Saturday, March 31, 2012

Artificial intelligence has failed my inbox

Today we have artificial intelligence infused into many aspects of our technological life. Siri on the iPhone can understand our verbal commands. IVR - or Interactive Voice Response - is ubiquitous nowadays. Machine learning algorithms are applied to our financial history to tell banks how to maximize our debt. Marketeers use advanced algorithms to maximize the one-way flow of cash from our wallets to their companies. Evolutionary Computation algorithms are currently being applied to the mechanical design of airplane jet engines - maximizing the flow of compressed air through it multiple stages. And the applications grow daily.

The promise of A.I. is finally coming true. The cyber-augmented future, the intelligent machine, the avatar of many a stories and movies is a reality today. Vernor Vinge's Singularity is approaching, some would say (although Paul Allen thinks differently!).

Yet, our most pervasive interface into this world, this Metaverse (to steal from Neal Stephenson), this collective intelligence, is still a throw-back to the late 1960s - and it is far from being intelligent. The venerable email and its inseparable companion, the inbox, are still very passive and dumb pieces of software.

Today I watched a talk by Neal Stephenson titled "Getting big stuff done" in which he laments our current inability to tackle the big challenges that are present in our lives today. He describes, as only he can, the leaps in technological advance we took from the early 1900s until about 1968 and the significant underachievement in the latter part of the century. He goes on to challenge us to think big. It was a very interesting, if somewhat unnerving observation (we are afraid of big projects, moonshot type of projects, that is!).

But today, I wasn't thinking about big problems (almost never do!). Today, I was perplexed by a far more mundane problem.

My inbox (at work) has over 40,000 messages (this doesn't include my "sent" messages, which are part of the problem I am lamenting about). Sure, I have some folders to which messages matching simple rules are route to. But that is it. My email inbox knows nothing about my reading habits. It doesn't really know what is important or not. It doesn't know which messages can be safely ignored, which should result in an instant warning sent to me (think a text message delivered to your phone). It doesn't know which messages are related to a project. It doesn't know which messages are simply noise, office chatter; messages which are best destined for the bit bucket that is the trash bin. It doesn't know which messages contain information that should be stored for later recall (think about "how-to" type of messages from your colleagues or replies from a Microsoft tech about an obscure bug your organization encountered and which is likely to pop up again). My inbox, your inbox, most of our inboxes, are dumb and very passive recipients of information.

The A.I. revolution has, by and large, left the email inbox behind. It has failed the inbox.

A quick Google search yields many research papers on this subject. Yet, that research has not materialized into a viable email agent that learns from my email reading, organizational, and replying habits. We have applied A.I. to far more complex problems. Today we have companies dealing with Big Data, looking for relational patterns to combat terrorism. Text mining and document classification is no longer just a research topic. Many companies (!) deal with this problem as their main line of business. But our inboxes remain clogged with useless message, messages that flood us every minute and which are not worth the time spent to determine how to triage them.

It is time for our inboxes to grow some brain. I suggest that we have enough algorithm and computing power in our hands (literally, think dual-core iPhone and Andriod devices) to support a far more intelligent interaction with emails.

I would like my email program to...

  • Learn from my manual categorization of messages (supervised learning) and apply that knowledge as its level of accuracy increases.
  • Learn about the association of messages and recipients or senders. Learn to advice me when a certain recipient should be added to an email thread. Think of your email system reacting to a message sent to you with a question: "In the past, so and so has answered this question for you. Would you like to forward this message to so and so?"
  • Learn to triage my messages based on urgency, time specifications. Think along the lines of: "You have received 10 messages on this topic during the last two days and this one appears to specify a deadline"
  • Review my draft replies and fix my mistakes. And no, I don't mean spelling or grammatical errors. I mean, emotional "errors". Think along the lines "Last time you replied to this person with similar words, a "nasty" exchanged ensued"!!! Imagine how much time and aggravation this would save!
  • Answer simple questions (or create a draft). Imagine a question from a colleague, a question that you might have already answered on a previous exchange with someone else. Why would you have to manually reply? Why wouldn't your email agent/avatar draft a reply with the answer?

I know these are hard problems to solve. But I believe the current state of A.I. can provide reasonable answers to them. Learning algorithms, specially when supervised, can build excellent stimuli-response systems. If we can have cars drive themselves, airplanes land automatically, and our participation in the free market maximized by algorithms, then we must be capable of creating a smart email system.

Perhaps we still have "small stuff" to be done!

UPDATE: Well, maybe not so small when Y Combinator considers this is an investment opportunity!

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