Have you ever really looked at a photon?
Part wave, part particle, all perfection. Yet
they bring out the worst in some people,
who bring out the worst in me. Let’s start
with the obvious: Photons, in all their
quantum quintessence, can improve the
security of internet connections. Any-
body can poke around standard-issue
encryption keys undetected, but when
the 1s and 0s are hooked into specific
photons, that snooping triggers telltale
state changes—revealing the presence
of a hacker! Clever, right? What’s less
clever, and more maddening, are the
ways companies overhype this style of
quantum cryptography. They witter of an
“unbreakable” and “unhackable” inter-
net. I like quantum engineering projects
as much as any midichlorian-blooded
nerd, but a cybersecurity panacea?
Au quantraire! The suggestion turns
me into Schrödinger’s sourpuss: nei-
ther angry nor disappointed but a super-
position of both. Only someone with the
brains of a baryon—they are delight-
ful but not smart—would claim quan-
tum cryptography promises foolproof
protection. Fancy tech is built by the
skin-bags of water and viscera we call
people, and people are not all perfection.
Go ahead and give a highly trained some-
one a top-secret mission and a computer
with a quantum-encrypted connection.
Before long, they will turn lusty or sleepy
or bored. They’ll forget about software
updates, share their passwords, and click
links they should not. (Don’t ask me how
I know.) A canny hacker can wait for you
to de-quantize your supersecret key and
then steal it. Quantum encryption is cool,
but the marketers need to cool off. Pho-
tons have an intrinsic angular momentum
of 1, and that’s all the spin they need.sighs, “has gone to garbage.” (Gabriel is not
his real name, though you probably figured
that out. He doesn’t want to burn bridges.)
Why do I raise the seemingly arcane sub-
ject of transcription? Because if you want
to understand the future of work, it offers
a succinct capsule.
Change is murky and weirder than
you might expect. For example, demand
for transcription has actually exploded in
recent years. “It’s big across every area,” says
Jill Kushner Bishop, who runs Multilingual
Connections, a Chicago transcription and
translation firm. Why? Because audio is
(As this story was going to press, Rev
announced the rate it charges custom-
ers would go to $1.25 but did not specify a
higher base pay rate for transcribers.)
Meanwhile, the sheer profusion of
phone-recorded audio can mean that
some is murky and muddled, making it
mind-wracking to decipher. It can also
be psychologically ghastly: Transcribers
have opened Rev audio files to discover
victims describing abuse or graphic files
from police body cameras. Disturbing con-
tent is nothing new, but at an old-school
firm the manager might warn a transcribereasier than ever to capture (via our pocket
computers), so people are recording ever
more meetings. Plus, video and podcasting
have become the dominant forms of rhet-
oric. Daily communication is increasingly
multimedia.
But multimedia is cumbersome; we still
can’t search the contents of video or audio
very well, so we need to transcribe it. “We’re
in this world where we are overwhelmed by
spoken word that’s recorded, and it piles
up and up,” says Jeffrey Kofman, the CEO
and founder of Trint, an AI transcription
firm. Gutenberg would savor the irony. The
growth of the shiniest new media has made
the dustiest—text—ever more relevant.
Now, theoretically, exploding demand
would drive up the price of labor, right?
Except that globalization and the gig busi-
ness model have exploded the supply of
workers. Much as with Uber, Rev made it
so easy to start transcribing that many more
folks now do it as a side hustle.
“They give a lot of people opportunity,
which is cool,” as one Rev transcriber told
me. And as with most gig companies, Rev
seems obsessed with making things simple
and frictionless for the customer—hence
that sweet, flat rate of $1 per audio min-
ute. But a low rate winds up screwing the
worker. This fall Rev abruptly dropped its
pay for some content to 30 cents per audio
minute, which works out to a bleak income
of perhaps $4.50 an hour.in advance. Many Rev transcribers have
said they get none. After a few hours of
intense material, “I need to have a drink—I
need to smoke a joint,” Gabriel says. (Rev
declined to comment on the conditions for
its transcribers.)
By now you may be thinking, hey,
aren’t machines going to destroy all these
jobs anyway? Not yet. Despite all the
deep-learning hype, AI struggles with the
messiness of reality. Background noise,
cross talk, non-Western accents all tend
to flummox transcription AI.
It could take a very long time to get over
that hump. Humans disambiguate bad
audio by grokking the context of the conver-
sation, by deploying common sense. Today’s
AI is no good at that, and AI experts are still
figuring out how to engineer it. Sure, the
machines will increasingly be able to tran-
scribe clear and simple audio. But the hard
stuff? That’ll require humans. Pissed-off,
overworked, underpaid humans.
So ponder their fate the next time you
think about the future of work. AI doesn’t
always win. Tech—and today’s sharklike
gig-work business models—don’t always
destroy jobs.
They just make them a lot more likely
to suck.Humans disambiguate bad audio by grokking
the context, by deploying common sense.
Today’s AI is not good at that.
THE QUANTUM CON
CLIVE THOMPSON (@pomeranian99) is a
wired contributing editor. Write to him at
[email protected].