The Media Candidate (10 page)

This set of policies not only drove the
decisions, but also automatically generated new decision criteria
or revised old ones as the environment required. This was the
innovative, and many said high-risk, part of COPE’s automated
management system. Many managers at COPE called this a foolish
dependence on an uncontrollable machine. Having a machine interpret
and apply existing policies, they said, was risky enough. But
empowering a machine to modify the policies themselves, or even to
institute new ones, was the ultimate foolishness. The young PhDs,
however, all educated in new-wave management science at the
country’s leading universities, carried the day. This was COPE’s
“window on the future.”

* * *

In 2042, four years before the Sherwood and
Jenner team were assigned to Project Dagger, the computer’s
development had been entrusted to Dr. Matthew I. Planck. Dr. Planck
viewed the computer, not as a machine to be enslaved, but as an
extension of himself to be liberated to share the task of human
management. He’d spent a distinguished career at the Institute for
Research on Artificial Life.

Dr. Planck’s artificial life forms were neural
network packages that would propagate, mutate, colonize, and
retreat, but not in a random way. They were driven by goals that
were initially directed by humans, but evolved along with their
tactics. He’d crafted many forms of life-like entities dividing and
multiplying in his Petri dish of silicon and gallium arsenide.

Not only had he cultivated these replicating and
evolving electronic entities, he had put them to work to develop
inorganic judgment systems of unprecedented power. He’d headed
teams that applied artificial life to a number of milestone
intelligent systems. His greatest success was a disease diagnostic
system that had been proven superior to the best teams of medical
doctors in numerous and varied tests. His greatest failure was his
inability to convince the medical establishment to use this
lifesaving technology. Dr. Planck’s outspoken criticism of the
medical community raised impediments to his continued effectiveness
at the Institute.

* * *

He agreed to be interviewed by Ms. Duvay from
the Silicon Valley Times. She arrived promptly at his office and
sat across his desk from him. A TV camera and operator perched
innocuously in one corner of the room. Ms. Duvay’s long blonde hair
and Cinderella voice contrasted with the sophistication of the
audience she addressed. Her hair and voice on TV was processed to
look and sound much more academic.

After getting more at ease with Dr. Planck, she
began the interview in earnest. “Could you explain how your
inorganic judgment systems differ from those of many other
researchers?”

“I’ll put this in layman’s terms,” he said.
“It’s like a baseball player trying to play wearing football pads
or hockey skates. You see, the baseball player needs the freedom to
do certain things that football players don’t normally do and, of
course, ice skates would be totally inappropriate. Such a player
adorned with all the protective gear of football would be
needlessly hampered in his ability to field or bat properly. And
the hockey player needs skates to—”

“I understand the analogy perfectly, Dr. Planck,
and our sports editor will be excited to talk to you later, but I’d
like to get into some of the technical aspects of your work.”

“Of course,” he said with a contrived smile. “I
was merely setting the stage for a discussion that can quickly
become laboriously painful for someone not adequately trained in
advanced computer technology.”

“We appreciate that, Dr. Planck. A few years
ago, an interdisciplinary team at the University of Dayton used
artificial-life concepts to develop advanced logic algorithms that
far exceeded the efforts of those using even the best Monte Carlo
or Bayesian techniques. But their results still fall short of the
phenomenal success you’ve achieved with your AIPs, your Autonomous
Intelligence Packages. Could you please explain what you’ve done
differently?”

“Ah … yes. I … I’d be most happy to address that
issue.” He cleared his throat as he studied his interviewer. “All
the other approaches, even the successful Dayton approach, have
been trying to force the computer to work according to rigid human
instructions in ways they believe computers should think. I treat
the computer like a gifted child, like my own son. I feed it
decision-making skills, but I let it decide, not only how to mutate
the instructions to best conform to its evolving decision matrix,
but also how to assemble the parts in a way that’s meaningful to it
and where to store the various pieces of the total package. I think
that’s the critical element. I construct an environment that
encourages the computer to establish its own storage map using
optimization of various figures-of-merit, which relate directly to
an innovative cognizance index. It’s the location in the computer
memory of not only the stored algorithms and data files, but even
down to the cellular automata level itself, that makes my technique
work.”

“Do you allow the computer total freedom as to
where it stores various kinds of data?”

“In a way, yes. But only after I’ve taught the
machine certain basic principles about the interrelationship of
data types; that is, how the descriptive parameters of objects
interact. For example, I’d teach it about the functional
relationships between a baseball glove and a hockey stick. You see,
the baseball glove interacts with the player in the same way
as—”

“I see, Dr. Planck, so what you’re saying is you
teach the computer basic functional relationships among the various
data sets, and then you just turn it loose?”

“Well … it’s not quite
that
simple. I
have to create certain optimization parameters that guide the
location of data with other data that may be similar in certain
ways. I start the computer off with a suggested list of data-type
correlations and their transfer functions, but then the computer
refines that list and even restructures the transfer functions
among the data types. Finally, it will be totally free to modify
the data types in any way that best optimizes the output. You see,
that’s the beauty of a neural network. It learns from its mistakes
just as you and I do.”

“That sounds very much like the neural networks
other researchers are developing.”

“That’s exactly right! But what I’ve done is to
give the computer the freedom to design its own neural networks and
to replicate them and intertwine them in such a way as to optimize
the basic parameters and transfer functions of the system. That’s
just the way the human brain works. Another thing I’m working on is
the integration of digital processing and neural processing to
achieve the benefits of both.”

“You have used the expression
transfer
function
a number of times. Could you explain just what you
mean by that?”

“Yes, of course. The transfer function is at the
heart of a neural network computer. You can picture a neural
network as a web of neurons with billions of intersections, which
we call nodes—not to be confused with the nodes of digital
computers. As an electrical pulse of information, which is
analogous to the electro-chemical pulses in your brain, reaches
each node, a decision must be made as to how much of the received
signal is distributed into the connecting neurons. Two or more
transfer functions define each of these inter-neuron distributions.
Keep in mind that the neural network of my device is an electrical
analog of the electro-chemical neural network known as your
brain.”

“I see. The transfer functions are the
mathematical equivalents of the inter-synaptic weighting factors of
the brain.”

“Yes,” replied Dr. Planck. “I didn’t want to
make it any more complex than necessary. It’s like the subtle
interactions among basketball players to let the teammates know
whether the play will be a drive to the paint or a kick-out to
three-point range. That kind of—”

“Thank you for that consideration, Dr. Planck.
Could you explain what a
cellular
automata
is?”

“Yes, of course. That’s simply the smallest unit
of autonomous, replicable code. It’s much like the human cell. It’s
the building block of my digital/neural network hybrid. I designed
a whole family of cellular automata, thousands of them. Each one
was a block of computer code that would perform a specific
function. They were similar to subroutines of the old days.”

“What do you mean—
were
?”

“That’s the interesting thing about this
computer. Those cellular automata that I designed probably don’t
even exist any more. I designed each one to seek other cellular
automata that perform functions that are similar, in sometimes
quite subtle ways, to the one it performs. Of course, each cellular
automata had several built-in docking sites—sort of analogous to
receptors in molecular biology. After link-up and testing, they’d
make a decision about whether to continue the relationship. If it
was positive, then a fracture would occur in the second cellular
automata, and some functional part of it, maybe even all of it,
would split off and adhere to the first one. Then the second one
would go looking for a docking partner. This is a way for the
system to evolve toward a higher function without the cellular
automata growing excessively. I didn’t want any particular types of
cellular automata to become too complex and dominate others or to
grow without constraints. That’d be sort of like cancer. So you
see, after a while the cellular automata might look and behave
quite differently from the ones I created.”

“That’s very exciting. It’s an evolution
somewhat analogous to what takes place between proteins as they
make subtle changes to human cells.

“Right.”

“Now, if we could switch gears for a moment, I’d
like to talk about an application. Why has the medical profession
not accepted your diagnostic program in light of its enormous
success over the last few years of testing?”

“They’re afraid. That’s all, just afraid.”

“Could you elaborate on that, please?”

“I always get in trouble with this question.”
Dr. Planck paused while he stared at the ceiling for a moment.
“We’ve performed over a hundred diagnoses with this system. In
every case, my system plus a single physician was able to perform
more accurate and faster diagnoses with far less patient testing
than any of the teams we’ve gone up against. In the few cases where
neither the team nor the machine were able to develop a correct
diagnosis, teaming the machine with the medical team finally
yielded the right answer. I can only assume that the medical
profession is afraid of the technology, that they can’t see it for
what it is, a helper not a threat.”

“In the past, you’ve had much more to say about
it, using such expressions as ‘blue collar doctors’. Have you
changed your mind?”

Dr. Planck looked directly into the camera and
said very deliberately, “My opinion is not a variable. If you want
a better answer, take your question to the medical community. You
might ask them how job security figures into their rejection of
this diagnostic system. It seems they have learned much from the
teaching community in this respect.”

The interview continued, addressing several
military and economic applications for AIPs, and then ended
amicably. As a final comment, Dr. Planck picked up a piece of paper
from his desk and read, “I have been engaged in artificial life and
other advanced computer concepts for over thirty years, and the
computer research community is finally beginning to appreciate my
work. I have the satisfaction of knowing I was able to point the
way toward the ultimate development of the greatest machines ever
created by man. I believe I will live to see the day when these
machines will demonstrate their ultimate capability to infallibly
and diligently serve the interests of man. My three decades of
exhausting work have occupied my time to the exclusion of many
personal activities such as antique car restoration and auto and
motorcycle racing. I have gladly forgone these interests for the
sake of my profession, however there is one that I must attend to.
I have been writing a book that will detail this great human
experiment with computer evolution. For its sake, I have chosen to
retire from the Institute and spend my time catching up on my book
and other interests. Thank you.”

The next day Dr. Planck accepted, with no media
attention, a position at COPE. There he found visionary thinkers
who were willing to push the envelope of performance and
applications to unprecedented heights. It would be an opportunity
to develop an automated management system, that he felt would be
the model for corporations and institutions everywhere. He became
the Associate Director for Data Services and single handedly took
over the role of computer-system advanced development while the
existing Data Services staff continued with the day-to-day
operations role.

Dr. Planck was a hybrid, his body was born of
human parents, but his mind evolved more like the computers he
nurtured than like the son of mortals. He was endowed with the
passion of a human being, yet he was single-minded in his career.
He didn’t just believe in computers, he was one with them. He
approached computer development as a father would teach his son
where the secret pools were with the most ancient trout and how to
tie the perfect fly that would dance across the water to excite
those docile leviathans with the vigor of youth. Dr. Planck had
married twice, and each marriage lasted long enough for his wife to
discover and capitulate to his lifelong mistress. In both cases, he
felt betrayed by weak humans.

He did, however, have one great passion beyond
computers—speed. The outlet for this passion was a 1956 Corvette
with chrome heads and glass pack duals. At a time when the muscle
cars, like most other motor vehicles, were equipped with silent
electric motors and electronic synthesizers to replicate some
engineer’s version of the sound of machismo, he had a
mint-condition historic car that could outperform any other car,
both on the pavement and in the testosteronic realm.