In a land that is right here and in a time that is right now, a technology has arisen so powerful that it can replace basic human document review. Is it time to bow down before our new robot overlords?

Last time I regaled or, alternately, disgusted you with a tale of my days as an objective coder. We covered such weighty topics as mind-numbingly repetitive labor, mind-pummelling attorney billing practices, and the prehistory of the human-computer-interface that is my beautiful two-year-old Apple fan-girl daughter. As I said, that was about context. About trying to establish a context in which you might find the introduction of a “predictive” technology to not be such an unwelcome thing.

Let’s stop for a second and consider a handful of predictive technological sidekicks that are so useful (if occasionally a nuisance) we no longer consider them innovative because they are, in fact, essential. Here’s a short roll call:

• Spam filters
• “Adult” content filters
• Explicit image searches
• Targeted advertising
• iOS’s auto-correct.

I know, I know. You’re thinking, “Wait, I thought he was going to try and convince me that predictive coding is a good thing”. And, sure, we’ve all missed an important email because the spam filter caught it. Or we’ve tried to do a legitimate search for, I don’t know, “chicken breasts”, only to be foiled by an overzealous content filter. Or we’ve attempted to use an explicit image search to filter out, ahem, questionable scenes only to find that the filter really didn’t understand that that picture was a picture of that. Oh my. We’ve also been persistently irritated by Google’s insistence that a “recommended” site for us might be this when actually we were looking for this. And the pithy things I can say about autocorrect would literally write themselves if I were using my iPhone to write this.

So, why would I, as the boxers say, lead with my nose? Because these examples are all hilarious exceptions to the rule otherwise established by the widespread adoption of these technologies. The rule (Virtual Canary Rule #4080) is that “you can absolutely teach a machine to think like a human when the human task it’s asked to replicate is a very mechanical process”. The spam filter, just like you would, sees an email from an address that does not look like a real person’s address or a message with a suspiciously generic subject and it trashes them. And, when it first gets started, you know that it’s wise to keep an eye on it, or at least to check when an email you expect never arrives. If you find something that you value more than the machine predicted you would, you say to it, “this is not spam”. At that point, it writes a new rule for itself and no longer trashes emails from that source. The machine has learned to think like you. And you rejoice. What’s more, when you went to look for the missing email, you saw exactly what had been going on the spam filter all this time without your input. And again, you rejoiced: you never had to look at all that garbage with your precious human eyes.

And that, my friends, is predictive coding. Truly the future is here and, as always, it turns out that it’s been here we us all along. When we talk about “Technology Assisted Review”, it’s nothing new. It’s simply litigation-grade spam filtering. You do a bit of preliminary review on a representative sample and your new high-tech best buddy (think C3PO) says, “Oh, I see, if you like these 1,000 documents as potentially relevant, then I recommend you also focus on these 10,000. You’re going to love them! And, please, don’t waste too much of your time or your client’s money on those 90,000 documents over here. I’m 98.769% sure there’s nothing there for you and I’ve put a little flag on them to remind you later.”

Next time, I’ll complete this trilogy by discussing just how the predictive coding engines work and present you with some recent case law not only validating but also mandating that we defer to the machines. Before then, please use this once amazing technology (I’m referring to the hyperlink) to transport yourself to my company’s entry into the predictive coding arena. Or, if you’d rather watch the tool in action, sign up here for a free live webinar.

As of this printing, we do still use actual humans to demonstrate the power of the tool.

In a land that is right here and in a time that is right now, a technology has arisen so powerful that it can replace basic human document review. Is it time to bow down before our new robot overlords?

First, here’s a little story about me: my life in the legal world began as a paralegal. My first case was a GIANT patent infringement case that was already six years old and had involved as many as five companies, multiple US courts, the ITC and an international standards committee. I knew nothing about any of this.

On my first day, my supervisor (a paralegal with at least eight other cases driving her crazy) sat me down in front of a Concordance database with a 100,000+ patents and patent file histories. “Code these,” she said. I learned that “coding”, for the purposes of this exercise, meant manually typing the inventor’s name, the title of the patent, the assignee, the file date, and other objective data for each document. I worked on that project – and only that project – for at least the first six months of my job. After a week or so, time began to blur.

What I know, in retrospect and with absolutely certainty, is that as time began to blur, so did my judgment. So did my attention to detail. If you could tell me that I did not make at least one mistake a day – one inconsistent spelling, one reversed day and month, one incorrectly spaced title – I frankly would need to see your evidence. I would not believe it. The human mind is trainable but it is not a machine.

After some time, I became slightly senior due to the fact that others were hired. I went on to code other projects. And then teams I managed coded other projects. Most of these projects covered the same ground: coding objective data so that the attorneys could perform subjective searches for it, maybe, someday. But, other projects were a little more advanced: we examined doc dates to determine relevancy or maybe we examined names and email addresses to determine privilege. As a bonus, if we saw something that was handwritten or that had a handwritten note, it was immediately suspect and perhaps “Attorney Work Product”.

In my personal experience, that was human coding. Moreover, the firm I worked for charged its clients for my time (billed, of course, by the hour) and for the time of my colleagues and other firms billed their clients for the time of our peers at other firms. The only explanations I have for this are that either clients were so successful that they no longer reviewed invoices or were so beaten-down by years of bills that they assumed they had no other choice. So, we continued, coding like fallible machines.

And then 2008 happened. And the bottom-line is an engine of change. Clients began to ask for the unthinkable: a better way to review documents. They began to (shudder to think) pay attention to the work folks like me were doing and weigh that against the price they were paying . . .

In the meantime, “googling” became a lower-case verb and librarians began pondering extinction. The Yellow Pages had already been reduced to a doorstop and Encyclopedia Brittanica stopped printing. Why? Because “technology” (accessed with our “computers”) now “assisted” us in “review”ing all of the information at our disposal without ever having to crack a book. The evolution of the human-computer has begun. Just ask my two-year-old, if you can pry her away from “her” iPad.

OK, why did I spend my valuable word-count discussing this? For context, friends.

And because, next time, I am going to – head on – tackle the fears that many still have of “Technology (or ‘Computer’) Assisted Review” (“TAR” or “CAR”). And hopefully instill in you an even greater fear: a fear of not embracing it. The machines are here to help us. Our poor coders are not equipped for the tasks we’ve given them. And the tasks are getting larger by the day.