Do you ever wonder why some gifted small children play Mozart, but you never see any child prodigy lawyers who can draft a complicated will?

The reason is that the rules of how to play the piano have far fewer permutations and judgment calls than deciding what should go into a will. “Do this, not that” works well with a limited number of keys in each octave. But the permutations of a will are infinite. And by the way, child prodigies can play the notes, but usually not as soulfully as an older pianist with more experience of the range of emotions an adult experiences over a lifetime.

You get to be good at something by doing a lot of it. You can play the Mozart over and over, but how do you know what other human beings may need in a will, covering events that have yet to happen?

Not by drafting the same kind of will over and over, that’s for sure.

Reviewing a lot of translations done by people is the way Google Translate can manage rudimentary translations in a split second. Reviewing a thousand decisions made in document discovery and learning from mistakes picked out by a person is the way e-discovery software looks smarter the longer you use it.

But you would never translate a complex, nuanced document with Google Translate, and you sure wouldn’t produce documents without having a partner look it all over.

The craziness that can result from the mindless following of rules is an issue on the forefront law today, as we debate how much we should rely on artificial intelligence.

Who should bear the cost if AI makes a decision that damages a client? The designers of the software? The lawyers who use it? Or will malpractice insurance evolve enough to spread the risk around so that clients pay in advance in the form of a slightly higher price to offset the premium paid by the lawyer?

Whatever we decide, my view is that human oversite of computer activity is something society will need far into the future. The Mozart line above was given to me by my property professor in law school and appeared in the preface of my book, The Art of Fact Investigation.

The Mozart line is appropriate when thinking about computers, too. And in visual art, I increasingly see parallels between the way artists and lawyers struggle to get at what is true and what is an outcome we find desirable. Take the recent exhibition at the Metropolitan Museum here in New York, called Delirious: Art at the Limits of Reason, 1950 to 1980.

It showed that our struggle with machines is hardly new, even though it would seem so with the flood of scary stories about AI and “The Singularity” that we get daily. The show was filled with the worrying of artists 50 and 60 years ago about what machines would do to the way we see the world, find facts, and how we remain rational. It seems funny to say that: computers seem to be ultra-rational in their production of purely logical “thinking.”

But what seems to be a sensible or logical premise doesn’t mean that you’ll end up with logical conclusions. On a very early AI level, consider the databases we use today that were the wonders of the world 20 years ago. LexisNexis or Westlaw are hugely powerful tools, but what if you don’t supervise them? If I put my name into Westlaw, it thinks I still live in the home I sold in 2011. All other reasoning Westlaw produces based on that “fact” will be wrong. Noise complaints brought against the residents there have nothing to do with me. A newspaper story about disorderly conduct resulting in many police visits to the home two years ago are also irrelevant when talking about me.[1]

The idea of suppositions running amok came home when I looked at a sculpture last month by Sol LeWitt (1928-2007) called 13/3. At first glance, this sculpture would seem to have little relationship to delirium. It sounds from the outset like a simple idea: a 13×13 grid from which three towers arise. What you get when it’s logically put into action is a disorienting building that few would want to occupy.

As the curators commented, LeWitt “did not consider his otherwise systematic work rational. Indeed, he aimed to ‘break out of the whole idea of rationality.’ ‘In a logical sequence,’ LeWitt wrote, in which a predetermined algorithm, not the artist, dictates the work of art, ‘you don’t think about it. It is a way of not thinking. It is irrational.’”

Another wonderful work in the show, Howardena Pindell’s Untitled #2, makes fun of the faith we sometimes have in what superficially looks to be the product of machine-driven logic. A vast array of numbered dots sits uneasily atop a grid, and at first, the dots appear to be the product of an algorithm. In the end, they “amount to nothing but diagrammatic babble.”

Setting a formula in motion is not deep thinking. The thinking comes in deciding whether the vast amount of information we’re processing results in something we like, want or need. Lawyers would do well to remember that.

[1] Imaginary stuff: while Westlaw does say I live there, the problems at the home are made up for illustrative purposes.

Anyone following artificial intelligence in law knows that its first great cost saving has been in the area of document discovery. Machines can sort through duplicates so that associates don’t have to read the same document seven times, and they can string together thousands of emails to put together a quick-to-read series of a dozen email chains. More sophisticated programs evolve their ability with the help of human input.

Law firms are already saving their clients millions in adopting the technology. It’s bad news for the lawyers who used to earn their livings doing extremely boring document review, but good for everyone else. As in the grocery, book, taxi and hotel businesses, the march of technology is inevitable.

Other advances in law have come with search engines such as Lexmachina, which searches through a small number of databases to predict the outcome of patent cases. Other AI products that have scanned all U.S. Supreme Court decisions do a better job than people in predicting how the court will decide a particular case, based on briefs submitted in a live matter and the judges deciding the case.

When we think about our work gathering facts, we know that most searching is done not in a closed, limited environment. We don’t look through a “mere” four million documents as in a complex discovery or the trivial (for a computer) collection of U.S. Supreme Court cases. Our work is done when the entire world is the possible location of the search.

A person who seldom leaves New York may have a Nevada company with assets in Texas, Bermuda or Russia.

Until all court records in the U.S. are scanned and subject to optical character recognition, artificial intelligence won’t be able to do our job for us in looking over litigation that pertains to a person we are examining.

That day will surely come for U.S records, and may be here in 10 years, but it is not here yet. For the rest of the world, the wait will be longer.

Make no mistake: computers are essential to our business. Still, one set of databases including Westlaw and Lexis Nexis that we often use to begin a case are not as easy to use as Lexmachina or other closed systems, because they rely on abstracts of documents as opposed to the documents themselves.

They are frequently wrong about individual information, mix up different individuals with the same name, and often have outdated material. My profile on one of them, for instance, includes my company but a home phone number I haven’t used in eight years. My current home number is absent. Other databases get my phone number right, but not my company.

Wouldn’t it be nice to have a “Kayak” type system that could compare a person’s profile on five or six paid databases, and then sort out the gold from the garbage?

It would, but it might not happen so soon, and not just because of the open-universe problem.

Even assuming these databases could look to all documents, two other problems arise:

  1. They are on incompatible platforms. Integrating them would be a programming problem.
  2. More importantly, they are paid products, whereas Kayak searches free travel and airline sites. In addition, they require licenses to use, and the amount of data you can get is regulated by one of several permissible uses the user must enter to gain access to the data. A system integration of the sites would mean the integrator would have to vet the user for each system and process payment if it’s a pay-per-use platform.

These are hardly insurmountable problems, but they do help illustrate why, with AI marching relentlessly toward the law firm, certain areas of practice will succumb to more automation faster than others.

What will be insurmountable for AI is this: you cannot ask computers to examine what is not written down, and much of the most interesting information about people resides not on paper but in their minds and the minds of those who know them.

The next installment of this series on AI will consider how AI could still work to help us toward the right people to interview.

By now, if a lawyer isn’t thinking hard about how automation is going transform the business of law, that lawyer is a laggard.

You see the way computers upended the taxi, hotel, book and shopping mall businesses? It’s already started in law too.  As firms face resistance over pricing and are looking to get more efficient, the time is now to start training people to work with – and not in fear of – artificial intelligence.

And be not afraid.
And be not afraid

There will still be plenty of lawyers around in 10 or 20 years no matter how much artificial intelligence gets deployed in the law. But the roles those people will play will in many respects be different. The new roles will need different skills.

In a new Harvard Business Review article (based on his new book, “Humility is the New Smart”) Professor Ed Hess at the Darden School of Business argues that in the age of artificial intelligence, being smart won’t mean the same thing as it does today.

Because smart machines can process, store and recall information faster than any person, the skills of memorizing and recall are not as important as they once were. The new smart “will be determined not by what or how you know but by the quality of your thinking, listening, relating, collaborating and learning,” Hess writes.

Among the many concrete things this will mean for lawyers are two aspects of fact investigation we know well and have been writing about for a long time.

  1. Open-mindedness will be indispensable.
  2. Even for legal research, logical deduction is out, logical inference is in.

Hess predicts we will “spend more time training to be open-minded and learning to update our beliefs in response to new data.” What could this mean in practice for a lawyer?

If all you know how to do is to gather raw information from a limited universe of documents, or perhaps spend a lot of time cutting and pasting phrases from old documents onto new ones, your days are numbered. Technology-assisted review (TAR) already does a good job sorting out duplicates and constructing a chain of emails so you don’t have to read the same email 27 times as you read through a long exchange.

But as computers become smarter and faster, they are sometimes overwhelmed by the vast amounts of new data coming online all the time. I wrote about this in my book, “The Art of Fact Investigation: Creative Thinking in the Age of Information Overload.”

I made the overload point with respect to finding facts outside discovery, but the same phenomenon is hitting legal research too.

In their article “On the Concept of Relevance in Legal Information Retrieval” in the Artificial Intelligence and Law Journal earlier this year,[1] Marc van Opijnen and Cristiana Santos wrote that

“The number of legal documents published online is growing exponentially, but accessibility and searchability have not kept pace with this growth rate. Poorly written or relatively unimportant court decisions are available at the click of the mouse, exposing the comforting myth that all results with the same juristic status are equal. An overload of information (particularly if of low-quality) carries the risk of undermining knowledge acquisition possibilities and even access to justice.

If legal research suffers from the overload problem, even e-discovery faces it despite TAR and whatever technology succeeds TAR (and something will). Whole areas of data are now searchable and discoverable when once they were not. The more you can search, the more there is to search. A lot of what comes back is garbage.

Lawyers who will succeed in using ever more sophisticated computer programs will need to remain open-minded that they (the lawyers) and not the computers are in charge. Open-minded here means accepting that computers are great at some things, but that for a great many years an alert mind will be able to sort through results in a way a computer won’t. The kind of person who will succeed at this will be entirely active – and not passive – while using the technology. Anyone using TAR knows that it requires training before it can be used correctly.

One reason the mind needs to stay engaged is that not all legal reasoning is deductive, and logical deduction is the basis for computational logic. Michael Genesereth of Codex, Stanford’s Center for Legal Informatics wrote two years ago that computational law “simply cannot be applied in cases requiring analogical or inductive reasoning,” though if there are enough judicial rulings interpreting a regulation the computers could muddle through.

For logical deduction to work, you need to know what step one is before you proceed to step two.  Sherlock Holmes always knew where to start because he was the character in entertaining stories of fiction. In solving the puzzle he laid it out in a way that seemed as if it was the only logical solution.

But it wasn’t. In real life, law enforcement, investigators and attorneys faced with mountains of jumbled facts have to pick their ways through all kinds of evidence that produces often mutually contradictory theories. The universe of possible starting points is almost infinite.

It can be a humbling experience to sit in front of a powerful computer armed with great software and connected to the rest of the world, and to have no idea where to begin looking, when you’ve searched enough, and how confident to be in your findings.

“The new smart,” says Hess, “will be about trying to overcome the two big inhibitors of critical thinking and team collaboration: our ego and our fears.”

Want to know more about our firm?

  • Visit charlesgriffinllc.com and see our two blogs, this one and The Divorce Asset Hunter;
  • Look at my book, The Art of Fact Investigation (available in free preview for Kindle at Amazon). There is a detailed section on logic and inference in the law.
  • Watch me speak about Helping Lawyers with Fact Finding, here. We offer training for lawyers, and I speak across the country to legal groups about the proper mindset for legal inquiry.
  • If you are member of the ABA’s Litigation Section, see my piece in the current issue of Litigation Journal, “Five Questions Litigators Should Ask: Before Hiring an Investigator (and Five Tips to Investigate It Yourself). It contains a discussion of open-mindedness.

[1] van Opijnen, M. & Santos, C. Artif Intell Law (2017) 25: 65. doi:10.1007/s10506-017-9195-8

 

One lawyer we know has a stock answer when clients ask him how good their case is: “I don’t know. The courts are the most lawless place in America.”

What he means is that even though the law is supposed to foster predictability so that we will know how to act without breaking our society’s civil and criminal rules, there is a wide variety of opinion among judges even in the same jurisdictions about the matters that make or break a case on its way to a jury.

Our friend’s answer came to mind while reading an interesting roundup of experienced trial lawyers over the weekend about why the trial of Bill Cosby outside Philadelphia resulted in a deadlocked jury and mistrial, announced on Saturday.

In the New York Times, the attorneys mostly fell into two camps: those who thought lead witness Andrea Constand presented the jury with credibility problems because of inconsistent testimony, and those who thought the judge’s decision to limit the admission of evidence of many other similar allegations substantially weakened the prosecution’s case.

My view is that the two reasons are linked: evidence that many women have made claims similar to Constands’ could easily have overcome the credibility problem if the jury had been able to hear about many of the other women who alleged Cosby had drugged and had sexual contact with them too.

In another case with identical facts and a different judge, the other accusers may have made it in a great example of two things we tell clients all the time:

  1. Persuasive evidence is good, but admissible evidence is what you really want when you know you’re going to trial.
  2. A lot of legal jobs are now being done by computers, but while there are human judges they will differ the way humans always do: in a way that is never 100% predictable.

Admissibility

When we are assigned to gather facts in civil or criminal matters, all of the evidence we get must always be gathered legally and ethically. Otherwise it could easily turn out to be inadmissible. But even if you do everything right, admissibility is sometimes out of your control. The whole case can turn on it.

If all you are doing is trying to get as much information as you can without any thought of taking it to trial, then admissibility may not be much of a concern. Think about deciding whether someone is rich enough to bother suing using hearsay evidence; or finding personally damaging information that may be excluded as prejudicial, but even the thought of arguing a motion about that information would be too much for the other side to bear. It could increase the chance of a more favorable settlement for you.

In the Cosby case the information in question would have been very helpful to the prosecution.

Ordinarily the justice system doesn’t like to see evidence of other bad acts used in a case to paint a picture of  a defendant’s character. Rule 404 (b) of the Federal Rules of Evidence excludes this kind of thing, but allows admission of evidence of another act “as proving motive, opportunity, intent, preparation, plan, knowledge, identity, absence of mistake, or lack of accident.”

So the prosecution could have argued that all the other accusers making similar claims that they were drugged and subjected to sexual contact were evidence of Cosby’s intent, or a lack of accident, and may even have been seen as preparation for the time Constand went to Cosby’s home and was drugged.

But the judge wouldn’t let any of that in. In Pennsylvania, the rules in this section are tougher on the prosecution than are the federal rules. The state’s rule 404(b) (2) “requires that the probative value of the evidence must outweigh its potential for prejudice. When weighing the potential for prejudice of evidence of other crimes, wrongs, or acts, the trial court may consider whether and how much such potential for prejudice can be reduced by cautionary instructions.”

It seems that the judge was afraid that even warning the jury not to read too much into the other accusers would have prejudiced them even if he instructed them that the other accusers alone did not constitute proof of Cosby’s guilt — in this matter with Constand.

Unpredictability

The legal world is justifiably occupied in trying to figure out how to reduce costs by automating as many tasks as possible. Gathering of some facts can be automated, but not always, for the simple reason that facts are infinitely variable and therefore not wholly predictable.

Implicit in fact gathering is evaluating the facts you get, as you gather them. You are constantly evaluating because you can’t look everywhere, so promising leads get follow-up, the others don’t. Machines can scan millions of documents using optical character recognition because there are only so many combinations of letters out there. But the variety of human experience is limitless.

If machines can’t be trusted to properly evaluate someone’s story, imagine the problems if that story has never been written down. Think about all the things you would not want the world to know about you. How much of all of that has been written down? Probably very little. It was human effort alone that developed the other witnesses the prosecution wanted to call.

The only way a computer might have helped in this case would have been to predict – based on prior cases – which way the judge would rule in excluding the other evidence. Even that would be a tough program to write because these decisions turn on so many unique factors. But since judges are chosen at random, it wouldn’t have helped shape the decision about whether or not to charge Cosby.

Want to know more about our firm?

  • Visit charlesgriffinllc.com and see our two blogs, this one and The Divorce Asset Hunter;
  • Look at my book, The Art of Fact Investigation (available in free preview for Kindle at Amazon);
  • Watch me speak about Helping Lawyers with Fact Finding, here.
  • If you are member of the ABA’s Litigation Section, see my piece in the current issue of Litigation Journal, “Five Questions Litigators Should Ask: Before Hiring an Investigator (and Five Tips to Investigate It Yourself).

Step one: don’t have a manual. That’s the message in an information-packed new book about the inner workings of the SEC just after the Madoff and now largely forgotten (but just as egregious) Allen Stanford frauds.

Step 1

In his memoir of five years at the agency, former SEC Director of Investment Management Norm Champ (now back in private practice) writes that he was stunned to arrive into public service in 2010 to find that examiners had no set procedures both when looking at regulated entities or in following up on their findings.

“If SEC inspectors ever arrived at a financial firm for an examination and discovered that the firm had no manual about how to comply with federal securities laws, that firm would immediately be cited for deficiencies and most likely subject to enforcement action,” he writes in Going Public (My Adventures Inside the SEC and How to Prevent the Next Devastating Crisis).

Among his proudest achievements were instituting such procedures at the SEC, and holding accountable anyone at the SEC who begins to follow up on a whistle-blower’s report – the kind that the Commission ignored in relation to Madoff and Stanford.

We’ve written and spoken lots about our methodology for due diligence. You start from scratch and look not just to verify what you’ve been handed, but for information the person or company don’t want you to see. You don’t close investigative doors prematurely even though human nature makes you want to do just that.

Starting from scratch means that you assume nothing. You don’t assume Madoff has all those assets under management unless you check. It would have been easy to do but nobody asked. Anyone who was suspicious of the absence of an independent custodian or a major auditor similarly let it slide.

This is what we refer to as a Paint-by-Numbers investigation: the forms and relationships are all taken as givens, and all you get to do is decide on color. In Madoff’s case, the “forms” (the existence of invested money) were illusory. Who cares about the color (say, the risk profile of the “securities”) of something that doesn’t exist?

In Stanford’s case, there was lots of information he wouldn’t have been proud of. An April 2007 FINRA report on the Stanford Group Company said the firm had been found to be operating a securities business while failing to maintain its required minimum net capital.  A former employee of Stanford’s alleged in an April 2006 complaint in Florida state court that Stanford was operating a Ponzi scheme.

Without internal accountability procedures in place, did all of the people at the SEC just sit there? No. Champ (who arrived post-Madoff and Stanford) describes an agency packed with a lot of dedicated professionals but with a good bit of deadwood immune to the disciplines of the private-sector job market. As we read about the federal budget proposals that seek to cut funding at a variety of agencies, this book contains two other pertinent messages:

  1. If you could fire people in government the way you can in the private sector, it would be easier for the government to save money.
  2. That battle is so tough that most people (including Champ) just try to work with the good people they can find and leave personnel reform for someone else.

Champ makes no promises that there won’t be more Ponzi schemes, but hopes that his organizational reforms will reduce the chances. As in any due diligence, you can’t promise that you will always catch everything – only that if there are repeated indications of a problem staring you in the face (complete with former employees blowing whistles), you will follow up.

Among Champ’s recommendations for blunting the damage of the next crisis, one is especially welcome: eliminate the scandalous government sponsorship of lotteries. Lotteries are the world’s worst investment, and yet the poorest members of society spend like crazy on them, all prompted by a lot of misleading and predatory government advertising “far beyond what private businesses are allowed.”

Champ asks us to imagine what could be done with all that money people waste if it were properly invested and devoted to investor education.

We agree. The millionaires who lost with Madoff could at least have afforded $2,000 of due diligence on their investment. The poor who play the lottery and who should be saving their money are the ones who need help the most help from the SEC and from state governments that need to find a less repugnant way to raise revenue.

Want to know more?

  • Visit charlesgriffinllc.com and see our two blogs, The Ethical Investigator and the Divorce Asset Hunter;
  • Look at my book, The Art of Fact Investigation (available in free preview for Kindle at Amazon);
  • Watch me speak about Helping Lawyers with Fact Finding, here.

 

What to do when the databases you rely on start stripping out the very data you are paying for?Due diligence databases

Word in today’s Wall Street Journal that the main credit reporting firms will be removing many civil judgments and tax liens from credit reports prompts us to restate one our core beliefs:

Not only do databases routinely mix people up, they are far from complete in the information they contain.

Now, they will be even farther away from complete, because in order to list adverse information the credit reporting companies want several identifiers on each piece of information before they include it in a credit report. Even if there is only one person in the United States with a particular name, if his address and Social Security number are not included in a court filing against him, that filing may never make it onto his report. From what we’ve seen, there are almost no SSN’s in most of the filings we review.

As a result of this new policy, the credit scores of a lot of people are about to go up, says the Journal.

To answer the question posed at the top of this posting: what you do is you go after the information yourself. You (or a competent pro you hire) looks at databases and courthouse records for liens, litigation and other information people use every day to evaluate prospective associates, counterparties and debtors. If there’s enough money at stake, you may want to conduct interviews, not only with references but with people not on the resume.

The idea that databases are missing a lot is old news to anyone who stops to take a careful look.

The next time you are searching in a paid database, you may notice a little question mark somewhere around the box where you enter your search terms. Click on that and prepare to be shocked.

“Nationwide” coverage of marriage licenses may include only a handful of states, because such licenses are not public information in many jurisdictions. In other cases, the information is public but the database doesn’t include it because it’s too expensive to gather data that has not been scanned and stored electronically.

Of course, sending someone to a courthouse costs more than a few clicks performed while sitting at your desk. But does it cost more than lending to the wrong person who defaulted on a big loan six months ago?

Want to know more?

  • Visit charlesgriffinllc.com and see our two blogs, The Ethical Investigator and the Divorce Asset Hunter;
  • Look at my book, The Art of Fact Investigation (available in free preview for Kindle at Amazon);
  • Watch me speak about Helping Lawyers with Fact Finding, here.

What will it take for artificial intelligence to surpass us humans? After the Oscars fiasco last night, it doesn’t look like much.

As a person who thinks a lot about the power of human thought versus that of machines, what is striking is not that the mix-up of the Best Picture award was the product of one person’s error, but rather the screw-ups of four people who flubbed what is about the easiest job there is to imagine in show business.

Not one, but two PwC partners messed up with the envelope. You would think that if they had duplicates, it would be pretty clear whose job it was to give out the envelopes to the presenters. Something like, “you give them out and my set will be the backup.” But that didn’t seem to be what happened.

Then you have the compounded errors of Warren Beatty and Faye Dunaway, both of whom can read and simply read off what was obviously the wrong card.

The line we always hear about not being afraid that computers are taking over the world is that human beings will always be there to turn them off if necessary. Afraid of driverless cars? Don’t worry; you can always take over if the car is getting ready to carry you off a cliff.

An asset search for Bill Johnson that reveals he’s worth $200 million, when he emerged from Chapter 7 bankruptcy just 15 months ago? A human being can look at the results and conclude the computer mixed up our Bill Johnson with the tycoon of the same name.

But what if the person who wants to override the driverless car is drunk? What if the person on the Bill Johnson case is a dimwit who just passes on these improbable findings without further inquiry? Then, the best computer programming we have is only as good as the dumbest person overseeing it.

We’ve written extensively here about the value of the human brain in doing investigations. It’s the theme of my book, The Art of Fact Investigation.

As the Oscars demonstrated last night, not just any human brain will do.

Want to know more?

  • Visit charlesgriffinllc.com and see our two blogs, The Ethical Investigator and the Divorce Asset Hunter;
  • Look at my book, The Art of Fact Investigation (available in free preview for Kindle at Amazon);
  • Watch me speak about Helping Lawyers with Fact Finding, here.

There is a huge branch of the “fake news” business that gets no attention at all: the fake news consumed each day by corporate America that has nothing to do with politics, but everything to do with business – the bulk of the $18 trillion U.S. economy.Fake news investigation

We’ve been sorting through this kind of thing for years — It’s often why our clients hire us. I’ve also been talking on the subject recently in a speech called Fighting Fake News (see an excerpt here).

The everyday expression for figuring out what’s fake and what isn’t is: Due diligence. Good businesses are good at it, bad ones aren’t.

Six months ago, the term “fake news” meant false political information that the originator or spreader of the “news” knew was false. It’s hardly a new phenomenon, as the Wall Street Journal helpfully pointed out this week with Vladimir Putin’s Political Meddling Revives Old KGB Tactics.

By now, the term has been expanded to mean anything that’s partly or wholly untrue in the eye of the beholder, whether or not it was intentionally misstated.

What is corporate fake news? The massive amount of company, financial and personal information reported but never checked. Plenty of what’s put out is accurate, but a lot isn’t. Ask any public relations professional you know who will give you a frank appraisal of his business. If you issue a news release that’s well written, with nice quotes from your client, what happens to it?

In many cases, it will be printed word for word as a news story. There will be a news byline over it, but the body of the release will be all but unchanged. The “story” will be on dozens of television news department websites, in local newspapers, and then reproduced again based on that “reporting.”

Do “quality journalists” do this? Not that way.

Off the Beaten Track

But consider a company that is not sexy and attractive to Wall Street bankers or a lot of investors – perhaps a mid-sized printing company in Ohio or a private auto-parts manufacturer in Indiana. If that company issues a dull news release, the New York Times or the Chicago Tribune will almost certainly devote zero hours to verifying what’s in that news release. They may not report on the company at all.

If the company is public, you may get a couple of lines with earnings, usually in the context of “beating” or “missing” what analysts had predicted the earnings would be. Good luck relying on that. You would need to ask, are those the analysts who missed the dot-com bubble, the housing crisis, last year’s plunge in oil prices?

What are you to do then, when you are considering hiring someone who worked at one of these thinly covered companies? Or if you may want to enter into a long-term contract with one of them, or perhaps acquire one? Of what use will the “news” about the company be when you start looking?

There is another dimension to the problem aside from what the company says about itself. Company valuation is always relative to the health of its competitors, and they too have not only the same interest in promoting themselves, but also in reflecting negative news on their competitors.

If there is good news about fake news in politics today, it’s that people have heard a lot about made-up “news” sites, and reputable news outlets have devoted resources to reporting on them. Whatever your political viewpoint, there are plenty of places to go that will scrutinize the other side’s speeches and writings.

But where do you go if you need to scrutinize a thinly-traded or private company in refrigerated freight? Printing? A company that imports socks from Italy or manganese from Africa?

If you care enough, if the issue is valuable to you, you do your own research. Just as in the political realm, you read widely from a variety of sources and make your own decision.

Gray Matter

The problem with any kind of fake news detection comes when what is said is partially true. Neither black nor white, but gray. Evaluating gray takes the kind of gray matter a computer does not offer.

In politics, we see this all the time. President Obama’s promise “If you like your doctor, you can keep your doctor” has been given evolving degrees of truthfulness ratings since the time he said it. Many people have been able to keep their doctors; many have not (absent paying several times what they used to pay).

In business, things are almost always a shade of gray. During due diligence, an interview with a person who has posted an enthusiastic recommendation of a person on LinkedIn can reveal notes of hesitancy or qualification. You can ask questions that relate to matters not covered in the recommendation.

If a company has posted wonderful earnings, in depth analysis of the figures can show you that “wonderful” can mean “better than expected, but not sustainable because the company keeps selling assets to make its numbers.” Interviews can tell you it’s a lousy place to work, which could mean something if it’s a service business and may reflect poorly on the CEO and board.

As we tell our clients all the time, if you are about to hand the keys to a $30 million business to someone, doesn’t it make sense to make a few calls about that person to people not listed as references, and to see if there are jobs not listed on the person’s resume you’re holding?

In the world of due diligence, the most damaging fake news can come from omission — the information that is never written. Our challenge is to find it.

 

Want to know more?

  • Visit charlesgriffinllc.com and see our two blogs, The Ethical Investigator and the Divorce Asset Hunter;
  • Look at my book, The Art of Fact Investigation (available in free preview for Kindle at Amazon);
  • Watch me speak about Helping Lawyers with Fact Finding, here.

A wonderful piece in the Wall Street Journal here called “The Logic of Our Fear of Flying” does a great job explaining our irrational fear of flying using concepts from math. We all know that our chances of dying in a plane crash are much lower than dying in a car accident, and yet many of us get highly stressed when our plane takes off but think nothing of getting into the car and driving at 60 miles an hour on a crowded freeway. Why?

Mathematician Eugenia Cheng explains this irrationality in three ways.

  1. Conditional probability. Our chances of being in a plane crash are low, but our chances of dying IF we are in a plane crash are high. If our car has an accident it could be a fender bender from which we emerge unharmed thanks to seatbelts and airbags.
  2. Expected values. If you may win a $300 million lottery but there are 300 million tickets sold, your expected value is $1. If you attribute the value of your life as infinity or close to it, loss of that life (despite low chances of it happening aboard your aircraft) still looks like a nearly infinite potential loss.
  3. Rate of change. On a plane you go from feeling very safe (on the ground) to very unsafe (during takeoff, one of two most dangerous times to be on a plane) in the space of a few seconds. The faster the rate of change of the chance of disaster, the more anxious Cheng becomes.

I read this article and thought about another risk assessment problem I talk about when I speak to lawyers and lenders around the country about my book, The Art of Fact Investigation.

It’s the paradox that companies are happy to risk handing millions of dollars a year to a relatively unknown new hire who will run a part of their business worth hundreds of millions of dollars, and that they do this while insisting that to spend more than $2,000 on a background check of that person is too expensive.

Why do people take a chance (that they will lose their company millions) when for a thousand or two they could reduce the chances of disaster?

  1. Conditional probability. As with car accidents, there is low conditional probability that an employee who doesn’t work out is so awful that he takes down the entire company. Hiring an MBA to run your company is not the same thing as hiring a convicted murderer on probation to do any kind of job.
  2. Expected values. If you characterize the downside of a bad hire as a “bad fit” at the job that can be remedied, then you as the hiring decision-maker won’t get as much blame as if you had hired the next Nick Leeson who ruins you and everyone you work with.
  3. Rate of change. When an employee officially “doesn’t work out” it’s usually not a surprise event but a combination of factors that have built over time. Perhaps there has been high turnover of people under that person or a string of underperforming quarters, until the company decides that person doesn’t work. The Nick Leeson rate of change (from hero to zero overnight) is rare.

In mathematical terms, then, skimping on due diligence is explainable.

Still, imagine that for some reason the air crash statistics of individual airlines were not easily available, but for $2,000 every three years you could subscribe to a service that would tell you that Aeroflot crashes a lot more per mile travelled than Qantas.

Flying on Aeroflot is still safer than driving on July 4, but many of us would probably renew our subscriptions.

Any traveler challenged on paying this kind of money for such information would tell you, “I’m just doing my due diligence.”

Want to know more?

  • Visit charlesgriffinllc.com and see our two blogs, The Ethical Investigator and the Divorce Asset Hunter;
  • Look at my book, The Art of Fact Investigation (available in free preview for Kindle at Amazon);
  • Watch me speak about Helping Lawyers with Fact Finding, here.