My Big Law Student Loan Debt

A college graduate without student loan debt is akin to reading a kind quote about Kim Kardashian in a tabloid—it’s rare.

In the past eight years, student loan debt has nearly tripled to a whopping $1.1 trillion, and in the past 10 years, the percentage of 25-year-olds with such debt has risen from 25% to 43%

It’s gotten so bad, in fact, that New York Fed economists warned last month that the burden of student debt could stilt consumer spending by twentysomethings, as well as further hamper the recovery of the housing market and economy.

To get a better idea of what massive student loan debt (we’re talking over $100,000 massive) looks like, we talked to an attorney who graduated with a large student loan debt. We also consulted LearnVest Planning Services CFP® Katie Brewer to see just how their repayment plans stack up.

S. Fischer, 36, Attorney
Graduated: 2001
How Much I Borrowed: $100,000
What I Still Owe: $45,000

When I was 21, I had no real concept of money. I’d lived off my parents as a college student, and anything that I made from part-time jobs was “fun money.” So the amount of student loan debt that I was accruing seemed very abstract. Not to mention that I really bought into the idea that large student loans are an “investment” in law school, and they’ll pay off in the form of money! money! money! upon graduation.Unfortunately, that wasn’t the case for me. I went to a private “regional” law school (that’s a euphemism for a bottom-tier school, according to the rankings) that nobody outside of Florida has heard of because it was the only school that accepted me.

So every month, $308.19 comes out of my checking account, which is a lot considering that I make only about $55,000 a year. My salary is about 40% less than what most attorneys with my years of experience typically make because I don’t work for a private firm—I believe quality of life is as important as quality of work.

The culture of the legal profession is to never talk about your student loan debt because most people who’ve paid it off are resented by contemporaries who haven’t. But I am comforted in the knowledge that if I run into tough times, I can always defer the loans—while accumulating interest, of course. And since the interest rate is low at 2.875%, I’m not scrambling to pay it off.

What Katie Says: Shane is correct when he says that his interest rate is great—under 3% is fantastic—but I would caution him not to get too comfortable with those loans. He mentioned that he’s also thinking about paying down his mortgage faster, and saving for retirement and travel, which is smart, but I’d recommend that he keep the 50/20/30 rule in mind. At least 20% of his income should go toward financial priorities, which includes savings and debt repayment.

Have questions about your student loan?
At LearnVest, our goal is to arm you with the unbiased information you need to make the best financial decisions possible. The LearnVest website is full of expert advice, tips, tools and the latest news and more to help you make the most of your money. Visit LearnVest and create a free account today.

Information shown is for illustrative purposes only and is not intended as investment advice. Please consult a financial advisor for advice specific to your financial situation.

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It’s the time of year when law students assess their transfer opportunities, perhaps to focus on a specific area at another school, to spend a visiting year, or to better manage the financial demands of law study.

If you’re thinking along those lines, Arizona Law is worth a long look.

For 98 years, we’ve offered students one of the most highly individualized programs in the country, with faculty who love to teach and are leaders in their fields, and an increasingly national – even international – alumni base. While maintaining a strong core, we’ve kept in touch with the changing landscape of legal education and practice.

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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.

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Ed. note: The Asia Chronicles column is authored by Kinney Recruiting. Kinney has made more placements of U.S. associates, counsels and partners in Asia than any other recruiting firm in each of the past six years. You can reach them by email:

We currently have a number of active openings for associate roles at US and UK firms in HK / China, Singapore and two new in-house openings. As always, please feel free to reach out to us at in order to get details of current openings in Asia, as well as to discuss the Asia markets in general and what we expect for openings later this year. Our Evan Jowers and Robert Kinney will be in Beijing the week of March 25 and Evan Jowers will be in Hong Kong the week of April 1, if you would like to meet them in person.

The US associate openings we have in law firms are in the usual areas of M&A, cap markets, FCPA / white collar litigation, finance, and project finance. The most urgent of our top tier (top 15 US or magic circle) law firm openings in Asia (among many other firm openings that we have in Asia) are as follows:

• 2nd to 5th year mandarin fluent M&A associates needed in Beijing and Hong Kong at several firms;
• Korean fluent 2nd to 4th year cap markets associate needed in Hong Kong;
• 2nd to 5th year Japanese fluent M&A associates needed in Tokyo;
• 4th to 6th year mandarin fluent cap markets associate needed in Hong Kong;
• 2nd to 4th year M&A / cap markets mix associate needed in Singapore.

Also, we have the two below in-house openings:

In-House position at hedge fund in Singapore (3 to 4 years experience)

This position is at a growing and well known hedge fund, founded several years ago, in Singapore, which is looking to hire its first in-house counsel. The new hire will likely come from a top US or UK firm in Singapore or Hong Kong, but they will consider candidates from other markets. The role will be compliance heavy so significant compliance experience, preferably dealing with funds, is a must. Compensation will be at around the current top law firm associate comp level of the new hire.

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The last time I flapped my wings your way, I tried to make at least enough noise about your mobile phone to make you more than a little bit uncomfortable.  I hope I did.  If enough of us become anxious enough about the known and unknown unknowns and knowns in our mobile phones, then we can start making wise decisions about how to manage that information and its resultant investigations.

Today, I’d like to put a finer point on the last installment’s topic by asking a question that seemed to catch most attendees off-guard at a conference panel that I moderated last week:  is there discoverable personal information in a mobile app?  Our panelists’ answer was a uniform “yes” with one stating that, if he had to choose only one type of data that he could discover from a mobile phone, he’d choose app data.  Why?  Because there’s simply so much of it and because almost all of it is objective – not just user-created like an email – but machine-tracked like GPS, usage duration, log in and log out times, browsed web addresses, browsed actual addresses.   Also, most of us seem to have the idea that data doesn’t actually “stick” to our mobile devices the way it “sticks” to our hard drives.  Maybe there’s a disconnect based on the fact that our phones are mobile so we assume the data is mobile to?  That it “mobilizes” its way out of discoverability?  I’m not sure.  But I know that I was wrong about this too, until I attended the right webinar on a day when I was able to listen.  And I know that when we think we aren’t leaving much of a footprint, we are not terribly careful about where we step.

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