The Importance of Witness Interviews: ‘What Happens in Vegas Shouldn’t Stay in Vegas’

September 16, 2018

A discovery order in Vegas shows the importance of witness interviews and what can happen when you take a cavalier attitude towards preservation. Small v. University Medical CenterCase No. 2:13-cv-0298-APG-PAL (D.C. Nev., 9/9/18) (FLSA class action seeking unpaid wages for skipped meal breaks). The lengthy order is entitled Report and Recommendation and Final Findings of Fact and Conclusions of Law and imposes severe sanctions on the defendant. The order proves, when it comes to e-discovery at least, what happens in Vegas doesn’t stay in Vegas. The truth does and should come out, including where’s the electronic evidence. Interviews are a good way to find out what really happened.

This is a long blog – 5,122 words – but it is still a lot shorter than the 123 page Short opinion, which is not short at all. I counted, it is 48,980 words. Not that I’m complaining, but it is one of the longest discovery orders I have ever read. It has many good instructional elements. Specialists should probably read and skim the whole opinion.

The Short opinion also has the distinction of having taken longer to prepare than any other discovery order I have ever read – FOUR YEARS! Can you imagine any decision taking that long? I am sure there were good reasons, but still. That is a full presidential term.

First Steps of e-Discovery: Prepare and Preserve

The FLSA suit arose from a DOL investigation that faulted the defendant employer hospital, UMC, for failing to keep “accurate records” of the time worked. UMC’s alleged records failures continued after it was sued. They failed to give timely preservation notices and failed to interview key custodians. That’s a failure of the first two legal tasks a lawyer is required to do in Electronic Discovery Best Practices (EDBP), steps two and three (step one is prepare). See EDBP.com (detail shown above right with all ten legal activities shown below); also see: Favro, Phillip, Vegas Court Spotlights the Importance of Custodian Interviews with New ESI Sources (LegalTech News 8/30/18) (further discussed below); John Patzakis, Three Key eDiscovery Preservation Lessons from Small v. University Medical Center (Next Generation eDiscovery Blog, 9/12/18).

Judge Peggy Leen’s Order

Magistrate Judge Peggy A. Leen is the learned judge who wrote the opinion in Small v. University Medical Center, Report and Recommendation and Final Findings of Fact and Conclusions of Law. The order affirms and implements most of the recommendations of the Special Master for e-Discovery appointed several years ago in this case, Daniel Garrie.

The Special Master’s Report was issued four years earlier on August 18, 2014, two years after the suit was filed in July 2012. The Report was notable for characterization of defendant’s discovery misconduct as so egregious as to “shock the conscience” and make “a mockery of the orderly administration of justice.” It was a long, complicated report.

When she completed her work she ruled in large part for the plaintiffs and  sanctioned the defendant:

VI. THE COURT’S FINDINGS AND CONCLUSIONS

The court has personally conducted a thorough review of the record prior to the special master’s appointment and the record of the proceedings conducted by the special master. The record before the court and the record developed by the special master amply supports his findings that UMC destroyed evidence by failing to identify, preserve, collect, process, and search multiple repositories of information relevant to the parties’ claims and defenses.

UMC failed to preserve several different types of ESI, including an estimated 26,000 text messages and 38,000 documents from a shared drive “containing human resources, corporate compliance, employee grievance, payroll, and DOL investigation data.” The documents lost include important policy and procedure manuals regarding meal breaks and compensation. Relevant ESI on laptops, desktops and local drives were not preserved until some 18 months into the litigation. UMC also failed to comply with multiple discovery orders, leading to the plaintiffs’ motions for sanctions.

Judge Leen did not follow the recommendation of the Special Master to impose a sanction of default judgment in favor of 613 class members on the Fair Labor Standards Act claims. Instead, she imposed a permissive adverse inference jury instruction, along with monetary sanctions. These jury instructions can have a profound impact on the jury, but not as  strong as a mandatory adverse inference instruction. The mandatory instruction almost always leads to a verdict against the spoliating party. The permissive kind of instruction imposed here still gives a defendant like UMC a chance. The sanctioned party can still prevail with a jury on the merits of the case, albeit a slim chance. Here is the specific language that Judge Leen suggested be used at trial with the jury:

2. UMC is sanctioned in the form of an instruction to the jury that the court has found UMC failed to comply with its legal duty to preserve discoverable information, failed to comply with its discovery obligations, and failed to comply with a number of the court’s orders. The instruction will provide that these failures resulted in the loss or destruction of some ESI relevant to the parties’ claims and defenses and responsive to plaintiffs’ discovery requests, and that the jury may consider these findings with all other evidence in the case for whatever value it deems appropriate.

Careful study of the long opinion shows a very practical, albeit unstated reason for Judge Leen to make this concession. It made her order much harder to appeal; some would say appeal-proof. (After you put four years into something you want it to last.) That is because near the end of the process at one of the hearings Judge Leen was able to get defendant’s own attorney to concede that an adverse inference jury instruction would be appropriate. You do not see that happen very often. But this attorney apparently saw the writing on the wall from the comments the judge was making and realized that accepting a permissive inference was the best they could hope for and certainly a lot better than default judgments for all 613 class members.

Here is Judge Leen’s explanation of how this admission came about.

During oral argument on its objections to the special master’s R & R, counsel for UMC stated “I’m not even going to tell you that I don’t think we shouldn’t be sanctioned.” (Hr’g Tr. 24:28-25:1, Oct. 21, 2014, ECF No. 229.) When asked what sanction he felt was appropriate based on the developed record, UMC’s counsel suggested that an adverse inference jury instruction would be appropriate. (Tr. 25:4-10.)

Here we see a wise and experienced judge in action. Too bad Peggy Leen retires in 2019.

Judge Leen had good reason under the law to hesitate to enter default judgments on 613 claims, effectively ending the cases except to determine the amount of damages, all without any hearing on the merits of the claims. Entry of the  lesser sanction of a permissive instruction was consistent with Judge Leen’s analysis of Rule 37(b) on sanctions for violation of court orders.

[T]he court cannot conclude that UMC’s multiple discovery failures and failure to comply with the court’s orders threatens to interfere with the rightful decision of this case on the merits.

The lesser sanction was also consistent with her analysis of 2015 revisions to Rule 37(e) on sanctions for ESI spoliation, Rule 1 on just-speedy-inexpensive, and Rule 26(b)(1) on proportionality. Here is Judge Leen’s well-accepted analysis of 37(e):

To summarize, the court may impose sanctions against UMC under the current version of Rule 37(e) only if it finds: (1) UMC failed to preserve ESI “that should have been preserved” in anticipation or conduct of litigation; (2) the information was lost because UMC failed to take reasonable steps to preserve it; (3) the ESI cannot be restored or replaced; and (4) the plaintiffs were prejudiced by the loss. If all of these prerequisites are met, the court may issue sanctions no greater than necessary to cure the prejudice caused by the loss. Only if the court finds UMC acted with intent to deprive may the court impose the most severe sanctions.

Judge Leen then applied the law to the facts.

The court has found that UMC failed to preserve ESI that should have been preserved in anticipation of litigation, and throughout the course of this litigation. The court has also found that the information was lost because UMC failed to take reasonable steps to preserve it. Thousands of text messages on UMC Blackberry devices were lost and cannot be restored. Tens of thousands of files from the Q-Drive were lost and cannot be restored prior to December 2013. . . .

However, the special master’s extraordinary expertise and persistence resulted in restoration, remediation, and production of a great deal of relevant and discoverable ESI. The special master was able to direct restoration of the time tracking systems UMC failed to disclose until near the end of special master proceedings. Fortunately, Jackie Panzeri, UMC’s payroll manager who described herself as a “pack rat” that “keeps documents forever” had a lot of documents on her personal drive and several archives full of emails she did not delete or modify. She was involved in the DOL investigation from the beginning and saved both documents collected and produced to the DOL and for this case. The court is also mindful that ESI is stored in multiple locations and that modified or lost data from the seven key custodians is likely to be found in other locations. . . .

Although the court finds plaintiffs have been prejudiced by the loss of data from key repositories and custodians, the loss has not threatened to interfere with the rightful decision of the case on its merits given the large volume of ESI the special master was able to ensure that UMC produced. For these reasons, the court finds that lesser sanctions are appropriate, proportional, and no greater than necessary to cure the prejudice caused by the loss of ESI uncovered by the special master.

As you can see, hope springs eternal. Judge Leen’s still thinks that the now lost ESI from the seven key custodians is likely to be found in other locations. 

I doubt the Special Master Garrie would share the same optimism. He has already called defendant’s conduct a mockery of the orderly administration of justice. In his Report the Special Master said he has “serious doubts that UMC can complete discovery in a defensible manner going forward without increased candor to the Court and their own counsel, and more competent technical assistance.’ Well, maybe they will change. If not, and Judge Leen is wrong and the missing ESI is not found, then Judge Lee or her successor might reconsider and upgrade the sanction to a mandatory adverse inference. Special Master Garrie may yet get his way.

Defendant’s Threshold Errors

The quotes below from Small summarize the key factual findings of defendants’ threshold errors, the ones that lead to most of the others (emphasis added), much like a domino effect. To me these are the most important errors made and you should study Judge Leen’s words here closely.

D. UMC Executives Failed to Accept Responsibility for Ensuring that ESI was Preserved and Failed to Notify Key Custodians and IT Staff to Preserve, and Prevent Loss, or Destruction of Relevant, Responsive ESI

The record amply supports the special master’s findings that UMC had no policy for issuing a litigation hold, and that no such hold was issued for the first eight months of this litigation until after Mr. Espinoza was deposed on April 8, 2013, and was asked about UMC’s response to plaintiff’s August 6, 2012 preservation letter. The special master accurately found that UMC executives were unaware of their preservation duties, ignored them altogether, or at best addressed them “in the hallway in passing.” . . .

The special master’s finding that UMC executives failed to accept responsibility for their legal duty to preserve is amply supported in the record. UMC executives and counsel failed to communicate with and provide adequate instructions to the department heads and IT personnel of repositories containing discoverable ESI to prevent the loss or destruction of potentially relevant ESI. . . .

There is no evidence in the record, and UMC does not suggest there is any, that current or former counsel gave instructions to UMC to suspend business as usual to prevent the destruction, deletion or modification of ESI responsive to plaintiffs’ discovery requests. . . .

It is also undisputed that UMC’s prior and current counsel failed to conduct timely custodian interviews. Custodian interviews were not conducted until well into the special master proceedings when it became apparent they had not been done. The special master required the interviews to be conducted a second time because the initial custodian interviews conducted by counsel were inadequate. . . .

There is ample support in the record that UMC executives displayed a cavalier attitude about their preservation obligations addressing them in passing, and that UMC executives repeatedly took the position in declarations and testimony that responsibility for preservation was someone else’s job. . . .

The special master correctly found that current and former counsel failed to conduct timely custodian interviews to identify individuals with discoverable information and key repositories of discoverable ESI.

The record in this matter is very complex and voluminous. That is why the Special Master Report and the Order by Judge Leen are so lengthy; 123 pages for the order alone. Suffice it to say, if witness interviews of key custodians been conducted when they should have, shortly after suit was filed, a great deal of relevant evidence that ultimately was lost could have been saved. The Special Master’s detailed findings make that obvious. The lost-files could have been identified and preserved unaltered. Lines of responsibility to comply with legal preservation obligations could have been clarified and enforced. Had these interviews been conducted, and the ESI found quickly, the relevant ESI could have been bulk-collected and the evidence saved from spoliation.

As it is, the actions and mistakes of defendant here have severely weakened their case. That’s what can easily happen when a company has a cavalier attitude to compliance with their legal obligation to preserve potentially relevant ESI.

Eight Failed Challenges to the Special Master’s Report

Judge Leen considered and rejected eight challenges to the Special Master’s report that were raised by the defendant employer, UMC:

  1. Competence and Impartiality of the Special Master, Daniel Garrie.
  2. UMC’s Failure to Comply with the Court’s Orders to Preserve and Produce ESI.
  3. UMC’s Failure Have a Preservation Policy or Litigation Hold Policy and Failure to Timely Implement One.
  4. UMC’s Executives Failure to Accept Responsibility for Ensuring that ESI was Preserved and Failure to Notify Key Custodians and IT Staff to Preserve, and Prevent Loss, or Destruction of Relevant, Responsive ESI.
  5. UMC’s Failure to Disclose the Existence of Relevant ESI Repositories, Including Multiple Timekeeping Systems and the Q-Drive Until Late in the Special Master Proceedings.
  6. UMC Modified, Lost, Deleted and/or Destroyed ESI Responsive to Plaintiffs’ Discovery Requests.
  7. UMC’s Failure to Comply with its Legal Duty to Preserve, Failure to Put in Place a Timely Litigation Hold, Failure to Comply with Multiple Court Orders to Preserve and Produce Responsive ESI, and Loss and Destruction of Responsive ESI (1) Necessitated the Appointment of a Special Master, (2) Caused Substantial Delay of these Proceedings, and (3) Caused Plaintiffs to Incur Needless Monetary Expenses.
  8. The Special Master Correctly Concluded UMC Repeatedly Misrepresented the Completeness of its Production of Documents Produced to DOL; However, UMC Was Not Ordered to Produce Kronos Payroll Data in Spreadsheet Format.

Defendants failed in their challenges to the Special Master’s findings, including the threshold challenge to Special Master Dan Garrie’s competence. Ouch! Garrie is a Senior Managing Partner of Law & Forensics. He has written numerous articles and books on law, technology and e-discovery. See eg. D. Garrie & Yoav Griver. Dispute Resolution and E-Discovery, Thomson Reuters (2nd ed. 2013). Garrie earned a Masters degree in computer science at Brandeis University before going on to law school. A challenge to his expertise was misplaced.

The challenge did not go over well with the supervising Judge who studied his work more closely than anyone. After emphatically rejecting the hospital arguments, Judge Peggy Leen stated:

The court has conducted a de novo review of all of the special master proceedings and finds that he was professional and courteous, if occasionally frustrated by testimony displaying a lack of appreciation of UMC’s legal duties to preserve and produce responsive ESI. He was repeatedly told by UMC executives and employees that they did not know about their duty to preserve, had not learned about their preservation obligations from counsel, did not know what a litigation hold was, and had not explored relevant repositories of information responsive to plaintiffs’ discovery requests.

Bench Slap of Defendant’s Attorneys

With a background like that it is not surprising that the Special Master uncovered so much evidence of incompetence and malfeasance in preserving evidence. Judge Leen held: (emphasis added)

UMC was on notice that its timekeeping, time systems, payroll policies, and procedures were relevant to this litigation. UMC also knew it was unable to document that employees were being compensated for actual time worked. Both UMC and its former and current counsel failed to comply with UMC’s legal duty to suspend routine document retention/destruction policies to ensure the preservation of relevant documents. UMC failed to communicate the need to preserve relevant documents and ESI to employees in possession or likely to be in possession of discoverable information, or for that matter to communicate this duty even to “key players.” UMC and its counsel failed to identify, locate, and maintain information relevant to specific, predictable, and identifiable claims involved in this litigation.

Note that Judge Leen goes out of her way to include the defendant and its lawyers in the blame, both its  prior attorneys and its present attorneys. All of these attorneys failed in the “legal duty to suspend routine document retention/destruction policies to ensure the preservation of relevant documents.” In situations of shared blame like this the attorneys involved are sometimes personally sanctioned along with the client, but this has not happen here. Judge Leen did make several sharp comments against the defendants lawyers, includi9ng this finding:

UMC’s current counsel blamed former counsel and their ESI consultants for the delay in producing responsive ESI. Counsel for UMC advised the court at the hearing on June 25, 2013, that the client did not have any real understanding of what MPP had done or what data had been collected. This representation turned out to be false. . . . Thus, the representation UMC’s current counsel made to the court that the client did not have any real idea of what prior counsel had done regarding ESI collection was patently false. In the light most favorable to current counsel, they did not ask the right questions of the individuals involved in the initial collection. The people involved in the process— MPP, its vendors and consultants, and the IT personnel at UMC who did the collection of ESI from 26 custodians—were simply not asked until after the special master was appointed and made the appropriate inquiries.

You do not see comments like that very often. Basically the judge is saying you lied to me and I cannot trust you. Again, more conscience shocking conduct by these attorneys, well outside the norm of accepted behavior.

Importance and Art of Custodian Interviews

The interviews that eventually were taken under the Special Master’s order and supervision show that critical evidence could have been saved from routine destruction, if the interviews been done at the time the suit was filed, not years later. The interviews would have ensured that preservation notices were properly given, understood and followed, and the right ESI was collected and effectively searched. See William A. Gross Construction Associates, Inc. v. American Manufacturers Mutual Insurance Co., 256 F.R.D. 134, 136 (S.D.N.Y. 2009) (custodian interviews to assist also in keyword search formulation).

It is important to note that the custodian interviews in Small had to be done twice. The attorneys botched the first attempt at witness interviews. They were ordered to do it again. I am not surprised. Many people underestimate the complexity and sophistication of interviews in cases like this. They also underestimate the wiliness of custodians and tendency of some of them to evade questions.

It is very difficult for most attorneys to conduct an interview on the subject of information storage, IT systems, company document storage systems, email, texts, other personal messaging, social media, personal computers, phones, other devices and  software programs used. Questions on these subjects are very different from questions on the merits of a case. A good custodian interview requires special technical knowledge and skills, which, unfortunately, most lawyers still lack. Too bad, because witness interviews are so very important to big cases with complex, messy ESI systems.

Philip Favro, an expert consultant for Driven, Inc., makes this point well in his excellent article on Small:

Fulsome custodian interviews are essential for ensuring that relevant electronically stored information (ESI) is preserved. Such interviews are characterized by exhaustive questioning on any number of topics including traditional and newer sources of ESI.

Properly conducted, custodian interviews should provide counsel with a thorough understanding of the nature and types of relevant information at issue in the litigation, together with the sources where that information is located. If custodian interviews are neglected or deficient, parties are vulnerable to data loss and court sanctions. The Small v. University Medical Center case is instructive on these issues.

Vegas Court Spotlights the Importance of Custodian Interviews with New ESI Sources (LegalTech News 8/30/18).

Phil’s explanation of some of the facts behind the Special Master ordered redo of the interviews shows how difficult some custodian interviews can be, especially when they want to hide something from the lawyers:

Once conducted, the interviews were deemed insufficient by the special master and (later on) the court. In its order, the court spotlighted some of the evasive answers that UMC’s custodians provided. For example, UMC’s director of human resources disclosed the existence of only one relevant timekeeping application despite having approved the use of other timekeeping systems for certain employees. UMC argued that its HR director was only obligated to disclose the timekeeping application he actually used:

[The custodian] did not use those applications himself and therefore had no obligation to disclose these systems in custodian interviews ordered by the special master because a “custodian interview is aimed at uncovering the applications, systems, programs, data with which the actual custodian interfaces.” (emphasis added).

The court decried this limited notion of a custodian interview, observing that it failed to satisfy UMC’s “legal obligation to identify, locate, maintain, and produce relevant information.”

In Small they never did any custodian interviews until after the case blew up and a Special Master was appointed. Even when interviews were finally conducted by defense counsel, they did a poor job; they were not well-informed of the client IT systems and were not “tough enough” with the interviewees. They seemed to be easily deceived and accepted evasive, incomplete answers. You must cross-examine and be the devils advocate for effective interviews, especially when the custodian is evasive.

Favro recommends:

Interviews should go beyond cursory questioning and focus instead on identifying all sources of relevant information. Nor should they be limited to safe topics like “where can relevant messages be found in your email account” or “where are relevant documents stored on your laptop.” Interviews should now include questions regarding the existence of information exchanged through new communications media or stored in online locations . . .

There is an art to interviews like this. The witnesses have to be comfortable telling you the truth, the full truth, without fear of reprisals. Assurances of confidentiality and witness protection can be a good tongue loosener, but do not mislead them. Remind them who you represent, typically at the very beginning.

Trust, friendliness and rapport are important in interviews, but fear has its place too. I like to tell the witness up front how important it is for them to be fully truthful and candid. A short, but stern formal reminder can go a long way if delivered properly. Since interviews are usually not under oath this is especially important. Some formality is important as part of the tongue-loosening process. Moreover, interviews like this are typically done one-on-one with no court reporter and no written statement for the witness to read and sign at the end. An interview is just two people talking, one asking all of the questions, preferably face-to-face and preferably in the witnesses office with their computer equipment at the ready to show you something, if need be.

To encourage full honesty and to help get at the truth I also sometimes inform a witness that they will likely be deposed and subject to intense cross-exam by opposing counsel. (I might possibly exaggerate the adversaries capabilities from time to time.) I point out how it will all be under oath and penalty of perjury. Then I start my role of the devils advocate, saying these are the kind of questions you will be asked, and then tear into them and make sure the story is straight and the memory not too patchy. Hey, do not get mad at me for pressing on you; these are the kind of questions you can expect and we have to be prepared. That works. Fear can be a powerful motivator of truth. So can good cross-exam. The carrot and stick approach is usually effective.

Another important guardian of truth is for the questioning attorneys to be able to look the witness in the eye and follow exactly what they are saying; full technical understanding of the ESI questions. Do not speak the language? Too technical? Then bring a translator, an expert. Do not allow the witness to speak over your head. They may well be bs-ing you. Nodding your head at everything said, even when you do not understand, is a natural lawyer tendency that you must fight against. Do not be afraid to ask stupid questions. When it comes to technical interviews of any kind I interrupt and ask questions all of the time. Much of the language used in tech and e-discovery is vague and subject to multiple meanings. You need to ask questions. Only a fool is afraid to ask questions for fear of seeming foolish.

Good interviews are a best practice to start e-discovery off right and protect clients from wasted expense and unnecessary risks. See the fine article on point by Kelly Twigger, 5 Things A Great Custodian Interview Can Do For Your Case And Your Budget (Above The Law, 6/27/17).

Proper custodian interviews require skill and training. They require the attorney or paralegal doing the interview to have a basic understanding of technology, communications software and social media. It can be challenging in some situations and even advanced practitioners need a good detailed outline to do it right. Make sure your law firm or law department has a good ESI custodian interview outline. I suggest having both a short and long form. These help even experienced lawyers to make sure they do not forget to ask something.

Expert consultants like Kelly Twigger of ESI Attorneys can help you to prepare good outlines and other tools. They can also do the most challenging tasks for you, such as prepare custom Preservation Notices, conduct Custodian Interviews, supervise ESI Collection, attend the 26(f) conference and prepare an ESI discovery plan, and ultimately, document search, review and production. An e-discovery expert can make it far easier and less expensive to stay current with the many technical-legal issues in the field.

A custodian interview can provide a wealth of information to help lawyers to find and save important evidence, but only if done properly by skilled legal practitioners. Do not risk the judge ordering a redo. Make sure you do a proper interview of the key custodians as soon as possible

Conclusion

Small shows what can happen when you take a cavalier attitude towards ESI preservation and interviews. Small v. University Medical CenterCase No. 2:13-cv-0298-APG-PAL, Report and Recommendation and Final Findings of Fact and Conclusions of Law dated August 9, 2018. Preservation errors at the beginning of a case can easily cascade into serious negligence and ESI destruction. This often results in sanctions motions and discovery about discovery. That diverts everyone from the merits of the case. In Small the sanctions not only included a permissive inference jury instruction, but also monetary sanctions, amount yet to be determined. What happened to the defendant in federal court in Vegas in Small is something that you should fear and loathe ever happening to you.

Proper timely custodian interviews could have prevented the loss of data in Small, could have prevented any sanctions. We all know that what happens in Vegas does not stay in Vegas, at least not when discovery in a law suit is concerned. The truth will come out as it should. This is especially true in a case like Small with misconduct that shocks the conscience in a mockery of justice, as Special Master Dan Garrie put it back in 2014.

Early custodian Interviews are an important, well-accepted best-practice, especially in a large matter like Small v. UMC. Interviews are the third step in the ten-step best practices of Electronic Discovery shown below. Electronic Discovery Best Practices (EDBP.com). They are one of three important activities that attorneys must perform in every law suit to preserve potential electronic evidence (shown in blue in the diagram below): hold notices, interviews and ESI collections.

See EDBP on Preservation.

In a large firm like mine, which only does Labor and Employment law, you can use one of the specialists in e-discovery to assist in these tasks, at least until you become proficient on your own. Specialists in large firms are usually experienced attorneys that now limit their work to e-discovery. (I recommend against specializing too early, but some are able to do it effectively.) In my firm there is only one full-time specialist, me, but I have over fifty attorney liaisons to assist. They have special training in e-discovery and are the go-to e-discovery lawyers for their office (we have 50), but they spend most of their time in employment litigation and other services outside of e-discovery. Other large firms have more full-time e-discovery specialists, but fewer part-time specialists. I decided to try to spread out the knowledge.

One of the things a specialists do, full or part-time, is help to create and update good standard witness interview question outlines for use by other attorneys in the firm. For instance, I have both a long and short form that I recently updated. Your firm probably has something similar. If not, do it now. Better late than never.

If you are in a smaller firm and do not have a full-time specialist in your ranks, then you should consider retaining an outside specialist as co-counsel in larger e-discovery matters. They can help you to save on overall costs and, most importantly, prevent a disaster like Small v. University Medical Center from ever darkening your door.

 

 

 


e-Discovery and Poetry on a Rainy Night in Portugal

April 17, 2018

From time to time I like read poetry. Lately it has been the poetry of Billy Collins, a neighbor and famous friend. (He was the Poet Laureate of the United States from 2001 to 2003.) I have been reading his latest book recently, The Rain in Portugal. Billy’s comedic touches balance the heavy parts. Brilliant poet. I selected one poem from this book to write about here, The Five Spot, 1964. It has a couple of obvious e-discovery parallels. It also mentions a musician I had never heard of before, Roland Kirk, who was a genius at musical multi-tasking. Enjoy the poem and videos that follow. There is even a lesson here on e-discovery.

The Five Spot, 1964

There’s always a lesson to be learned
whether in a hotel bar
or over tea in a teahouse,
no matter which way it goes,
for you or against,
what you want to hear or what you don’t.

Seeing Roland Kirk, for example,
with two then three saxophones
in his mouth at once
and a kazoo, no less,
hanging from his neck at the ready.

Even in my youth I saw this
not as a lesson in keeping busy
with one thing or another,
but as a joyous impossible lesson
in how to do it all at once,

pleasing and displeasing yourself
with harmony here and discord there.
But what else did I know
as the waitress lit the candle
on my round table in the dark?
What did I know about anything?

Billy Collins

The famous musician in this poem is Rahsaan Roland Kirk (August 7, 1935[2] – December 5, 1977). Kirk was an American jazz multi-instrumentalist who played tenor saxophone, flute, and many other instruments. He was renowned for his onstage vitality, during which virtuoso improvisation was accompanied by comic banter, political ranting, and, as mentioned, the astounding ability to simultaneously play several musical instruments.

Here is a video of Roland Kirk with his intense multimodal approach to music.

One more Kirk video. What a character.

____

The Law

There are a few statements in Billy Collins’ Five Spot poem that have obvious applications to legal discovery, such as “There’s always a lesson to be learnedno matter which way it goes, for you or against, what you want to hear or what you don’t.” We are all trained to follow the facts, the trails, wherever they may lead, pro or con.

I do not say either pro or con “my case” because it is not. It is my client’s case. Clients pay lawyers for their knowledge, skill and independent advice. Although lawyers like to hear evidence that supports their client’s positions and recollections, after all it makes their job easier, they also want to hear evidence that goes against their client. They want to hear all sides of a story and understand what it means. They look at everything to craft a reasonable story for judge and jury.

Almost all cases have good and bad evidence on both sides. There is usually some merit to each side’s positions. Experienced lawyers look for the truth and present it in the best light favorable for their client. The Rules of Procedure and duties to the court and client require this too.

Bottom line for all e-discovery professionals is that you learn the lessons taught by the parties notes and documents, all of the lessons, good and bad.

The poem calls this a “… joyous impossible lesson in how to do it all at once, pleasing and displeasing yourself with harmony here and discord there.” All lawyers know this place, this joyless lesson of discovering the holes in your client’s case. As far as the “doing it all at once ” phrase, this too is very familiar to any e-discovery professional. If it is done right, at the beginning of a case, the activity is fast and furious. Kind of like a Roland Kirk solo, but without Roland’s exuberance.

Everybody knows that the many tasks of e-discovery must be done quickly and pretty much all at once at the beginning of a case: preservation notices, witness interviews, ESI collection, processing and review. The list goes on and on. Yet, in spite of this knowledge, most everyone still treats e-discovery as if they had bags of time to do it. Which brings me to another Billy Collins poem that I like:

BAGS OF TIME

When the keeper of the inn
where we stayed in the Outer Hebrides
said we had bags of time to catch the ferry,
which we would reach by traversing the causeway
between this island and the one to the north,

I started wondering what a bag of time
might look like and how much one could hold.
Apparently, more than enough time for me
to wonder about such things,
I heard someone shouting from the back of my head.

Then the ferry arrived, silent across the water,
at the Lochmaddy Ferry Terminal,
and I was still thinking about the bags of time
as I inched the car clanging onto the slipway
then down into the hold for the vehicles.

Yet it wasn’t until I stood at the railing
of the upper deck with a view of the harbor
that I decided that a bag of time
should be the same color as the pale blue
hull of the lone sailboat anchored there.

And then we were in motion, drawing back
from the pier and turning toward the sea
as ferries had done for many bags of time,
I gathered from talking to an old deckhand,
who was decked out in a neon yellow safety vest,

and usually on schedule, he added,
unless the weather has something to say about it.

Conclusion

Take time out to relax and let yourself ponder the works of a poet. We have bags of time in our life for that. Poetry is liable to make you a better person and a better lawyer.

I leave you with two videos of poetry readings by Billy Collins, the first at the Obama White House. He is by far my favorite contemporary poet. Look for some of his poems on dogs and cats. They are especially good for any pet lovers like me.

One More Billy Collins video.

 


Ethical Guidelines for Artificial Intelligence Research

November 7, 2017

The most complete set of AI ethics developed to date, the twenty-three Asilomar Principles, was created by the Future of Life Institute in early 2017 at their Asilomar Conference. Ninety percent or more of the attendees at the conference had to agree upon a principle for it to be accepted. The first five of the agreed-upon principles pertain to AI research issues.

Although all twenty-three principles are important, the research issues are especially time sensitive. That is because AI research is already well underway by hundreds, if not thousands of different groups. There is a current compelling need to have some general guidelines in place for this research. AI Ethics Work Should Begin Now. We still have a little time to develop guidelines for the advanced AI products and services expected in the near future, but as to research, the train has already left the station.

Asilomar Research Principles

Other groups are concerned with AI ethics and regulation, including research guidelines. See the Draft Principles page of AI-Ethics.com which lists principles from six different groups. The five draft principles developed by Asilomar are, however, a good place to start examining the regulation needed for research.

Research Issues

1) Research Goal: The goal of AI research should be to create not undirected intelligence, but beneficial intelligence.

2) Research Funding: Investments in AI should be accompanied by funding for research on ensuring its beneficial use, including thorny questions in computer science, economics, law, ethics, and social studies, such as:

  • How can we make future AI systems highly robust, so that they do what we want without malfunctioning or getting hacked?
  • How can we grow our prosperity through automation while maintaining people’s resources and purpose?
  • How can we update our legal systems to be more fair and efficient, to keep pace with AI, and to manage the risks associated with AI?
  • What set of values should AI be aligned with, and what legal and ethical status should it have?

3) Science-Policy Link: There should be constructive and healthy exchange between AI researchers and policy-makers.

4) Research Culture: A culture of cooperation, trust, and transparency should be fostered among researchers and developers of AI.

5) Race Avoidance: Teams developing AI systems should actively cooperate to avoid corner-cutting on safety standards.

Principle One: Research Goal

The proposed first principle is good, but the wording? Not so much. The goal of AI research should be to create not undirected intelligence, but beneficial intelligence. This is a double-negative English language mishmash that only an engineer could love. Here is one way this principle could be better articulated:

Research Goal: The goal of AI research should be the creation of beneficial intelligence, not  undirected intelligence.

Researchers should develop intelligence that is beneficial for all of mankind. The Institute of Electrical and Electronics Engineers (IEEE) first general principle is entitled “Human Benefit.” The Asilomar first principle is slightly different. It does not really say human benefit. Instead it refers to beneficial intelligence. I think the intent is to be more inclusive, to include all life on earth, all of earth. Although IEEE has that covered too in their background statement of purpose to “Prioritize the maximum benefit to humanity and the natural environment.”

Pure research, where raw intelligence is created just for the hell of it, with no intended helpful “direction” of any kind, should be avoided. Because we can is not a valid goal. Pure, raw intelligence, with neither good intent, nor bad, is not the goal here. The research goal is beneficial intelligence. Asilomar is saying that Undirected intelligence is unethical and should be avoided. Social values must be built into the intelligence. This is subtle, but important.

The restriction to beneficial intelligence is somewhat controversial, but the other side of this first principle is not. Namely, that research should not be conducted to create intelligence that is hostile to humans.  No one favors detrimental, evil intelligence. So, for example, the enslavement of humanity by Terminator AIs is not an acceptable research goal. I don’t care how bad you think our current political climate is.

To be slightly more realistic, if you have a secret research goal of taking over the world, such as  Max Tegmark imagines in The Tale of the Omega Team in his book, Life 3.0, and we find out, we will shut you down (or try to). Even if it is all peaceful and well-meaning, and no one gets hurt, as Max visualizes, plotting world domination by machines is not a positive value. If you get caught researching how to do that, some of the more creative prosecuting lawyers around will find a way to send you to jail. We have all seen the cheesy movies, and so have the juries, so do not tempt us.

Keep a positive, pro-humans, pro-Earth, pro-freedom goal for your research. I do not doubt that we will someday have AI smarter than our existing world leaders, perhaps sooner than many expect, but that does not justify a machine take-over. Wisdom comes slowly and is different than intelligence.

Still, what about autonomous weapons? Is research into advanced AI in this area beneficial? Are military defense capabilities beneficial? Pro-security? Is the slaughter of robots not better than the slaughter of humans? Could robots be more ethical at “soldiering” than humans? As attorney Matt Scherer has noted, who is the editor of a good blog, LawAndAI.com and a Future of Life Institute member:

Autonomous weapons are going to inherently be capable of reacting on time scales that are shorter than humans’ time scales in which they can react. I can easily imagine it reaching the point very quickly where the only way that you can counteract an attack by an autonomous weapon is with another autonomous weapon. Eventually, having humans involved in the military conflict will be the equivalent of bringing bows and arrows to a battle in World War II.

At that point, you start to wonder where human decision makers can enter into the military decision making process. Right now there’s very clear, well-established laws in place about who is responsible for specific military decisions, under what circumstances a soldier is held accountable, under what circumstances their commander is held accountable, on what circumstances the nation is held accountable. That’s going to become much blurrier when the decisions are not being made by human soldiers, but rather by autonomous systems. It’s going to become even more complicated as machine learning technology is incorporated into these systems, where they learn from their observations and experiences in the field on the best way to react to different military situations.

Podcast: Law and Ethics of Artificial Intelligence (Future of Life, 3/31/17).

The question of beneficial or not can become very complicated, fast. Like it or not, military research into killer robots is already well underway, in both the public and private sector. Kalashnikov Will Make an A.I.-Powered Killer Robot: What could possibly go wrong? (Popular Mechanics, 7/19/17); Congress told to brace for ‘robotic soldiers’ (The Hill, 3/1/17); US military reveals it hopes to use artificial intelligence to create cybersoldiers and even help fly its F-35 fighter jet – but admits it is ALREADY playing catch up (Daily Mail, 12/15/15) (a little dated, and sensationalistic article perhaps, but easy read with several videos).

AI weapons are a fact, but they should still be regulated, in the same way that we have regulated nuclear weapons since WWII. Tom Simonite, AI Could Revolutionize War as Much as Nukes (Wired, 7/19/17); Autonomous Weapons: an Open Letter from AI & Robotics Researchers.

Principle Two: Research Funding

The second principle of Funding is more than an enforcement mechanism for the first, that you should only fund beneficial AI. It is also a recognition that ethical work requires funding too. This should be every lawyer’s favorite AI ethics principle. Investments in AI should be accompanied by funding for research on ensuring its beneficial use, including thorny questions in computer science, economics, law, ethics, and social studies. The principle then adds a list of five bullet-point examples.

How can we make future AI systems highly robust, so that they do what we want without malfunctioning or getting hacked. The goal of avoiding the creation of AI systems that can be hacked, easily or not, is a good one. If a hostile power can take over and misuse an AI for evil end, then the built-in beneficence may be irrelevant. The example of a driverless car come to mind that could be hacked and crashed as a perverse joy-ride, kidnapping or terrorist act.

The economic issues raised by the second example are very important: How can we grow our prosperity through automation while maintaining people’s resources and purpose? We do not want a system that only benefits the top one percent, or top ten percent, or whatever. It needs to benefit everyone, or at least try to. Also see Asilomar Principle Fifteen: Shared Prosperity: The economic prosperity created by AI should be shared broadly, to benefit all of humanity.

Yoshua Bengio, Professor of Computer Science at the University of Montreal, had this important comment to make on the Asilomar principles during an interview at the end of the conference:

I’m a very progressive person so I feel very strongly that dignity and justice mean wealth is redistributed. And I’m really concerned about AI worsening the effects and concentration of power and wealth that we’ve seen in the last 30 years. So this is pretty important for me.

I consider that one of the greatest dangers is that people either deal with AI in an irresponsible way or maliciously – I mean for their personal gain. And by having a more egalitarian society, throughout the world, I think we can reduce those dangers. In a society where there’s a lot of violence, a lot of inequality, the risk of misusing AI or having people use it irresponsibly in general is much greater. Making AI beneficial for all is very central to the safety question.

Most everyone at the Asilomar Conference agreed with that sentiment, but I do not yet see a strong consensus in AI businesses. Time will tell if profit motives and greed will at least be constrained by enlightened self-interest. Hopefully capitalist leaders will have the wisdom to share the great wealth with all of society that AI is likley to create.

How can we update our legal systems to be more fair and efficient, to keep pace with AI, and to manage the risks associated with AI? The legal example is also a good one, with the primary tension we see so far between fair versus efficient. Just policing high crime areas might well be efficient, at least for reducing some type of crime, but would it be fair? Do we want to embed racial profiling into our AI? Neighborhood slumlord profiling? Religious, ethic profiling? No. Existing law prohibits that and for good reason. Still, predictive policing is already a fact of life in many cities and we need to be sure it has proper legal, ethical regulation.

We have seen the tension between “speedy” and “inexpensive” on the one hand, and “just” on the other in Rule One of the Federal Rules of Civil Procedure and e-discovery. When applied using active machine learning a technical solution was attained to these competing goals. The predictive coding methods we developed allowed for both precision (“speedy” and “inexpensive”) and recall (“just”). Hopefully this success can be replicated in other areas of the law where machine learning is under proportional control by experienced human experts.

The final example given is much more troubling: What set of values should AI be aligned with, and what legal and ethical status should it have? Whose values? Who is to say what is right and wrong? This is easy in a dictatorship, or a uniform, monochrome culture (sea of white dudes), but it is very challenging in a diverse democracy. This may be the greatest research funding challenge of all.

Principle Three: Science-Policy Link

This principle is fairly straightforward, but will in practice require a great deal of time and effort to be done right. A constructive and healthy exchange between AI researchers and policy-makers is necessarily a two-way street. It first of all assumes that policy-makers, which in most countries includes government regulators, not just industry, have a valid place at the table. It assumes some form of government regulation. That is anathema to some in the business community who assume (falsely in our opinion) that all government is inherently bad and essentially has nothing to contribute. The countervailing view of overzealous government controllers who just want to jump in, uninformed, and legislate, is also discouraged by this principle. We are talking about a healthy exchange.

It does not take an AI to know this kind of give and take and information sharing will involve countless meetings. It will also require a positive healthy attitude between the two groups. If it gets bogged down into an adversary relationship, you can multiply the cost of compliance (and number of meetings) by two or three. If it goes to litigation, we lawyers will smile in our tears, but no one else will. So researchers, you are better off not going there. A constructive and healthy exchange is the way to go.

Principle Four: Research Culture

The need for a good culture applies in spades to the research community itself. The Fourth Principal states: A culture of cooperation, trust, and transparency should be fostered among researchers and developers of AI. This favors the open source code movement for AI, but runs counter to the trade-secret  business models of many corporations. See Eg.:OpenAI.com, Deep Mind Open Source; Liam , ‘One machine learning model to rule them all’: Google open-sources tools for simpler AI (ZDNet, 6/20/17).

This tension is likley to increase as multiple parties get close to a big breakthrough. The successful efforts for open source now, before superintelligence seems imminent, may help keep the research culture positive. Time will tell, but if not there could be trouble all around and the promise of full employment for litigation attorneys.

Principle Five: Race Avoidance

The Fifth Principle is a tough one, but very important: Teams developing AI systems should actively cooperate to avoid corner-cutting on safety standards. Moving fast and breaking things may be the mantra of Silicon Valley, but the impact of bad AI could be catastrophic. Bold is one thing, but reckless is quite another. In this area of research there may not be leisure for constant improvements to make things right. HackerWay.org.
Not only will there be legal consequences, mass liability, for any group that screws up, but the PR blow alone from a bad AI mistake could destroy most companies. Loss of trust may never be regained by a wary public, even if Congress and Trial Lawyers do not overreact. Sure, move fast, but not too fast where you become unsafe. Striking the right balance is going to require an acute technical, ethical sensitivity. Keep it safe.

Last Word

AI ethics is hard work, but well worth the effort. The risks and rewards are very high. The place to start this work is to talk about the fundamental principles and try to reach consensus. Everyone involved in this work is driven by a common understanding of the power of the technology, especially artificial intelligence. We all see the great changes on the horizon and share a common vision of a better tomorrow.

During an interview at the end of the Asilomar conference, Dan Weld, Professor of Computer Science, University of Washington, provided a good summary of this common vision:

In the near term I see greater prosperity and reduced mortality due to things like highway accidents and medical errors, where there’s a huge loss of life today.

In the longer term, I’m excited to create machines that can do the work that is dangerous or that people don’t find fulfilling. This should lower the costs of all services and let people be happier… by doing the things that humans do best – most of which involve social and interpersonal interaction. By automating rote work, people can focus on creative and community-oriented activities. Artificial Intelligence and robotics should provide enough prosperity for everyone to live comfortably – as long as we find a way to distribute the resulting wealth equitably.

Moravec’s Paradox of Artificial Intelligence and a Possible Solution by Hiroshi Yamakawa with Interesting Ethical Implications

October 29, 2017

Have you heard of Moravec’s Paradox? This is a principle discovered by AI robotics expert Hans Moravec in the 1980s. He discovered that, contrary to traditional assumptions, high-level reasoning requires relatively little computation power, whereas low-level sensorimotor skills require enormous computational resources. The paradox is sometimes simplified by the phrase: Robots find the difficult things easy and the easy things difficult. Moravec’s Paradox explains why we can now create specialized AI, such as predictive coding software to help lawyers find evidence, or AI software that can beat the top human experts at complex games such as Chess, Jeopardy and Go, but we cannot create robots as smart as dogs, much less as smart as gifted two-year-olds like my granddaughter. Also see the possible economic, cultural implications of this paradox as described, for instance, by Robots will not lead to fewer jobs – but the hollowing out of the middle class (The Guardian, 8/20/17).

Hans Moravec is a legend in the world of AI. An immigrant from Austria, he is now serving as a research professor in the Robotics Institute of Carnegie Mellon University. His work includes attempts to develop a fully autonomous robot that is capable of navigating its environment without human intervention. Aside from his paradox discovery, he is well-known for a book he wrote in 1990, Mind Children: The Future of Robot and Human Intelligence. This book has become a classic, well-known and admired by most AI scientists. It is also fairly easy for non-experts to read and understand, which is a rarity in most fields.

Moravec is also a futurist with many of his publications and predictions focusing on transhumanism, including Robot: Mere Machine to Transcendent Mind (Oxford U. Press, 1998). In Robot he predicted that Machines will attain human levels of intelligence by the year 2040, and by 2050 will have far surpassed us. His prediction may still come true, especially if exponential acceleration of computational power following Moore’s Law continues. But for now, we still have a long was to go. The video below gives funny examples of this in a compilation of robots falling down during a DARPA competition.

But then just a few weeks after this blog was originally published, we are shown how far along robots have come. This November 16, 2017, video of the latest Boston Dynamics robot is a dramatic example of accelerating, exponential change.

Yamakawa on Moravec’s Paradox

A recent interview of Horoshi Yamakawa, a leading researcher in Japan working on Artificial General Intelligence (AGI), sheds light on the Moravec Paradox.  See the April 5, 2017 interview of Dr. Hiroshi Yamakawa, by a host of AI Experts, Eric Gastfriend, Jason Orlosky, Mamiko Matsumoto, Benjamin Peterson, and Kazue Evans. The interview is published by the Future of Life Institute where you will find the full transcript and more details about Yamakawa.

In his interview Horoshi explains the Moravec Paradox and the emerging best hope for its solution by deep learning.

The field of AI has traditionally progressed with symbolic logic as its center. It has been built with knowledge defined by developers and manifested as AI that has a particular ability. This looks like “adult” intelligence ability. From this, programming logic becomes possible, and the development of technologies like calculators has steadily increased. On the other hand, the way a child learns to recognize objects or move things during early development, which corresponds to “child” AI, is conversely very difficult to explain. Because of this, programming some child-like behaviors is very difficult, which has stalled progress. This is also called Moravec’s Paradox.

However, with the advent of deep learning, development of this kind of “child” AI has become possible by learning from large amounts of training data. Understanding the content of learning by deep learning networks has become an important technological hurdle today. Understanding our inability to explain exactly how “child” AI works is key to understanding why we have had to wait for the appearance of deep learning.

Horoshi Yamakawa calls his approach to deep learning the Whole Brain Architecture approach.

The whole brain architecture is an engineering-based research approach “To create a human-like artificial general intelligence (AGI) by learning from the architecture of the entire brain.”  … In short, the goal is brain-inspired AI, which is essentially AGI. Basically, this approach to building AGI is the integration of artificial neural networks and machine-learning modules while using the brain’s hard wiring as a reference. However, even though we are using the entire brain as a building reference, our goal is not to completely understand the intricacies of the brain. In this sense, we are not looking to perfectly emulate the structure of the brain but to continue development with it as a coarse reference.

Yamakawa sees at least two advantages to this approach.

The first is that since we are creating AI that resembles the human brain, we can develop AGI with an affinity for humans. Simply put, I think it will be easier to create an AI with the same behavior and sense of values as humans this way. Even if superintelligence exceeds human intelligence in the near future, it will be comparatively easy to communicate with AI designed to think like a human, and this will be useful as machines and humans continue to live and interact with each other. …

The second merit of this unique approach is that if we successfully control this whole brain architecture, our completed AGI will arise as an entity to be shared with all of humanity. In short, in conjunction with the development of neuroscience, we will increasingly be able to see the entire structure of the brain and build a corresponding software platform. Developers will then be able to collaboratively contribute to this platform. … Moreover, with collaborative development, it will likely be difficult for this to become “someone’s” thing or project. …

Act Now for AI Safety?

As part of the interview Yamakawa was asked whether he thinks it would be productive to start working on AI Safety now? As readers here know, one of the major points of the AI-Ethics.com organization I started is that we need to begin work know on such regulations. Fortunately, Yamakawa agrees. His promising Whole Brained Architecture approach to deep learning as a way to overcome Moravec’s Paradox thus will likley have a strong ethics component. Here is Horoshi Yamakawa full, very interesting answer to this question.

I do not think it is at all too early to act for safety, and I think we should progress forward quickly. Technological development is accelerating at a fast pace as predicted by Kurzweil. Though we may be in the midst of this exponential development, since the insight of humans is relatively linear, we may still not be close to the correct answer. In situations where humans are exposed to a number of fears or risks, something referred to as “normalcy bias” in psychology typically kicks in. People essentially think, “Since things have been OK up to now, they will probably continue to be OK.” Though this is often correct, in this case, we should subtract this bias.

If possible, we should have several methods to be able to calculate the existential risk brought about by AGI. First, we should take a look at the Fermi Paradox. This is a type of estimation process that proposes that we can estimate the time at which intelligent life will become extinct based on the fact that we have not yet met with alien life and on the probability that alien life exists. However, using this type of estimation would result in a rather gloomy conclusion, so it doesn’t really serve as a good guide as to what we should do. As I mentioned before, it probably makes sense for us to think of things from the perspective of increasing decision making bodies that have increasing power to bring about the destruction of humanity.

 


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