individuals. They simply cannot care.
One positive result of trying out the
Tesla's autosteering system is that my
wife now has a high opinion of my
driving, or, at least, believes that I am
better than your average Tesla.

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APRIL 2017

IEEE Consumer Electronics Magazine

107

Table of Contents for the Digital Edition of IEEE Consumer Electronics Magazine - April 2017