Why Machine Learning isn’t about machines

How will machine learning change us as a society? It’s now time to ask this question — before we start building products and services that have unintended consequences.

I wanted to start this blog post by referencing “the turn of the the last century.” I realized that would put me smack dab in the middle of the Y2K hysteria, and not in the birth of bureaucracy (whence such hysteria came).

No, we only know what the “turn of the century” means, many years in retrospect. Now, we can look back on the year 1900 and see quite clearly that its significance was the shift from idiosyncratic, family-run, and sometimes chaotic organizations toward professional management, and of course, bureaucracy.

It was hard to see while it was happening, but Max Weber saw it (perhaps that’s why he had a nervous breakdown). Weber saw that we had begun to run our businesses and governments with standardized rules, and standardized hierarchies. No longer could the boss’s son waltz in and tell everyone what to do, unless he had an actual job title. (Well, that was the idea anyway; we apparently still let the boss’s kids take jobs they’re not qualified for).

This was radically new and had huge implications for how we purchase, exchange, work, and live. Bureaucracy became the irrationally rational norm; rules were to be followed even if they made no sense.

Which brings me to machine learning. Machines can learn if we give them the tools to learn, and the data to help them practice. But they cannot see what Max Weber saw. Machines cannot know they are creating an irrational bureaucratic hellscape — and nor would they care. They are very good at things humans are bad at, namely, vigilance and repetitive tasks. We should let them do those things.

But we should not let machines make decisions about rules, about whether the boss’s son is qualified, or other culturally and socially important questions. At the turn of this century, we are making machines that can do all of those things, but we are not pausing to evaluate whether we should.

Historians like to say that the 19th century did not really end on the arbitrary date of December 31, 1899, but instead on the more auspicious and socially meaningful date of November 11, 1918. It was only then that humanity realized what its changes had wrought, what horrors we had invented, and that humans themselves must take responsibility for those changes. I would argue we need to do the same now, before an equally socially meaningful date in the future.

Why Cortana doesn’t work at work

Microsoft is betting that Cortana will bring AI to the workplace. Here’s why that won’t happen.

Cortana is an intelligent agent  that is supposed to act as a personal assistant. You can interact with her (notice I said “her”? More on that in a minute) via voice or text, on mobile devices or on desktop computers. Given that Microsoft’s mobile market share has fallen below 1%, it’s pretty much a certainty that most people would interact with Cortana in their offices.

We know that most Windows 10 computers are in workplaces, so there’s a very strong likelihood that people will talk to Cortana in an office. This is very different place than where people might interact with Siri on their phones, or Alexa in their homes. Siri and Alexa t are called upon in private, controlled places (in fact, just 3% of iOS users report using Siri in public).

Let’s walk through that interaction of Cortana as a member of a workplace.

Microsoft encourages you to command Cortana by saying, “Hey Cortana…” and then giving her a command. A typical office scenario might be, “I wonder if I should book a vacation for the first week of August. Hmm. I’ll ask Cortana.”

This is how Cortana is supposed to work:

User: Hey Cortana, should I book a vacation for the first week of August?

Cortana: Let me check your calendar. Looks like you have a meeting on Monday, August 1st. Should I move it for you?

User: Yes, that’d be great.

Cortana: Okay, I’ve moved that meeting to Monday August 8th. Would you like to see some vacation suggestions?

User: Yes, please!

This is exactly how it plays out on a demo video one Microsoft’s site.

But let’s face it: there are a lot of contextually dependent reasons why this is completely unrealistic. Leaving aside Cortana’s technical limitations for the moment (and there are many), let’s take a look at what a real office and real user might look like.

Most offices are either open concept without even the suggestion of walls. As many as 70% of us work in open concept offices. As anyone who’s worked in such an office can tell you, hearing a neighbor on the phone can be excruciatingly annoying or excruciatingly awkward, depending on your neighbor’s TMI quotient.

cortana

So there’s a good chance that everyone in the user’s office will hear this idealized scenario.  There are two clear disincentives against this happening. First, Cortana will make more “boundary work” for office workers. The mere act of trying to keep your private life private at work is turns out to be, well, work. Recent research  has found that keeping work and life private actually causes cognitive overload. If people use Cortana as intended, she is poised to make that much worse.

Second, Cortana demands office workers treat their workplaces as if they were kings and queens, instead of pawns and rooks. Voice interactions require workers to own their workspace, something that we know they do not do. Typical workers share their workspaces with others, and because we are apt social animals, we tend to comply with unwritten rules of workplace etiquette. Bosses’ calendars take precedence over workers’ calendars. Bosses talk more than workers. Men talk more than women. In other words, people with power talk out loud more than people with less power.

Which brings me to the fact that Cortana is a woman. Is it any coincidence that most intelligent agents today are anthropomorphized as women? One of the most striking changes in the twentieth century workplace was the almost total elimination of support staff, which were typically women. Only the most senior executives have assistants nowadays, and other mid-level white collar workers are on their own for scheduling  and administrative work.

cortana 02

Let’s not forget that Cortana is actually based on a supportive AI character in a video game. Cortana provides these workers with a sense that they can indeed recoup the times of Mad Men and have a compliant, supportive, and self-abnegating assistant who has no needs of her own. Practically, this promises white-collar workers with a huge productivity boost, but the symbolic nature of this is even more interesting. When white-collar workers have a virtual assistant, they have re-claimed a sense of hierarchy, of control, and power (even if it is completely imaginary).

And this is why Cortana will not work in the workplace. Today’s typical office worker does not have power enough to command the space around her, and bark orders to anyone out loud, even if just to an intelligent agent. This office worker has been stripped of her ability to occupy a rung on the ladder higher than admin or support staff, because there is no admin or support staff. This typical office worker is embedded in a physical space that reflects this lack of hierarchical position — she has no command over it.

Scholars of gender and technology have described some ill-advised approaches to gender equality as “add women and stir.” The same applies to Cortana and other intelligent agents. You cannot “add Cortana and stir” and expect to see productivity improvements that somehow negate the existing organizational and physical structures of contemporary workplaces.

 

Microsoft’s Future Productivity Vision

At long last, I am able to share our work on the future of productivity. Video storytelling is a way of envisioning the future without the constraints of actually building all the prototypes. These conceptual prototypes cover a few important themes. Look for:

  • The end of the full-time job
  • Inter-generational care work, via distance
  • Online reputation management
  • Networked production of several enterprises and individuals
  • Just-in-time work spaces and places
  • Mobile productivity and seamless integration with traditional computing systems
  • Visualizing production through social network analysi