My two-year old just got his first iPhone. Now, Pickle (yes, Pickle!) is never without it. The iPhone goes everywhere with him the way other kids might drag along a stuffed bear. We are even thinking about getting Pickle a haute couture fanny pack to ensure his iPhone is on him at all times.

I’ll give some of you moment to catch your breath…. Scrambling to ascend that high horse so quickly probably took a lot out of you. Yes, I am familiar with the research on screen time and brain development. I don’t care. I don’t care because we didn’t get Pickle an iPhone so we could subject him to the perverse moral dystopia of Thomas the Train.

We got him an iPhone because he was recently diagnosed as a Type 1 diabetic. The iPhone links to his continuous glucose monitor and transmits the readings to his mother and me. It alarms if Pickle’s blood sugar gets too high (so we can dose him with insulin) or too low (so we can pump him full of sugar). If you don’t think that is a good enough reason to get a two-year old an iPhone (an older model donated to us), you can take it up with my wife. Let me know how that works out for you.

Of course that means that my kid is a cyborg. How sweet is that?



Pickle’s life literally depends upon computers—a glucose monitor and an insulin pump—that are attached to him. He is a being with both organic and biomechatronic body parts. He is an organism that has restored function due to the integration of some artificial component or technology that relies on feedback. My Pickle is a cyborg.

Using the term a little more loosely, however, aren’t most of us professional cyborgs at this point? I know that I feel my ability to conduct business draining away anytime the battery life on my iPhone or laptop approaches critical level. How exactly does a modern lawyer operate without relying on modern technology?

How do you not Google? How do you exchange documents your clients without email? How do you file anything according to local court rules and efiling protocols without an entire array of hardware and software? How do you conduct a litigation of any appreciable size without some understanding of ediscovery? How do you handle divorces without knowing about Facebook? How do you complete an M&A transaction without considering IT and information assets?

You can actually be ignorant of all those things and still be an obscenely successful lawyer. The trick is to already be successful. I was in the audience a few years ago when the great Ted Olson gave the opening remarks at Legaltech. His talk was not well received because he made it clear at the outset that he considered the audience a bunch of nerds (which, to be fair, we are). After all, a yellow pad was all the legal tech he needed to be Ted freakin Olson. And that’s fine, for Ted Olson. Ted Olson is so ridiculously good at the things that Ted Olson is hired to do that no one should care that Ted Olson doesn’t use tech. If Ted Olson decided to incorporate augury into his preparation for oral argument, most clients would happily pay for the birds.

But you know who is probably using tech pretty heavily? Some of the people on Ted Olson’s team. I believe Ted Olson when he claims that he operates without any device that requires electricity. I doubt the same can be said for his team, let alone his firm. As a client, you want Ted Olson as your lawyer (if it is the kind of matter that demands Ted Olson) but you would not necessarily want Ted Olson chairing the firm’s technology committee.

Ted Olson telling a room full of legal tech folks that the only tech he needed was a legal pad would be like him telling a room full of legal marketing professionals that the only marketing he ever had to do was establish himself as one of the most prominent and successful appellate lawyers in history. True enough. But not exactly replicable at scale.

I am reflecting on this because I often get lured into pointless philosophical debates about what constitutes ‘real’ lawyering. Frankly, I am ill equipped to discuss such lofty Platonic ideals. If it affects the outcome or the bill, it is real enough for me. Delegation to associates or nonlawyers does not make it any less real or obviate the duty of oversight. (As always, I hate the term “nonlawyer” and prefer allied professional, but the ABA did not put me on the drafting committee for the model rule).

If I am feeling generous, I try to reframe what the person is saying. Usually, they are not actually arguing that tech is unnecessary. Rather, they are often expressing a belief that the tech-related work is not where lawyers add the most value. On this we almost completely agree. Which is why I find it so tragic that lawyers (and staff) waste so much time on tech-dependent activities because they have never trained to properly use the core technology tools at their disposal. We often find a place of consensus where we would both prefer a world where lawyers spent more of their finite time devoted to applying their learned judgment to solving client problems.

Sometimes, however, I discover that we are having a different discussion. It is not the one about whether lawyers should use tech. It is the complaint that while lawyers have to use tech, the tech has not lived up to the hype. Here I have even more sympathy. I’ll express it in Part 2.

Part 2 (originally a separate post because I’m trying to get more into the whole brevity thing)

Continuing with my two-year-old son, Pickle. As I laid out last post, Pickle is a cyborg. A Type 1 diabetic, his life literally depends on computers that are attached to his body. Because of him, I find myself contemplating the fact that we are almost all professional cyborgs. Technology is now an inescapable element of delivering legal services. The objection that using technology somehow differs from ‘real’ lawyering is misguided. If it affects the outcome or the bill, it is real enough.

Still, just because technology is essential does not mean it is all that good. With respect to my diabetic Pickle, I have one question: where the @#%& is his artificial pancreas?

My wife is also an insulin-deficient cyborg, I have therefore been reading the same damn story about the same pending breakthrough in closed-loop insulin delivery for over a decade (e.g., 2006, 2011, 2016). We are eternally on the cusp of the machine finally replacing humans in the labor-intensive process that is monitoring a diabetic’s blood sugar levels and delivering insulin when necessary.

Pickle has a continuous glucose monitor. But it needs to be calibrated multiple times a day. And it is not accurate enough to be relied on for dosing insulin. So the monitor does not obviate the need to regularly prick his fingers and draw blood to check sugar levels. Indeed, the best commercially available glucose monitor is actually a trained dog—the repurposing of 26,000-year-old technology and more evidence against functional fixedness. But a dog, like the monitor he actually has, cannot communicate with his insulin pump, which still needs to be run manually (i.e., we still have to direct the pump to dose insulin).

The cycles of hype and disappointment around an artificial pancreas give me quite a bit of sympathy for older lawyers who have been through many such cycles re artificial intelligence. As a stand-in for older, successful lawyers, I am going to assume a law school graduation year of 1977 since that is the median and modal graduation years of the chairs of the AmLaw 10. They have been hearing how machines were going to replace them since long before they took the bar.

If you believed the hype on artificial intelligence, it was silly for our now successful lawyer to even attend college, let alone law school. Near their high school graduation in 1970, they would have read the following in Life magazine:

In from three to eight years we will have a machine with the general intelligence of an average human being. I mean a machine that will be able to read Shakespeare, grease a car, play office politics, tell a joke, have a fight. At that point the machine will be able to educate itself with fantastic speed. In a few months it will be at genius level and a few months after that its powers will be incalculable.

Instead, their law school graduation in 1977 was at the tail end of the first AI winter—a period of reduced interest in AI due to its failure to live up to the hype.
A far cry from human-level general intelligence, the technological marvel of 1977 would be the Apple II. Poor predictions, of course, run in both directions. In reacting to the Apple II, Ken Olson, founder of Digital Equipment Corp. stated, “There is no reason anyone would want a computer in their home.”
But there is a legitimate question as to how long a prediction has to remain valid to be considered accurate. While Mr. Olson was dead wrong in the long run, a decade later, in 1987—when our successful lawyer had already made partner—only 10% of households had a personal computer. In the midst of that not-so-disruptive diffusion of computing power, important publications would continue to print pablum about the coming robot revolution. The New York Times ran stories with ledes like, “Before today’s teen-agers finish college, computers will interpret changes in tax law and plan tax strategies for business.”
Yet 1987 was also the year when economist Robert Solow observed his eponymous paradox, “You can see the computer age everywhere but in the productivity statistics.” In related news, another brutal AI winter was coming. After a resurgence in AI research and hype, the collapse of the Lisp machine market in 1987 presaged the imminent failures and fall from grace of the early expert systems, “fifth generation” computers, and the Strategic Computing Initiative. These disappointments resulted in New York Times articles like “Computer Fails as Job-Killer.”
In 1997, the machines finally won…at chess. IBM’s Deep Blue topped Gary Kasparov under tournament conditions. The press went nuts:

When Gary Kasparov beat IBM’s chess computer in 1989 he arrogantly told the programmers to “teach it to resign earlier”. Yesterday, though, the world champion found himself humbled by a 1.4-ton heap of silicone in a victory for IBM’s Deep Blue that marks a milestone in the progress of artificial intelligence. It is a depressing day for humankind in general. (here)

In brisk and brutal fashion, the I.B.M. computer Deep Blue unseated humanity (here)

Elsewhere in 1997, our successful lawyer had been a partner for more than a decade and practicing for two. The home computer market had not yet broken 40%. The still nascent home internet market had not yet cracked 20% penetration. In developments that would actually make an impact, the domain and famous spelling error was registered, almost a year before the company would be incorporated.

In 2007, our successful lawyer had been a partner for more than 20 years and practicing for 30 years. They could read increasingly more about the coming singularity and contemporary regurgitations of the Life article from 1970:

Social security will have to be expanded, introduced at lower and lower ages, till essentially everyone lives on social security. The taxes will be paid by fully-automated businesses run by robots. And human beings have to deal with the problem of excess leisure…I am afraid that the long term future we are building will have no space left for human beings…a world where we have these robots and better and better artificial intelligence, where systematically those systems replace humans, human services, human work…Is it a good or bad thing if robots become our natural successors and we fade into extinction?

But evidence of true machine intelligence outside of very narrow domains like chess remained illusory. As a practical matter, the tangible breakthroughs were mostly about being able to take the office with you everywhere. In 2007, Blackberries were a thing, and Apple announced the iPhone.

We are closing in on 2017 when our successful lawyer will celebrate 40 years in practice with more than 30 of those years as a partner. Much closer to the end of their career than the beginning, they can still read the same damn story about their imminent obsolescence. Or they can read the counterprogramming. We should forgive them for being a bit skeptical.

Yet there is something disingenuous about my account. It is accurate, as far as it goes. But it is also needlessly reductive in a way that I think is best captured by the incomparable xkcd:

Returning to my understandable focus on the perpetual promise of the artificial pancreas. In fixating on a closed system that eliminates the human factor post installation, I miss the genuine progress being made. What used to be a death sentence is now an inconvenience. And that inconvenience has gotten considerably easier to manage now that we can do things like monitor my son’s blood sugar remotely on a watch—continuous glucose monitor links to his iPhone; his iPhone transmits to my wife’s iPhone; her iPhone transmits to her Apple Watch. None of those devices were commercially available when my wife was diagnosed a decade ago. That is amazing even if it is not the technological nirvana we were promised.

One way to react to hype cycles is to laugh at the peaks in hindsight. Another is to pay attention to the progress that follows:

Because the story I told above focused on the more sensational claims of machines making humans obsolete, it treated the PC, the internet, and mobile as inconsequential asides that only served to demonstrate the hyperbolic nature of the press coverage. But like a good lawyer, I could use the same facts to tell a very different story in which technology crept into every aspect of our professional lives. There will be real similarities between the immediate lived experience of a lawyer who graduated in 1977 and the one who graduates in 2017. But there will also be real differences that would have seemed like bad science fiction to someone entering an analogue professional environment four decades ago.

I think there will be an artificial pancreas soon. Machines will be able to do that one sequence of things well enough. Likewise, I suspect that machines will continue to progress at doing other things well, including some traditionally done by lawyers. But I am doubtful* that we are nearing artificial general intelligence. Focus should therefore remain directed towards the automation of tasks rather than the complete elimination of jobs. As Robin Hanson has observed, while technology gains are exponential, the impact may be linear because job power levels are distributed lognormally:

I often meet people who think that because computer tech is improving exponentially, its social impact must also be exponential. So as soon as we see any substantial social impact, watch out, because a tsunami is about to hit. But it is quite plausible to have exponential tech gains translate into only linear social impact. All we need is a lognormal distribution, as in this diagram:

Imagine that each kind of jobs that humans do requires a particular level of computing power in order for computers to replace humans on that job. And imagine that these job power levels are distributed lognormally.

In this case an exponential growth in computing power will translate into a linear rate at which computers displace humans on jobs. Of course jobs may clump along this log-computing-power axis, giving rise to bursts and lulls in the rate at which computers displace jobs. But over the long run we could see a relatively steady rate of job displacement even with exponential tech gains. Which I’d say is roughly what we do see.

For our successful lawyer, however, the felt impact of technology progress on their professional accomplishments may be less than linear, it may be negligible. This has consequences for how lawyers in position of power react to those of who emphasize that we are all cyborgs now. More on that in Part 3.

*I’m way too dumb to have a smart take on the timing of general artificial intelligence. But the implications are so profound that it almost makes them not worth talking about. It would be similar to debating how the legal profession might change if the Earth were again struck by a meteor like the one that wiped out the dinosaurs. Everything changes, and almost no one is going to care what effect it has on profits per partner. Until then, I am in Ryan’s camp. It is only AI/magic until we start to use it, then it is software. It is only a human-displacing robot until we start to rely on it, then it is a dishwasher.

Part 3 (originally a separate post)

In Part 1, I introduced the idea that we are all professional cyborgs. I used my personal experience with a diabetic toddler whose life literally depends on computers attached to his body to ruminate on how technology is so deeply intertwined with our professional lives that we often don’t even notice it. I rejected the notion that the use of technology can somehow be considered distinct from ‘real’ lawyering.

In Part 2, I compared a decade of reading that an artificial pancreas is right around the corner to the even more drawn out asymptotic dawn of artificial lawyers. I used the professional progression of a composite successful lawyer who graduated law school in 1977—the mean and modal graduation year of the chairs of the AmLaw 10—as a touchstone for comparing the various AI hype cycles to more quotidian progress that had real impact (desktop computing, the internet, mobile). I, however, concluded with the idea that the failure of technology to live up to the hype was a good reason to be skeptical of hype but a terrible reason to be skeptical of technology.

In this Part 3, I will talk about what happens when technology does live up to the hype (we stop thinking about it) and why legal technology always appears to lag behind (because it does).

Expectation Calibration and Self-Driving Technology

We pay attention to that which demands our attention. The only reason I ever think about my own pancreas working is because my son’s doesn’t. Likewise, I don’t think about my pulmonary, respiratory, or digestive systems unless something is wrong (like we only notice the miracle that is breathing when we’re congested). If my son were ever to acquire the long-promised artificial pancreas, I would stop thinking about it. Just as when he switched over to an insulin pump I stopped thinking about giving him insulin shots.

We are predisposed to focus on what the technology doesn’t do well yet. As the comedian Louis C.K. discusses in this clip—which I pilfered from this great Daniel Pollick presentation at Lexpo—our expectations ratchet up almost instantaneously:

[For those of you who didn’t watch it, Louis recounts being on one of the first planes to test in-flight wifi. It works for a while. Then the wifi goes down. The gentleman in the next seat remarks, “This is bull&^!#.” Louis jokes about the guy being mad about something not working when five minutes before he hadn’t known it existed. The guy had recalibrated his expectations that quickly. This leads to a longer reflection by Louis on how we all complain about the hassle of air travel instead of constantly marvelling at the fact that we beat gravity. We are human beings flying through the air at hundreds of miles an hour thousands of feet above the Earth, and we’re pissed off about it.]

The partner who grew up on a Dictaphone and banker boxes is not going to proceed in a state of perpetual amazement that she can access all the world’s knowledge and all of her firm’s files from a $600 computer that weighs 5 oz., fits in her pocket, and performs 120,000,000x faster than the $23,000,000 computer that weighed 600 lbs. and guided Apollo 11 to the moon. She is going to complain that the connection is slow, the battery runs down too fast, and something mission critical isn’t quite working right. Alternatively, she is not going to learn to operate the device anywhere near its capability and, on the basis of her own ignorance, conclude that the device is not all that useful. Most commonly, a little of both.

We want self-driving technology. When we get it, we stop thinking about it and recalibrate our expectations. When we get partially self-driving technology, we focus on all the driving we still have to do. We are not built to be satisfied.

We’re Running The Red Queen’s Race And We’re Always Losing

“Now, here, you see, it takes all the running you can do, to keep in the same place. If you want to get somewhere else, you must run at least twice as fast as that!”

From Carroll’s Through the Looking Glass, those who run the Red Queen’s race go as fast as they can in order to stay put. When I was growing up, grandparents expected you to send them a school picture once a year. Today, grandparents complain if you don’t post daily kid photos to Facebook. It is not just that expectations reset at warp speed. They also tend to ratchet in ways that outpace our ability to deliver.

Enterprise IT, for example, faces all manner of expectations problems due to the consumerization of technology. In the beginning of the digital era, businesses always had the best technology. People had to go into the office so they could use this or that machine. For your standard knowledge worker, the dynamic has flipped. Now most people complain that what they have at home is better than what they have at the office.

Their personal phone is newer. Not bogged down by security protocols, their personal computer is faster. Google embarrasses their enterprise search capabilities. Amazon is light years ahead on filtering functionality. Dropbox seems better for document management. The result is incessant complaining and dangerous forays into shadow and stealth IT. People want something that works, now. They don’t care to hear about systems integration or that Apple took years to offer its consumer-targeted iPhone with enterprise-level security controls. IT can’t win, they can only try to keep up.

Arguably, legal has it even worse. Our technology is often reactive. We didn’t know we needed virtual deal rooms or electronic discovery until enterprise data volumes had already exploded. We were ‘late’ on information governance, social media, cybersecurity, privacy, BYOD, etc. because there was no role for us to play until there was role for us to play, at which point we were in perennial catch-up mode.

Relative to any time in the past, our tech is greatly improved. Relative to our actual reference classes—(i) what is available on the consumer market and (ii) the scale of the task at hand—the tech we notice is almost invariably deficient.

Real Lawyers Didn’t Need Tech To Be Successful

This is not where I launch into a diatribe about older people not getting tech. I consider such thinking to be lazy, essentialist nonsense. Older people invented tech. Being an impostor, I know many people, some of them lawyers, who are older and considerably more tech savvy than me. Oh, and the digital native is a load of malarkey.

Yet that older people are entirely capable of getting tech does not mean that they do. Some do. Many don’t. And many who don’t are wildly successful. You can be a successful lawyer without tech having much of a felt impact on your career, let alone contributing in any discernible way to your success.

The lawyer who graduated in 1977 probably made partner in 1985, a year Bruce MacEwen recently recalled:

Second, the staff:lawyer ratios today would be unrecognizable to a time traveler from, say, 1985. They might be tempted to protest, “how can we afford to pay lawyers to type?” Don’t scoff; an early and terminally benighted boss of mine uttered those unforgettable words to me in about that very year, when I offered to bring in my own very primitive DOS-based, green-screen IBM PC clone on which I’d taught myself WordPerfect.

Things have changed since 1985. But they have changed far more at the bottom than at the top of the pyramid where our successful lawyer now resides. In many respects, our successful lawyer may be like Bruce’s hypothetical time traveler. They sometimes visit the tech-centric inner workings of their firm, but they find it alien and have no need to live there.

I promise to someday explore some of the ramifications of this social distance. But today is not that day.

D. Casey Flaherty is a legal operations consultant who worked as both outside and inside counsel. Find more of his writing here. Connect with Casey on Twitter and LinkedIn. Or email

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Photo of Casey Flaherty Casey Flaherty

I am the co-founder and chief strategy officer at LexFusion, the go-to-market collective of legal innovation companies (tech and services). I am also the co-founder of Procertas (competency-based tech training). I was a BigLaw litigator and then in-house counsel who went into…

I am the co-founder and chief strategy officer at LexFusion, the go-to-market collective of legal innovation companies (tech and services). I am also the co-founder of Procertas (competency-based tech training). I was a BigLaw litigator and then in-house counsel who went into legal operations consulting before one of my BigLaw consulting clients hired me full-time to help them build the biggest and best legal project management team in world. A Lean Six Sigma black belt, I tend to think in terms of scalable systems that properly leverage people through process and technology. I am deeply experienced in legal operations, legal tech, strategic sourcing, process improvement, systems re-engineering, and value storytelling, in addition to spending over a decade in the legal trenches as a practitioner. I’ve long served  as a mesh point between law departments and law firms to promote structured dialogue that fosters deep supplier relationships (read about that here). I am a regular writer and speaker on practical legal innovation.