You Already Email Like a Robot — Why Not Automate It?
You Already Email Like a Robot — Why Not Automate It?
By John Herrman Nov. 7, 2018
In 1996, Microsoft unleashed Clippit, better known as
Clippy, on users of Microsoft Office. The legendarily irritating mascot-helper
spent the following years hovering around the edges of documents, blinking
dumbly under his lascivious eyebrows and blurting out, “It looks like you’re
writing a letter,” until he was sidelined by the company in 2001, officially
recognized as a mistake. Clippy’s problems were manifold. He announced his
presence, via a personified avatar, to tell us something that we already knew
(or that should have been obvious in the first place) and then proudly offered
us little in the way of actual help. He sat and watched us and learned nothing,
and repeated himself. He said too much and did too little.
Nevertheless, over 20 years later, the spawn of Clippy
are hiding everywhere, guessing what we’re trying to do and offering to help.
But Clippy’s successors are doing their best to avoid his mistakes. Most of the
time they are faceless, and if they speak, they do so in a disembodied but
humanlike voice. They tend to wait to be asked for help, rather than telling us
what they think they know unprompted. And when they do offer help, they tend to
be more subtle, more accurate or both. They have perhaps more in common with
Clippy’s unassuming partners, like Spelling and Grammar Check or AutoCorrect,
which spoke through red underlines or small actions carried out on reasonable
assumptions (who would intentionally type “teh”?). These tools have followed us
and our clumsy fingers to our new smartphones, where they have become both more
assertive and more useful, correcting us and only occasionally requiring us to
correct them back, and learning all the while.
What does the tech industry want to assist us with now?
Email. If you use Gmail, you’ve probably interacted with either Smart Reply or
Smart Compose, whether or not you know them by name. Google introduced Smart
Reply in 2015, and Smart Compose began rolling out this year. Both, in execution,
are self-explanatory. Smart Reply suggests canned responses to inbound emails,
based on the company’s best guess at what most emailers might be about to type.
The suggestions are short, peppy and often adequate, at least as a start.
Sometimes their tone prompts unhappy realizations about what Gmail sees in us.
The frequency with which they use exclamation marks emphasizes just how
peculiar the language of professional email communication has become (“Sounds
great!” “Very cool!” “Love it!”). Smart Compose, in contrast, offers word and
phrase suggestions, based on similar judgments, as the user types in real time.
You write “Take a look,” and ghostly text might appear to its right: “and let
me know what you think.” Its assumptions are more personalized, and they feel
that way because it is constantly, visibly, guessing what you’re thinking.
Smart Compose and Smart Reply are, at their core,
artificial-intelligence technologies: They are programmed to perform tasks, but
also to adapt. To start, Smart Reply was trained on publicly available bodies
of email text. (Among the most widely used for such projects is the cache of
some 500,000 emails collected during the discovery phase of the Enron
investigation.) “What makes machine learning different from regular programming
is you look at corpuses of data to make guesses about things,” says Paul
Lambert, a product manager for Gmail. “You create a model.”
Once that model was trained to deal with some of the more
obvious idiosyncrasies of email communications — corporate disclaimers and
phrases like “Sent from Outlook” — Google began training it on anonymized text
from actual Gmail users. Phrases that appear frequently enough come under
consideration for inclusion in Smart Reply. This, too, requires cleanup. Early
testers reported seeing “I love you” as a suggested response to work emails.
Armed with this catalog of phrases — currently more than
20,000, according to the company — the model can then start incorporating more
contextual clues: What was the subject of the email? Is the email asking a
question? Is it expressing a happy sentiment, or is it offering condolences?
Phrases are scored based on their utility — how much typing they save,
basically — as well as the A.I.’s confidence in the prediction.
Both features then take into account how people use them.
If, for example, it suggests a certain completion, and enough users take it,
that one will be more likely to appear in the future. If a canned reply is
never used, this is a signal that it should be purged; if it is frequently
used, it will show up more often. This could, in theory, create feedback loops:
common phrases becoming more common as they’re offered back to users, winning a
sort of election for the best way to say “O.K.” with polite verbosity, and even
training users, A.I.-like, to use them elsewhere. Such a dynamic would take
root only where a behavior is already substantially automated — typed, at work,
more as a learned performance rather than as an expression of will, or even an
idea. Smart Compose is, in other words, good at isolating the ways we’ve
already been programmed — by work, by social convention, by communication tools
— and taking them off our hands.
Using these features is a bit like minding a machine that
is trying to learn how to do what you do for a living. And even if it’s the
part of the job you wish you didn’t have to do, it still prompts uncomfortable
thoughts of replacement — or, if not replacement, then something close to it.
It is not remotely implausible that in the near future, a tremendous amount of
communication could be conducted in tandem with an A.I.
But constant sweeping changes in office communication —
from speaking and writing to phones and printing to emailing and instant
messaging — do not tell a tidy tale of increased efficiency or decreased
workload, even as they represent progress. Already, an undefined but undeniable
portion of workplace email amounts to human self-automation: an uncanny form of
communication where clichés aren’t shunned so much as recognized for their
usefulness; where a tone of polite enthusiasm is taken to its exclamatory extreme
to mash any ambivalence you may have about, say, “circling back later.” One can
visualize in the near future hundred-email chains between colleagues unfurling
from a single human starting point, composed of nothing but routinized replies.
Depending on what your current inbox looks like, this
might not require much imagination at all. A study conducted in 2016 by
researchers at Carleton University’s Sprott School of Business in Canada tried
to understand the role email had come to play in the modern office. They
surveyed “highly educated baby boomer or Gen X” subjects who were mostly
“managers or professionals” working in office jobs and found that they spend on
average a full third of their workweeks “processing” email. Whatever their
titles, they are — like many office workers — to a large extent professional
emailers. Even if their roles are otherwise highly specialized, in this
significant way they are not. They are their own assistants.
In 1930, John Maynard Keynes wrote that, thanks to new
efficiencies, workers of the future could expect “three-hour shifts or a
15-hour week.” He guessed that this would happen within a century. Automation
and the abundance it produced has indeed led to countless economic changes, but
it did not negate or replace the entire order. Asked for evidence of the
success of this newest tool, Google says that Smart Compose is already “saving
people a billion characters of typing each week.” This statistic supports one
half of what Keynes might have predicted at the dawn of automated communication
— the abundance and the glut — but is tellingly silent on the other half, the
same half he couldn’t quite see the first time. Self-automation can free us
only to the extent that it actually belongs to us. We can be sure of only one thing
that will result from automating email: It will create more of it.
A version of this article appears in print on Nov. 10,
2018, on Page 22 of the Sunday Magazine with the headline: Google is helping
relieve the knowledge workers of the world from the drudgery of email — by
revealing how inhuman it was in the first place.
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