Are we dumbing ourselves down?
In the symbiotic view, AI should be
viewed as IA: Intelligence Amplification. For the individual neurons in
our brain, the flood of data they experience also has no relevance for
the system except as more “food” to
“digest.” An AI that requires a human
to give semantics to its outputs is
performing a function much like the
neurons in our brain, which also, by
themselves, have nothing like comprehension. It is IA, not AI.
Symbiosis does not mean we are
out of danger. Again, from Dennett:
“The real danger, I think, is not that
machines more intelligent than we
are will usurp our role as captains of
our destinies, but that we will over-
estimate the comprehension of our
latest thinking tools, prematurely
ceding authority to them far beyond
In addition, doomsayers predict
new technospecies will shed their sym-
biotic dependence on humans, mak-
ing humans superfluous. Dennett’s
final words are more optimistic: “[I]f
our future follows the trajectory of our
past—something that is partly in our
control—our artificial intelligences
will continue to be dependent on us
even as we become more warily depen-
dent on them.”
I share this optimism, but also rec-
ognize that rapid coevolution, which is
most certainly happening, is danger-
ous to individuals. Rapid evolution re-
quires death. Many technospecies will
go extinct, and so will memetic species,
including programming languages
1. Alain, C. Propos d’un Normand 1906–1914. Gallimard,
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2. Dawkins, R. The Selfish Gene. Oxford University
3. Dennett, D.C. From Bacteria to Bach and Back: The
Evolution of Minds. W. W. Norton and Company, 2017.
4. Dyson, G. Turing’s Cathedral—The Origins of the Digital
Universe. Pantheon Books, 2012.
5. Lee, E.A. Plato and the Nerd: The Creative Partnership
of Humans and Technology. MI T Press, 2017.
6. Lehman, M.M. Programs, life cycles, and laws of
software evolution. In Proceedings of IEEE 68, 9 (1980).
7. Parker, A. In the Blink of an Eye: How Vision Sparked
the Big Bang of Evolution. Perseus, Basic Books, 2003.
8. Rogers, D.S. and Ehrlich, P.R. Natural selection
and cultural rates of change. In Proceedings of
the National Academy of Sciences 105, 9 (2008),
Edward A. Lee ( email@example.com) is the Robert S. Pepper
Distinguished Professor in EECS at UC Berkeley, CA, USA.
Copyright held by author.
building (living?) software by combin-
ing and mutating pre-existing mod-
ules. Humans are as much facilitators
as inventors, and as Dennett notes
about culture, “[S]ome of the marvels
of culture can be attributed to the ge-
nius of their inventors, but much less
than is commonly imagined ...”
The same is true of software.
Although Dennett overstates the
amount of TDID in technospecies, human cognitive decision making strongly influences their evolution. At the
hand of a human with a keyboard, software emerges. But this design is constructed in a context that has evolved,
and if it is not beneficial to humans,
it likely fails to propagate. Its context
includes various artifacts of technical
culture, such as human-designed programming languages that have themselves survived a Darwinian evolution
and encode a way of thinking, and software components created and modified over years by others. The human
is partly doing design and partly doing
husbandry, “facilitating sex between
software beings by recombining and
mutating programs into new ones.” 5 So
it seems that what we have is evolution
facilitated by elements of TDID.
Is facilitated evolution still evolution? Approximately 540 million years
ago, a relatively rapid burst of evolution called the Cambrian explosion
produced a very large number of metazoan species over a relatively short period of about 20 million years. In 2003,
Andrew Parker postulated the “Light
Switch” theory, in which the evolution
of eyes initiated the arms race that led
to the explosion. 7 Eyes made possible
a facilitated evolution because they
enabled predation. A predator facilitates the evolution of other species by
killing many of them off, just as the sea
“kills” boats. So facilitated evolution is
Humans designing software are facilitators in the current Googleian Explosion of technospecies. It is proactive
evolution, not just passive random mutation and dying due to lack of fitness.
Instead, it mixes husbandry and predation with some elements of TDID.
How far can this coevolution go?
How much smarter will humans with
technology get? Dennett observes
that our brains are limited, but, he
says, “human brains have become
equipped with add-ons, thinking
tools by the thousands, that multiply
our brains’ cognitive powers by many
orders of magnitude.”
Dennett cites language as a key tool.
But Wikipedia and Google are also
spectacular multipliers, greatly ampli-
fying the effectiveness of language and
of software engineering.
Dennett observes that collaboration between humans vastly exceeds
the capabilities of any individual
human. I argue that collaboration
between humans and technology
further multiplies this effect. Stack
Overflow, Eclipse, Google, and countless open source components vastly
enhance my own productivity writing software. Technology itself now
occupies a niche in our (cultural)
evolutionary ecosystem. Much like
the bacteria in our gut, which facilitate digestion, technology facilitates
thinking, and thereby facilitates the
evolution of technology.
Dennett calls AI, particularly deep
learning systems, “parasitic”: “[D]eep
learning (so far) discriminates but
doesn’t notice. That is, the flood of
data a system takes in does not have
relevance for the system except as
more ‘food’ to ‘digest’.”
This limitation evaporates when
these systems are viewed as symbiotic
rather than parasitic. In Dennett’s own
words, “deep-learning machines are
dependent on human understanding.”
An understanding of these systems as symbiotic mitigates today’s
hand-wringing and angst about AI.
Dennett raises one commonly expressed question: How concerned
should we be that we are dumbing ourselves down by our growing reliance
on intelligent machines?
should we be that
we are dumbing
by our reliance on