Lawyers’ Job Security in a Near Future World of AI, the Law’s “Reasonable Man Myth” and “Bagley Two” – Part Two

January 22, 2017

This is the second and concluding section to the two-part blog, Lawyers’ Job Security in a Near Future World of AI, the Law’s “Reasonable Man Myth” and “Bagley Two.” Click here to read Part One.

Robot_handshake

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Next consider Judge Haight’s closing words to the opinion dated December 22, 2016, Ruling On Plaintiff’s Motion To Compel; Bagely v. Yale, Civil Action No. 3:13-CV-1890 (CSH):

However, requiring this additional production, or a further deposition in case of need, is in keeping with a governing objective of the Federal Rules of Civil Procedure: “By requiring disclosure of all relevant information, the discovery rules allow ultimate resolution of disputed issues to be based on full and accurate understanding of true facts.” 6 Moore’s Federal Practice § 26.02 (Matthew Bender 3d ed.). 6

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6 While Yale may not welcome the measurement of its obligations in the case at bar by these principles, it is worth recalling that the treatise’s principal initial author, James Wm. Moore, was a towering figure on the faculty of Yale Law School. In his preface to the first edition (1938), Professor Moore referred to his effort “at all times to accord to the Rules the interpretation which is most likely to attain the general objective of the new practice: the settlement of litigation on the merits.” That is the interpretation this Ruling attempts to adopt.

william_moore_prof_yale

Prof. Moore (1905-1994)

Poor Yale. Moore’s Federal Practice is one of the most cited treatises in the law. James W. Moore was the author of the 34-volume Moore’s Federal Practice (2d ed., 1948) and the three-volume Moore’s Manual: Federal Practice & Procedure (1962). He was also the Sterling Professor Emeritus of Law at Yale University, where he taught for 37 years. Who else but Yale can have anything in Moore’s thirty-four volume treatise held against them personally? Seems kind of funny, but I am sure Yale’s attorneys were not laughing.

Getting back to the case and Judge Haight’s decision. Aside from showing the malleability and limits of reason, Bagley Two provides some important new precedent for e-discovery, namely his rulings on privilege and the discoverability of a party’s preservation efforts. Judge Haight starts by repeating what is now established law, that a party’s preservation efforts are not satisfied by mere issuance of a notice, that a whole process is involved and the process must be reasonable. He then goes on to provide a pretty good list of the facts and circumstances that should be considered to determine reasonability.

[A] party’s issuance of a litigation hold notice does not put an end to the party’s obligation to preserve evidence; it is, rather, the first in a series of related steps necessary to ensure that preservation. As Magistrate Judge Francis aptly observed in Mastr Adjustable Rate Mortgages Trust 2006 v. UBS Real Estate Securities Inc., 295 F.R.D. 77, 85 (S.D.N.Y. 2013): “A litigation hold is not, alone, sufficient; instead compliance must be monitored.”

In spoliation cases involving litigation hold notices, one can discern from Second Circuit and district court opinions a number of decisive questions:

1. When did a party’s duty to preserve evidence arise?
2. Did the party issue a litigation hold notice in order to preserve evidence?
3. When did the party issue a litigation hold notice, in relation to the date its duty to preserve the evidence arose?
4. What did the litigation hold notice say?
5. What did recipients of the litigation hold notice do or say, in response to or as result of, the notice?
6. After receiving recipients’ responses to the litigation hold notice, what further action, if any, did the party giving the notice take to preserve the evidence?

Questions 2 through 6 are entirely fact-specific to a given case. Question 1 is a mixed question of law and fact, whose legal element the Second Circuit defined in Fujitsu Ltd. v. Federal Express Corp., 247 F.3d 423, 436 (2d Cir. 2001): “The obligation to preserve evidence arises when the party has notice that the evidence is relevant to litigation or when a party should have known that the evidence may be relevant to future litigation.”

In the case at bar, I am unable to accept Yale’s argument that the litigation hold notices it issued about Bagley and the recipients’ responses to the notices are immune from discovery because (in the absence of proof that spoliation had in fact occurred) such documents “are subject to the attorney-client and to work product privileges,” Defendants’ Brief [Doc. 192], at 3. That contention is something of a stretch. … . Assuming that all of Clune’s litigation hold notices were sent to employees of Yale, Clune was in effect communicating with his client. However, the predominant purpose of that communication was to give recipients forceful instructions about what they must do, rather than advice about what they might do. 3

I like the list of six key facts to consider to weigh the reasonability of preservation efforts, especially the last one. But my primary point here is the malleability of reason in classifying the notice as unprotected. A letter from in-house counsel telling employees that the law requires them to preserve is not advice entitled to privilege protection? It’s predominant purpose was instead unprotected instructions? The language of the litigation hold notices was earlier quoted in the opinion. It’s language included the following:

[A]ll members of the Yale faculty and staff who have information in their possession or control relating or referring in any way to Professor Bagley, her employment and teaching at SOM, or the circumstances relating to the non-renewal of her faculty appointment (collectively “this Matter”) have a legal obligation to preserve that information. The law imposes this obligation to prevent the loss of potential evidence during litigation. You must preserve and retain, and not alter, delete, remove, discard or destroy, directly or indirectly, any information concerning this Matter. Failure to preserve information could seriously undermine Yale’s legal position and lead to legal sanctions.

The lawyer’s letter tells employees that they “have a legal obligation to preserve,” and the legal consequences if they do not. Yet this letter is not advice because the predominant purpose is just an unprotected instruction? That is the holding.

mental_impressionsJudge Haight gets rid of work product protection too.

As for the work product doctrine, it “is not actually a privilege, but rather a qualified immunity from discovery,” codified in Fed. R. Civ. P. Rule 26(b)(3), whose purpose “is to protect an attorney’s mental processes so that the attorney can analyze and prepare for the client’s case without interference from an opponent.” 6 Moore’s Federal Practice, § 26.70[1] (Matthew Bender 3d ed.). 4 That purpose is not implicated by the present exercise.

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4 Fed. R. Civ. P. 26 (b)(3) of Civil Procedure protects from disclosure those materials which reveal “the mental impressions, conclusions, opinions, or legal theories of a party’s attorney.” See also In re Steinhardt Partners, L.P., 9 F.3d 230, 234 (2d Cir. 1993) (“At its core, the work product doctrine shelters the mental processes of the attorney, providing a privileged area within which he can analyze and prepare his client’s case.”) (quoting United States v. Nobles, 422 U.S. 225, 238 (1975)) (emphasis added).

I do not agree with Judge Haight on this aspect of his ruling. I think both work product and attorney client apply to these particular notices and his “reasoning”on this issue is wrong. I do, however, agree with his final ruling requiring production. I think the protections had been waived by the circumstances and actions of defense counsel, which, by the way, they were correct in doing. I think the waiver on their part was necessary. Judge Haight also mentioned waiver, but as dicta alternative grounds in footnote three:

3 The Court also notes that to the extent that Yale’s litigation hold notices included the text of the exemplar provided to Plaintiff as “document preservation notices,” that text has already been revealed publicly in this case, so that secrecy or privilege relating to that language was destroyed or waived. See Doc. 191-1, Ex. F.

triggerJudge Haight then looks at the question of when Yale’s duty to preserve commenced. Recall Yale kept adding custodians in eight stages. The first were pre-litigation notices. They were made, I note, after Yale’s lawyer mental processes told him that litigation was reasonably likely. The last were made after suit was filed, again based on the lawyer’s mental processes causing him to believe that these additional witnesses might have relevant evidence. The mental processes of Plaintiff’s attorneys led them to believe that all of the notices, including the pre-litigation notices, were sent too late and thus spoliation was likely. Here is Judge Haight’s analysis of the trigger issue:

When, during the course of this melancholy chain of events, should Yale have known that evidence pertinent to Bagley’s reappointment might be relevant to future litigation? That is a crucial question in spoliation analysis. A state of reasonable anticipation clearly antedates the actual filing of a complaint; in Fujitsu, 247 F.3d at 436, the Second Circuit was careful to couple actual present and possible future litigation as catalysts of equal strength for the preservation of evidence.

Bagley has not yet formally moved for spoliation sanctions, and so the question is not yet before me for decision, but some preliminary, non-binding observations may be made. The record previously made in the case shows that Bagley’s personal distress and institutional disapproval and distrust grew throughout the winter and spring of 2012 (the last year of her five-year appointment), so that when on May 24, 2012, Dean Snyder told Bagley that she would not be reappointed, it would not be irrational to suppose that Bagley might soon transform herself from disheartened academic to vengeful litigant. In fact, Bagley filed an internal discrimination complaint against Yale during the following month of June 2012 (which had the effect of bringing Provost Salovey out of the wings and onto the stage).

Predictable_IrrationalNote the Judge’s use of the phrase not be irrational to suppose. What is the impact of hindsight bias on this supposedly objective, rational analysis? Bagley’s later actions made it obvious that she would sue. She did sue. The law suit has been very contentious. But was it really all that obvious back in 2012 that Yale would end up in the federal courthouse? I personally doubt it, but, admit it is a close judgment call. We lawyers say that a lot. All that phrase really means is that reason is not objective. It is in the eye of the beholder.

Judge Haight then wraps up his analysis in Bagley Two.

What happened in this case is that Yale identified 65 individuals who might have evidence relevant to Bagley’s denial of reappointment, and issued them litigation hold notices in eight separate batches, a process that took a considerable amount of time. The first nine notices were sent nine months after Snyder told Bagley she would not be reappointed. The last was sent eight months after Bagley filed this action. To characterize the pace of this notification process as culpable or even negligent would be premature on the present record, but it is fair to say that it was leisurely, to an extent making it impossible to dismiss as frivolous Bagley’s suggestion that she might move for a spoliation sanction. The six questions outlined supra arise in this case, and the factors pertinent to resolving them include an unreasonable delay in issuing the notices and a subsequent failure to implement and monitor the recipients’ responses. Judge Sweet said in Stimson that the Second Circuit has left open “the question of whether a sufficiently indefensible failure to issue a litigation hold could justify an adverse inference on its own,” and an additional factor would be “the failure to properly implement the litigation hold even after it was issued.” 2016 WL 54684, at *6. These are legitimate questions in the case at bar. Bagley is entitled to discovery with respect to them. 5 (footnote citations omitted)

I certainly agree with Judge Haight on all of those points and law. Those factual circumstances do justify the modest amount of discovery requested by the plaintiff in this motion.

gavelNow we get to the actual Order on the pending motion to compel:

Therefore I conclude that in the circumstances of this case, Bagley’s “Motion to Compel” [Doc. 190] is GRANTED. Bagley is entitled to examine the litigation hold notices issued by Yale, and the responsive survey forms that notice recipients returned to Yale. These documents bear directly upon the questions courts identify as dispositive in spoliation cases. Bagley is entitled to discovery in these areas, in order to discern the merit or lack of merit of a formal claim for spoliation claim. To the extent that Yale objects to production of these documents on the grounds of privilege or the work product doctrine, the objections are OVERRULED.

For the same reasons, Bagley is also entitled to an affidavit from a Yale officer or employee (not a notice recipient or recipients) which describes what non-ESI documents Yale received from notice recipients and what was done with them. On a spoliation claim, Bagley will ultimately bear the burden of showing that pertinent evidence was destroyed or rendered unavailable. This discovery may cast light on that disputed issue. Yale may prefer not to have to produce that information; Yale’s counsel miss no opportunity to remind the Court how much discovery effort the case has previously required.

Judge Haight then ended his opinion with the previously quoted zinger regarding Yale’s famous law Professor Moore. This zinger and comments about Yale’s leisurely efforts and Yale counsel’s missing no opportunities to remind the court tell a story of their own. It shows the emotional undertone. So too does his earlier noted comment about “spoliation” being a cardinal litigation vice, well known to practicing attorneys and judges, but “perhaps unfamiliar” to academics. I suspect this goes beyond humor.

Artificial Intelligence and the Future of Employment

robot_whispererI am sure legal reason will improve in the future and become less subjective, less subject to hidden irrationalities and prejudices. By using artificial intelligence our legal doctrines and decision making can be improved, but only if the human judges remain in charge. The same comment goes for all attorneys. In fact, it applies to all current employment.

The doom and gloom futurists disagree. They think AI will replace humans at their jobs, not empower them. They envision a future of cold automation, not man-machine augmentation. They predict wide-spread unemployment with a loss of half of our current employment. An University of Oxford study predicted that almost half of all U.S. jobs could be lost to automation in the next twenty years. Even the influential World Economic Forum predicts predicts that Five Million jobs could be lost by 2020. Five Million Jobs by 2020: the Real Challenge of the Fourth Industrial Revolution. Also seeThe Future of Jobs: Employment, Skills and Workforce Strategy for the Fourth Industrial Revolution (World Economic Forum, Jan. 2016).

A contrary view “augmentation” oriented group predicts the opposite, that at least as many new jobs will be created as lost. This is a subject of hot debate. See EgArtificial intelligence will save jobs, not destroy them (World Economic Forum, 1/19/17). Readers know I am in the half-full camp.

James Bessen: Law Prophet of the Future of Employment

james_bessonMany are like me and have an overall positive outlook, including James Bessen, an economist  and Lecturer in Law at the Boston University School of Law. Jim Bessen, who was a good hacker with an entrepreneurial background (he created the first WYSIWYG desktop publishing software), has researched the history of computer use and employment since 1980. Jim’s research has shown that for those who can keep up with technology, there will be new jobs to replace the ones lost. Bessen, How Computer Automation Affects Occupations: Technology, Jobs & Economics, Boston University School of Law Law & Economics Working Paper No. 15-49 (1/16/16). He also found that wages in occupations that use computers grow faster, not slower:

[B]ecause higher wage occupations use computers more, computer use tends to increase well-paid jobs and to decrease low-paid jobs. Generally, computer use is associated with a substantial reallocation of jobs, requiring workers to learn new skills to shift occupations.

Also see the article in The Atlantic magazine by Bessen, The Automation Paradox: When computers start doing the work of people, the need for people often increases, (The Atlantic, 1/19, 2016) where he said:

…workers will have greater employment opportunities if their occupation undergoes some degree of computer automation. As long as they can learn to use the new tools, automation will be their friend.

This is certainly consistent with what I have seen in the legal profession since I started practice in 1980.

james_bessenJames Bessen has also written a book on this, Learning by Doing: The Real Connection Between Innovation, Wages, and Wealth. (Yale U. Press 2015). In this book, Bessen, in his words:

… looks at both economic history and the current economy to understand how new technology affects ordinary workers and how society can best meet the challenges it poses.

He notes that major new technologies always require new human work skills and knowledge, and that today, as before, they are slow and difficult to develop. He also makes the observation, which is again consistent with my own experience as a tech-lawyer, that relevant technical knowledge “develops slowly because it is learned through experience, not in the classroom.” In his analysis that is because the new knowledge is not yet standardized. I agree. This is one reason my work has been focused on the standardization of the use of active machine learning in the search for electronic evidence; see for example Predictive Coding 4.0 and my experiments at the TREC conference on predictive coding methods sponsored by the National Institute of Standards and Technology. Also see: Electronic Discovery Best Practices. In spite of my efforts on standards and best practices for e-discovery, we are still in the early, rapidly changing, non-standardized stage of new technology. Bessen argues that employer policies and government policies should encourage such on-the-job learning and perfection of new methods.

Jim Bessen’s findings are starting to be discussed by many who are now concerned with the impact of AI on employment. See for instance, Andrea Willige’s article in the World Economic Forum concerning Davos for 2017Two reasons computers won’t destroy all the jobs (“jobs don’t disappear, they simply move up the skills and wage ladder. For workers to move up the ranks, they must acquire the necessary skillset.”).

Standardization v. On-the-Job Training

Moving on up requires new employment skills. It requires workers who can step-in, step-up, step-aside, step-narrowly, or step-forward. Only Humans Need Apply; Dean Gonsowski, A Clear View or a Short Distance? AI and the Legal Industry, and, Gonsowski, A Changing World: Ralph Losey on “Stepping In” for e-Discovery, (Relativity Blog) (Interview with references to the the 5-steps described in Only Humans Need Apply). Unless and until standardization emerges, and this is taught in a classroom, the new skills will be acquired by on-the-job learning only, sometimes with experienced trainers, but more often self-taught by trial and error.

Borg_Ralph_headI have been working on creating the perfect, standard method for electronic document review using predictive coding since Da Silva Moore. I have used trial and error and on-the-job learning, buttressed by spending a month a year over the last five years on scientific research and experiments with my own team (remember my Borg experiments and videos?) and with TREC, EDI and Kroll Ontrack. Borg Challenge: Report of my experimental review of 699,082 Enron documents using a semi-automated monomodal methodology (a five-part written and video series comparing two different kinds of predictive coding search methods); Predictive Coding Narrative: Searching for Relevance in the Ashes of EnronEDI-Oracle Study: Humans Are Still Essential in E-Discovery (LTN Nov., 2013); e-Discovery Team at TREC 2015 Total Recall Track, Final ReportTREC 2016 Total Recall Track NOTEBOOK.

predictive_coding_4-0_simpleAfter years we have finally perfected and standardized a highly effective method for document review using predictive coding. We call it Predictive Coding 4.0. This method is complete, well-tested, proven and standardized for my team, but not yet accepted by the industry. Unfortunately, industry acceptance of one lawyer’s method is very difficult (impossible?) in the highly competitive, still young and emerging field of electronic document review. I create a standard because I have to in my work, not because I unrealistically expect the industry to adopt it. The industry is still too young for that. I will continue with my on-the-job training, content with that, just as Bessen, Davenport and Kirby observe is the norm for all new technologies. Someday a standard will be generally accepted and taught in classrooms, but we are far from it.

Conclusion

There is more going on in Bagley Two than objective reason, even assuming such a thing exists. Experienced attorneys can easily read between the lines. Reasoned analysis is just the tip of the iceberg, or top of the pyramid, as I envisioned in the new model for Holistic Law outlined in my prior article, Scientific Proof.

There is far more to Senior District Judge Charles S. Haight, Jr., than his ability to be logical and apply reason to the facts. He is not just a “thinking machine.” He has wisdom from decades on the bench. He is perceptive, has feelings and emotions, good intuitions and, we can see, a sense of humor. The same holds true for most judges and lawyers, perhaps even law professors. We are all human and have many other capacities beyond what robots can be trained to do.

Jason_Ralph_RobotReason is just one of the things that we humans do, and, as the work of Professor Ariely has shown, it is typically full of holes and clouded by hidden bias. We need the help of computers to get reason done right, to augment our logic and reasoning skills. Do not try to compete with, nor exclude robots from tasks involving reason. You will ultimately lose that battle. Instead, work with the robots. Invite them in, but remain in control of the processes; use the AI’s abilities to enhance and enlarge your own.

I am sure legal reason will improve in the future and become less subjective. This will happen when more lawyers Step-In as discussed in Davenport and Kirby, Only Humans Need Apply and Dean Gonsowski, A Clear View or a Short Distance? AI and the Legal Industry, and A Changing World: Ralph Losey on “Stepping In” for e-Discovery

alex_hafezMany of us have stepped-in, to use Davenport and Kirby’s language, to manage the use of TAR and AI in document review, not just me. Consider, for instance attorney Alexander Hafez, currently a “Solutions Engineer” for FTI. He was the only other attorney featured in Only Humans Need Apply. Alex bootstrapped his way from minimum wage contract document reviewer, to his current large vendor consultant “step-in” job, by, in the book’s words, “educational bricolage” composed of on-the-job learning and “a specialized course of two and some autodidactic reading.” Id. pg. 144. There are thousands of lawyers in e-Discovery doing quite well in today’s economy. The use of AI and other advanced technologies is now starting to appear in other areas of the law too, including contract review, analysis and construction. See eg. Kira Systems, Inc.

Great-Depression_LitigatorsAs the other areas of the Law become as enhanced and augmented as e-discovery, we will see new jobs open up for the steppers. Old mechanistic law jobs will be replaced. That is for sure. There will be jobs lost in the legal economy. But if Davenport, Kirby and Bessen are correct, and I for one think they are, new, better paying jobs will be created to replace them. Still, for most luddite lawyers, young and old, who are unable to adapt and learn new technologies, the impact of AI on the Law could be devastating. 

Only the tech-savvy will be able to move up the skill and wage ladder by stepping-in to make the technology work right. I attained the necessary skill set to do this with legal technology by teaching myself, by “hacking around” with computers. Yes, it was difficult, but I enjoyed this kind of learning. My story of on the job self-learning is very common. Thus the name of Bessen’s book, Learning by DoingOthers might do better in a more structured learning environment, such as a school, but for the fact there currently is none for this sort of thing, at least in the Law. It falls between the cracks of law school and computer science. For now the self-motivated, self-learners will continue to lead the way.

brad_smith_microsoftNot only do we need to improve our thinking with machines, we need to contribute our other talents and efforts. We need to engage and expand upon the qualities of our job that are most satisfying to us, that meet our human nature. This uniquely human work requires what is sometimes called “soft skills.” This primarily includes the ability for good interpersonal communication, but also such things as the ability to work collaboratively, to adapt to a new set of demands, and to solve problems on the fly. Legal counseling is a prime example according to the general counsel of Microsoft, Brad Smith. Microsoft’s Top Lawyer Toasts Legal Secretaries (Bloomberg Law, 1/18/17). The top lawyer, once CEO of Microsoft, also opined:

Individuals need to learn new skills to keep pace, and this isn’t always easy.  Over the next decade this could become more daunting still, as technology continues to change rapidly.  There is a broadening need for new technical skills and stronger soft skills.  The ability – and opportunity – to continue learning has itself become more important.

Brad Smith, Constructing a Future that Enables all Americans to Succeed, (Dept. of Commerce guest blog, 11/30/16).

The Wikipedia article on “soft skills” lists ten basic skills as compiled by Heckman and Kautz, Hard Evidence on Soft Skills, Labour Econ. 2012 Aug 1; 19(4): 451–464.

  • Communication – oral, speaking capability, written, presenting, listening.
  • Courtesy – manners, etiquette, business etiquette, gracious, says please and thank you, respectful.
  • Flexibility – adaptability, willing to change, lifelong learner, accepts new things, adjusts, teachable.
  • Integrity – honest, ethical, high morals, has personal values, does what’s right.
  • Interpersonal skills – nice, personable, sense of humor, friendly, nurturing, empathetic, has self-control, patient, sociability, warmth, social skills.
  • Positive attitude – optimistic, enthusiastic, encouraging, happy, confident.
  • Professionalism – businesslike, well-dressed, appearance, poised.
  • Responsibility – accountable, reliable, gets the job done, resourceful, self-disciplined, wants to do well, conscientious, common sense.
  • Teamwork – cooperative, gets along with others, agreeable, supportive, helpful, collaborative.
  • Work ethic – hard working, willing to work, loyal, initiative, self-motivated, on time, good attendance.

soft-skills_cartoon

As Brad Smith correctly observed, the skills and tasks needed to keep pace with technology include these kinds of soft skills as well as new technological know-how, things like the best methods to implement new predictive coding software. The tasks, both soft and technical, are generally not overly repetitive and typically require some creativity, imagination, flexibility and inventiveness and, in my view, the initiative to exceed original parameters.

cute_robotA concerned lawyer with real empathy who counsels fellow humans is not likely to be replaced anytime soon by a robot, no matter how cute. There is no substitute for caring, human relationships, for comforting warmth, wit and wisdom. The calm, knowledgeable, confident presence of a lawyer who has been through a problem many times before, and assures you that they can help, is priceless. It brings peace of mind, relaxation and trust far beyond the abilities of any machine.

Stepping-in is one solution for those of us who like working with new technology, but for the rest of humanity, soft-skills are now even more important. Even us tech-types need to learn and improve upon our soft skills. The team approach to e-discovery, which is the basic premise of this e-Discovery Team blog, does not work well without them.

ralph_17_pallate_knife_2Brad Smith’s comment on the need for continued learning is key for everyone who wants to keep working in the future. It is the same thing that Bessen, Davenport and Kirby say. Continued learning is one reason I keep writing. It helps me to learn and may help others to learn too, as part of their “autodidactic reading” and “educational bricolage.” (How else would I learn those words?) According to Bessen’s, Davenport and Kirby’s research most of the key skills needed to keep pace can only be learned on-the-job and are usually self-taught. That is one reason online education is so important. It makes it easier than ever for otherwise isolated people to have access to specialized knowledge and trainers.


What Chaos Theory Tell Us About e-Discovery and the Projected ‘Information → Knowledge → Wisdom’ Transition

May 20, 2016
Ralph and Gleick

Gleick & Losey meeting sometime in the future

This article assumes a general, non-technical familiarity with the scientific theory of Chaos. See James Gleick’s book, Chaos: making a new science (1987). This field of study is not usually discussed in the context of “The Law,” although there is a small body of literature outside of e-discovery. See: Chen, Jim, Complexity Theory in Legal Scholarship (Jurisdymanics 2006).

The article begins with a brief, personal recapitulation of the basic scientific theories of Chaos. I buttress my own synopsis with several good instructional videos. My explanation of the Mandelbrot Set and Complex numbers is a little long, I know, but you can skip over that and still understand all of the legal aspects. In this article I also explore the application of the Chaos theories to two areas of my current work:

  1. The search for needles of relevant evidence in large, chaotic, electronic storage systems, such as email servers and email archives, in order to find the truth, the whole truth, and nothing but the truth needed to resolve competing claims of what happened – the facts – in the context of civil and criminal law suits and investigations.
  2. The articulation of a coherent social theory that makes sense of modern technological life, a theory that I summarize with the words/symbols: Information → Knowledge → Wisdom. See Information → Knowledge → Wisdom: Progression of Society in the Age of Computers and the more recent, How The 12 Predictions Are Doing That We Made In “Information → Knowledge → Wisdom.”

Introduction to the Science of Chaos

Gleick’s book on Chaos provides a good introduction to the science of chaos and, even though written in 1987, is still a must read. For those who have read this long ago, like me, here is a good, short, 3:53, refresher video James Gleick on Chaos: Making a New Science (Open Road Media, 2011) below:

mandelbrot_youngA key leader in the Chaos Theory field is the late great French mathematician, Benoit Mandelbrot (1924-2010) (shown right). Benoit, a math genius who never learned the alphabet, spent most of his adult life employed by IBM. He discovered and named the natural phenomena of fractals. He discovered that there is a hidden order to any complex, seemingly chaotic system, including economics and the price of cotton. He also learned that this order was not causal and could not be predicted. He arrived at these insights by study of geometry, specifically the rough geometric shapes found everywhere in nature and mathematics, which he called fractals. The penultimate fractal he discovered now bears his name, The Mandelbrot Fractalshown in the computer photo below, and explained further in the video that follows.

Mandelbrot set

Look here for thousands of additional videos of fractals with zoom magnifications. You will see the recursive nature of self-similarity over varying scales of magnitude. The patterns repeat with slight variations. The complex patterns at the rough edges continue infinitely without repetition, much like Pi. They show the unpredictable element and the importance of initial conditions played out over time. The scale of the in-between dimensions can be measured. Metadata remains important in all investigations, legal or otherwise.

mandelbrot_equation

The Mandelbrot is based on a simple mathematical formula involving feedback and Complex Numbers: z ⇔ z2 + c. The ‘c’ in the formula stands for any Complex Number. Unlike all other numbers, such as the natural numbers one through nine – 1.2.3.4.5.6.7.8.9, the Complex Numbers do not exist on a horizontal number line. They exist only on an x-y coordinate time plane where regular numbers on the horizontal grid combine with so-called Imaginary Numbers on the vertical grid. A complex number is shown as c= a + bi, where a and b are real numbers and i is the imaginary number. Complex_number_illustration

A complex number can be visually represented as a pair of numbers (a, b) forming a vector on a diagram called an Argand diagram, representing the complex plane. “Re” is the real axis, “Im” is the imaginary axis, and i is the imaginary number. And that is all there is too it. Mandelbrot calls the formula embarrassingly simple. That is the Occam’s razor beauty of it.

To understand the full dynamics of all of this remember what Imaginary Numbers are. They are a special class of numbers where a negative times a negative creates a negative, not a positive, like is the rule with all other numbers. In other words, with imaginary numbers -2 times -2 = -4, not +4. Imaginary numbers are formally defined as i2 = −1.

Thus, the formula z ⇔ z2 + c, can be restated as z ⇔ z2 + (a + bi).

The Complex Numbers when iterated according to this simple formula – subject to constant feedback – produce the Mandelbrot set.

mandelbrot

Mandelbrot_formulaThe value for z in the iteration always starts with zero. The ⇔ symbol stands for iteration, meaning the formula is repeated in a feedback loop. The end result of the last calculation becomes the beginning constant of the next: z² + c becomes the z in the next repetition. Z begins with zero and starts with different values for c. When you repeat the simple multiplication and addition formula millions of times, and plot it on a Cartesian grid, the Mandelbrot shape is revealed.

When iteration of a squaring process is applied to non-complex numbers the results are always known and predictable. For instance when any non-complex number greater than one is repeatedly squared, it quickly approaches infinity: 1.1 * 1.1 = 1.21 * 1.21 = 1.4641 * 1.4641 = 2.14358 and after ten iterations the number created is 2.43… * 10 which written out is 2,430,000,000,000,000,000,000,000,000,000,000,000,000,000. A number so large as to dwarf even the national debt. Mathematicians say of this size number that it is approaching infinity.

The same is true for any non-complex number which is less than one, but in reverse; it quickly goes to the infinitely small, the zero. For example with .9: .9.9=.81; .81.81=.6561; .6561.6561=.43046 and after only ten iterations it becomes 1.39…10 which written out is .0000000000000000000000000000000000000000000000139…, a very small number indeed.

With non-complex numbers, such as real, rational or natural numbers, the squaring iteration must always go to infinity unless the starting number is one. No matter how many times you square one, it will still equal one. But just the slightest bit more or less than one and the iteration of squaring will attract it to the infinitely large or small. The same behavior holds true for complex numbers: numbers just outside of the circle z = 1 on the complex plane will jump off into the infinitely large, complex numbers just inside z = 1 will quickly square into zero.

The magic comes by adding the constant c (a complex number) to the squaring process and starting from z at zero: z ⇔ z² + c. Then stable iterations – a set attracted to neither the infinitely small or infinitely large – become possible. The potentially stable Complex numbers lie both outside and inside of the circle of z = 1; specifically on the complex plane they lie between -2.4 and .8 on the real number line, the horizontal x grid, and between -1.2 and +1.2 on the imaginary line, the vertical y grid. These numbers are contained within the black of the Mandelbrot fractal.

Mandelbrot_grid

In the Mandelbrot formula z ⇔ z² + c, where you always start the iterative process with z equals zero, and c equaling any complex number, an endless series of seemingly random or chaotic numbers are produced. Like the weather, the stock market and other chaotic systems, negligible changes in quantities, coupled with feedback, can produce unexpected chaotic effects. The behavior of the complex numbers thus mirrors the behavior of the real world where Chaos is obvious or lurks behind the most ordered of systems.

With some values of ‘c’ the iterative process immediately begins to exponentially increase or fall into infinity. These numbers are completely outside of the Mandelbrot set. With other values of ‘c’ the iterative process is stable for a number of repetitions, and only later in the dynamic process are they attracted to infinity. These are the unstable strange attractor numbers just on the outside edge of the Mandelbrot set. They are shown on computer graphics with colors or shades of grey according to the number of stable iterations. The values of ‘c’ which remain stable, repeating as a finite number forever, never attracted to infinity, and thus within the Mandelbrot set, are plotted as black.

Mandel_Diagram

Some iterations of complex numbers like 1 -1i run off into infinity from the start, just like all of the real numbers. Other complex numbers are always stable like -1 +0i. Other complex numbers stay stable for many iterations, and then only further into the process do they unpredictably begin to start to increase or decrease exponentially (for example, .37 +4i stays stable for 12 iterations). These are the numbers on the edge of inclusion of the stable numbers shown in black.

Chaos enters into the iteration because out of the potentially infinite number of complex numbers in the window of -2.4 to .8 along the horizontal real number axis, and -1.2 to 1.2 along the vertical imaginary number axis. There are an infinite subset of such numbers on the edge, and they cannot be predicted in advance. All that we know about these edge numbers is that if the z produced by any iteration lies outside of a circle with a radius of 2 on the complex plane, then the subsequent z values will go to infinity, and there is no need to continue the iteration process.

By using a computer you can escape the normal limitations of human time. You can try a very large number of different complex numbers and iterate them to see what kind they may be, finite or infinite. Under the Mandelbrot formula you start with z equals zero and then try different values for c. When a particular value of c is attracted to infinity – produces a value for z greater than 2 – then you stop that iteration, go back to z equals zero again, and try another c, and so on, over and over again, millions and millions of times as only a computer can do.

Mandel_zoom_08_satellite_antennaMandelbrot was the first to discover that by using zero as the base z for each iteration, and trying a large number of the possible complex numbers with a computer on a trial and error basis, that he could define the set of stable complex numbers graphically by plotting their location on the complex plane. This is exactly what the Mandelbrot figure is. Along with this discovery came the surprise realization of the beauty and fractal recursive nature of these numbers when displayed graphically.

The following Numberphile video by Holly Krieger, an NSF postdoctoral fellow and instructor at MIT, gives a fairly accessible, almost cutesy, yet still technically correct explanation to the Mandelbrot set.

Fractals and the Mandelbrot set are key parts of the Chaos theories, but there is much more to it than that. Chaos Theory impacts our basic Newtonian, cause-effect, linear world view of reality as a machine. For a refresher on the big picture of the Chaos insights and how the old linear, Newtonian, machine view of reality is wrong, look at this short summary: Chaos Theory (4:48)

Anther Chaos Theory instructional applying the insights to psychology is worth your view. The Science and Psychology of the Chaos Theory (8:59, 2008). It suggests the importance of spontaneous actions in the moment, the so-called flow state.

Also see High Anxieties – The Mathematics of Chaos (59:00, BBC 2008) concerning Chaos Theories, Economics and the Environment, and Order and Chaos (50:36, New Atlantis, 2015).

Application of Chaos Theories to e-Discovery

The use of feedback, iteration and algorithmic processes are central to work in electronic discovery. For instance, my search methods to find relevant evidence in chaotic systems follow iterative processes, including continuous, interactive, machine learning methods. I use these methods to find hidden patterns in the otherwise chaotic data. An overview of the methods I use in legal search is summarized in the following chart. As you can see, steps four, five and six iterate. These are the steps where human computer interactions take place. 
predictive_coding_3.0

My methods place heavy reliance on these steps and on human-computer interaction, which I call a Hybrid process. Like Maura Grossman and Gordon Cormack, I rely heavily on high-ranking documents in this Hybrid process. The primary difference in our methods is that I do not begin to place a heavy reliance on high-ranking documents until after completing several rounds of other training methods. I call this four cylinder multimodal training. This is all part of the sixth step in the 8-step workflow chart above. The four cylinders search engines are: (1) high ranking, (2) midlevel ranking or uncertain, (3) random, and (4) multimodal (including all types of search, such as keyword) directed by humans.

Analogous Application of Similar Mandelbrot Formula For Purposes of Expressing the Importance of the Creative Human Component in Hybrid 

4-5-6-only_predictive_coding_3.0

Recall Mandelbrot’s formula: z ⇔ z² + c, which is the same as z ⇔ z2 + (a + bi). I have something like that going on in my steps four, five and six. If you plugged the numbers of the steps into the Mandelbrot formula it would read something like this: 4 ⇔ 4² + (5+6i). The fourth step is the key AI Predictive Ranking step, where the algorithm ranks the probable relevance of all documents. The fourth step of computer ranking is the whole point of the formula, so AI Ranking here I will call ‘z‘ and represents the left side of the formula. The fifth step is where humans read documents to determine relevance, let’s call that ‘r‘ and the sixth step is where human’s train the computer, ‘t‘. This is the Hybrid Active Training step where the four cylinder multimodal training methods are used to select documents to train the whole set. The documents in steps five and six, r and t are added together for relevance feedback, (r + ti).

Thus, z ⇔ z² + c, which is the same as z ⇔ z2 + (a + bi), becomes under my system z ⇔ z + (r + ti). (Note: I took out the squaring, z², because there is no such exponential function in legal search; it’s all addition.) What, you might ask, is the i in my version of the formula? This is the critical part in my formula, just as it is in Mandelbrot’s. The imaginary number – i – in my formula version represents the creativity of the human conducting the training.

The Hybrid Active Training step is not fully automated in my system. I do not simply use the highest ranking documents to train, especially in the early rounds of training, as do some others. I use a variety of methods in my discretion, especially the multimodal search methods such a keywords, concept search, and the like. In text retrieval science this use of human discretion, human creativity and judgment, is called an ad hoc search. It contrasts with fully automated search, where the text retrieval experts try to eliminate the human element. See Mr EDR for more detail on 2016 TREC Total Recall Track that had both ad hoc and fully automated sections.

My work with legal search engines, especially predictive coding, has shown that new technologies do not work with the old methods and processes, such as linear review or keyword alone. New processes are required that employ new ways of thinking. The new methods that link creative human judgments (i) and the computer’s amazing abilities at text reading speed, consistency, analysis, learning and ranking (z).

A rather Fat Cat. My latest processes, Predictive Coding  3.0, are variations of Continuous Active Training (CAT) where steps four, five and six iterate until the project is concluded. Grossman & Cormack call this Continuous Active Learning or CAL, and they claim Trademark rights to CAL. I respect their right to do so (no doubt they grow weary of vendor rip-offs) and will try to avoid the acronym henceforth. My use of the acronym CAT essentially takes the view of the other side, the human side that trains, not the machine side that learns. In both Continuous Active Learning and CAT the machine keeps learning with every document that a human codes. Continuous Active Learning or Training, makes the linear seed-set method obsolete, along with the control set and random training documents. See Losey, Predictive Coding 3.0.

In my typical implementation of Continuous Active Training I do not automatically include every document coded as a training document. This is the sixth training step (‘t‘ in the prior formula). Instead of automatically using every document to train that has been coded relevant or irrelevant, I select particular documents that I decide to use to train. This, in addition to multimodal search in step six, Hybrid Active, is another way in which the equivalent of Imaginary Numbers come into my formula, the uniquely human element (ti). I typically use most every relevant document coded in step five, the ‘r‘ in the formula, as a training document, but not all. z ⇔ z + (r + ti)

I exercise my human judgment and experience to withhold certain training documents. (Note, I never withhold hot trainers (highly relevant documents)). I do this if my experience (I am tempted to say ‘my imagination‘) suggests that including them as training documents will likely slow down or confuse the algorithm, even if temporarily. I have found that this improves efficiency and effectiveness. It is one of the techniques I used to win document review contests.

robot-friendThis kind of intimate machine communication is possible because I carefully observe the impact of each set of training documents on the classifying algorithm, and carryover lessons – iterate – from one project to the next. I call this keeping a human in the loop and the attorney in charge of relevance scope adjudications. See Losey, Why the ‘Google Car’ Has No Place in Legal Search. We humans provide experienced observation, new feedback, different approaches, empathy, play and emotion. We also add a whole lot of other things too. The AI-Robot is the Knowledge fountain. We are the Wisdom fountain.That it is why we should strive to progress into and through the Knowledge stage as soon as possible. We will thrive in the end-goal Wisdom state.

Application of Chaos Theory to Information→Knowledge→Wisdom

mininformation_arrowsThe first Information stage of the post-computer society in which we live is obviously chaotic. It is like the disconnected numbers that lie completely outside of the Mandelbrot set. It is pure information with only haphazard meaning. It is often just misinformation. Just exponential. There is an overwhelming deluge of such raw information, raw data, that spirals off into an infinity of dead-ends. It leads no where and is disconnected. The information is useless. You may be informed, but to no end. That is modern life in the post-PC era.

The next stage of society we seek, a Knowledge based culture, is geometrically similar to the large black blogs that unite most of the figure. This is the finite set of numbers that provide all connectivity in the Mandelbrot set. Analogously, this will be a time when many loose-ends will be discarded, false theories abandoned, and consensus arise.

In the next stage we will not only be informed, we will be knowledgable. The information we all be processed. The future Knowledge Society will be static, responsible, serious and well fed. People will be brought together by common knowledge. There will be large scale agreements on most subjects. A tremendous amount of diversity will likely be lost.

After a while a knowledgable world will become boring. Ask any professor or academic.  The danger of the next stage will be stagnation, complacency, self-satisfaction. The smug complacency of a know-it-all world. This may be just as dangerous as the pure-chaos Information world in which we now live.

If society is to continue to evolve after that, we will need to move beyond mere Knowledge. We will need to challenge ourselves to attain new, creative applications of Knowledge. We will need to move beyond Knowledge into Wisdom.

benoit-mandelbrot-seahorse-valleyI am inclined to think that if we ever do progress to a Wisdom-based society, we will be a place and time much like the unpredictable fractal edges of the Mandelbrot. Stable to a point, but ultimately unpredictable, constantly changing, evolving. The basic patterns of our truth will remain the same, but they will constantly evolve and be refined. The deeper we dig, the more complex and beautiful it will be. The dry sameness of a Knowledgable based world will be replaced by an ever-changing flow, by more and more diversity and individuality. Our social cohesivity will arise from recursivity and similarity, not sameness and conformity. A Wisdom based society will be filled with fractal beauty. It will live ever zigzagging between the edge of the known and unknown. It will also necessarily have to be a time when people learn to get along together and share in prosperity and health, both physical and mental. It will be a time when people are accustomed to ambiguities and comfortable with them.

In Wisdom World knowledge itself will be plentiful, but will be held very lightly. It will be subject to constant reevaluation. Living in Wisdom will be like living on the rough edge of the Mandelbrot. It will be a culture that knows infinity firsthand. An open, peaceful, ecumenical culture that knows everything and nothing at the same time. A culture where most of the people, or at least a strong minority, have attained a certain level of personal Wisdom.

Conclusion

Back to our times, where we are just now discovering what machine learning can do, we are just beginning to pattern our investigations, our search for truth, in the Law and elsewhere, on new information gleaned from the Chaos theories. Active machine learning, Predictive Coding, is a natural outgrowth of Chaos Theory and the Mandelbrot Set. The insights of hidden fractal order that can only be seen by repetitive computer processes are prevalent in computer based culture. These iterative, computer assisted processes have been the driving force behind thousands of fact investigations that I have conducted since 1980.

I have been using computers to help me in legal investigations since 1980. The reliance on computers at first increased slowly, but steadily. Then from about 2006 to 2013 the increase accelerated and peaked in late 2013. The shift is beginning to level off. We are still heavily dependent on computers, but now we understand that human methods are just as important as software. Software is limited in its capacities without human additive, especially in legal search. Hybrid, Man and Machine, that is the solution. But remember that the focus should be on us, human lawyers and search experts. The AIs we are creating and training should be used to Augment and Enhance our abilities, not replace them. They should complement and complete us.

butterfly_effectThe converse realization of Chaos Theory, that disorder underlies all apparent order, that if you look closely enough, you will find it, also informs our truth-seeking investigatory work. There are no smooth edges. It is all rough. If you look close enough the border of any coastline is infinite.

The same is true of the complexity of any investigation. As every experienced lawyer knows, there is no black and white, no straight line. It always depends on so many things. Complexity and ambiguity are everywhere. There is always a mess, always rough edges. That is what makes the pursuit of truth so interesting. Just when you think you have it, the turbulent echo of another butterfly’s wings knock you about.

The various zigs and zags of e-discovery, and other investigative, truth-seeking activities, are what make them fascinating. Each case is different, unique, yet the same patterns are seen again and again with recursive similarity. Often you begin a search only to have it quickly burn out. No problem, try again. Go back to square one, back to zero, and try another complex number, another clue. Pursue a new idea, a new connection. You chase down all reasonable leads, understanding that many of them will lead nowhere. Even failed searches rule out negatives and so help in the investigation. Lawyers often try to prove a negative.

The fractal story that emerges from Hybrid Multimodal search is often unexpected. As the search matures you see a bigger story, a previously hidden truth. A continuity emerges that connects previously unrelated facts. You literally connect the dots. The unknown complex numbers – (a + bi) – the ones that do not spiral off into the infinite large or small, do in fact touch each other when you look closely enough at the spaces.

z ⇔ z2 + (a + bi)

SherlockI am no Sherlock, but I know how to find ESI using computer processes. It requires an iterative sorting processes, a hybrid multimodal process, using the latest computers and software. This process allows you to harness the infinite patience, analytics and speed of a machine to enhance your own intelligence ……. to augment your own abilities. You let the computer do the boring bits, the drudgery, while you do the creative parts.

The strength comes from the hybrid synergy. It comes from exploring the rough edges of what you think you know about the evidence. It does not come from linear review, nor simple keyword cause-effect. Evidence is always complex, always derived from chaotic systems. A full multimodal selection of search tools is needed to find this kind of dark data.

The truth is out there, but sometimes you have to look very carefully to find it. You have to dig deep and keep on looking to find the missing pieces, to move from Information → Knowledge → Wisdom.

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blue zoom Mandelbrot fractal animation of looking deeper into the details

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How The 12 Predictions Are Doing That We Made In “Information → Knowledge → Wisdom”

April 5, 2016
TS_Eliot

T. S. Eliot (1888-1965). See his work The Rock

A year ago, April 5, 2015, we published what some consider the e-Discovery Team’s best essay, even though it had little to do with e-discovery: Information → Knowledge → Wisdom: Progression of Society in the Age of Computers. We wrote about the rapid changes in society caused by personal computers and set out our theory of three stages of social development.

hypothesis_testing-cycleThe Information → Knowledge → Wisdom blog included twelve predictions to test the accuracy of our social-technological hypothesis. The predictions concerned the transition of society from an Information Age, in which we believe we now live, to a society based on Knowledge. The transition from mere Information to Knowledge is seen as a necessary survival step for society, not an idealistic dream.

socrates3The next Knowledge Age is also seen as a transition step to the ultimate goal of a society based on Wisdom. Our predictions did not address this last step to Wisdom because this step is, in our opinion, too far out time-wise for any meaningful predictions. It is possible for some individuals to make this step now, but not enough for a whole society to be centered in Wisdom. We have a long way to go to move from an Information to a Knowledge Society before we can make predictions on how a Wisdom based society will arise.

Our time-line for the first transition from Information to Knowledge is already pretty “far-out.” We thought the predictions would come true in five to twenty years. In this blog, a year later, we check the predictions (in bold) and provide a short report on how well they are doing.

Ralph_VRBottom line, our predictions are holding up remarkably well, especially our top prediction of new kinds of cyber education environments and VR. It is very encouraging to see how far society has progressed in just a year. Our technological civilization is still in danger from Information overload, and lack of processed Knowledge, to be sure. The political events of the last year underscore the serious threats. Still, our technology is evolving as predicted and, overall, society is moving in the right direction.

Here is our first prediction.

Top Prediction – VR Community Education

1. Several inventions, primarily in insanely great new computer hardware and software, will allow for the creation of many new types of cyber and physical interconnectivity environments. There will be many more places that will help people to go beyond information to knowledge. They will be both virtual realities, for you or your avatars to hang out, and real-world meeting places for you and your friends to go to. They will not be all fun and games (and sex), although that will be a part of it. Many will focus exclusively on learning and knowledge. The new multidimensional, holographic, 3D, virtual realities will use wearables of all kinds, including Oculus-like glasses, iWatches, and the like. Implant technology will also arise, including some brain implants, and may even be common in twenty years. Many of the environments, both real and VR, will take education and knowledge to a new level. Total immersion in a learning environment will take on new meaning. The TED of the future will be totally mind-blowing.

SONY_VRAlthough we said five to twenty years for these predictions, as it turns out the first prediction is much further along than we knew. On the new inventions front, we now know that Sony will release a PlayStation VR in October 2016 for $399. Also see 7 Virtual Reality Highlights From the Game Developers Conference (NYT, 3/19/16).

holoportationWe also now know that Microsoft is releasing new technology in 2016 that it calls Windows Holographic, and modestly describes as “the most advanced holographic computer the world has ever seen.” It allows for both VR and augmented reality. That means it can add holograms to the real 3D world around you. Microsoft is also reportedly working on a related 3D communications technology that simulates teleportation using the HoloLens augmented-reality glasses that it has dubbed ‘Holoportation‘ (shown in picture above). That looks really cool.

There have been a host of other inventions as well, including improved VR hand sensorsanimated ebooks controlled by the speed of your voice, Samsung phone display holograms. Virtual reality is taking off for a number of small and large companies. Virtual reality trips were, for instance, everywhere at the South by Southwest conference in 2016. Many VR communities are in various stages of development, including a VR City that is well along, which has many social-educational components, called Hypatia.

oculus_riftFacebook’s long-awaited Oculus Rift (shown right) began shipping at the end of March 2016. Right now it costs $599 and you need a souped-up PC to use it. First reviews of the Oculus hardware are praise-filled, although the device itself is well ahead of the software designed to use it. All of these new VR headsets are expected to trigger many new apps, some of which will likely have educational components.

NYT_VR_cellphoneThe New York Times give-away of Google Cardboard VR viewers was also a big deal in late 2015. I got one included with my Sunday paper. I was surprised by the quality of both the free cardboard headset and the content the Times created for it. All you do is put your cell phone in the cardboard box that has lenses in it. It’s simple and works well. This is good start to a new type of total immersion journalistic reports. I highly recommend you try one of the Google cardboard viewers, especially since they are still very low cost. Most of apps, including games, designed to work on them them are also free or low cost.

Immersive_Ed_2015On the importance of VR to education, and thus the transition to a Knowledge based society, a noteworthy conference was held in Paris in October 2015, sponsored by the Sorbonne and the Smithsonian called IMMERSION 2015. One of the modules of the conference was Immersive Education: Teaching and Learning in the Age of ImmersionVR Education group. Also see Two students hope to help explain complex 3D math and science concepts through virtual reality enterprise. I am sure if we kept researching we would find many more examples like that.

Larissa_BailiffThe first prediction is moving into reality faster than we expected. That is good news. Larissa Bailiff, the senior editor of education and content for WoofbertVR (shown right) wrote in her article When Virtual Reality Meets Education:

In what may turn out to be an immersive education game changer, Google launched its Pioneer Expeditions in September 2015. Under this program, thousands of schools around the world are getting — for one day — a kit containing everything a teacher needs to take their class on a virtual trip …

And with VR platforms like AltspaceVR and LectureVR (an initiative of Immersive VR Education), entirely new possibilities are available for teachers of all kinds, as the technology of making avatars and supporting “multi-player” sessions allows for an exponentially­ scaled level of socialization and outreach.

3d-phone_YogaThe use of VR for educational environments in global communities is already far along. When the even better technology just released is developed in the marketplace, and prices come down, this should scale quickly. The Sony, Microsoft, Samsung, and Facebook (Oculus) hardware coming out in 2016 will enable thousands of software entrepreneurs to enter the market. So too will new projects coming out by Google, Apple, etc., in 2017. These new technologies will allow education and art content creators to have the kind of impact needed to push us into a Knowledge-based Society.

rfid-chip-handThe use of implants that is part of the first prediction is also progressing rapidly. See Eg. Grinders, Cyborgs & TranshumanistsScientists propose ‘cortical modem’ implantDARPA is sending brain implants on a voyage round the body to power artificial limbsDo-it-yourself biology: Biohackers implanting rice grain-sized chips under skin. I question the balance of people experimenting with body augmentation at this early stage, but some people like dangerous things, such as the hand implant shown by the thumb in the x-ray photo above.

iWatch_futureNew applications for the i-Watch and other wearables will hopefully come out soon too. (The iWatch to date has largely been a dud, thanks to poor sensors and app development delays.) Increased sensor abilities should also come soon. When that happens it will be easier to personalize information in a holistic manner and so hopefully facilitate self-knowledge.

There is at least one-far out type of technology research now underway that involves the targeted stimulation of the peripheral nervous system to facilitate learning in a wide range of cognitive skills. It sounds bogus, but for the fact it is sponsored by DARPA, the Defense Departments Advanced Research Projects Agency. DARPA calls the project Targeted Neuroplasticity Training (TNT). According to the DARPA announcement of 3/16/16:

Doug_Webber_DARPA“Recent research has shown that stimulation of certain peripheral nerves, easily and painlessly achieved through the skin, can activate regions of the brain involved with learning,” said TNT Program Manager Doug Weber (shown here) adding that the signals can potentially trigger the release of neurochemicals in the brain that reorganize neural connections in response to specific experiences. “This natural process of synaptic plasticity is pivotal for learning, but much is unknown about the physiological mechanisms that link peripheral nerve stimulation to improved plasticity and learning,” Weber said. “You can think of peripheral nerve stimulation as a way to reopen the so-called ‘Critical Period’ when the brain is more facile and adaptive. TNT technology will be designed to safely and precisely modulate peripheral nerves to control plasticity at optimal points in the learning process.”

neurostimulation

DAPRA chart by Dr. Weber

You can follow Dr. Weber here on Twitter. We are.

Nerves_VagusIn an article on this project by Kurzweill News, DARPA’s ‘Targeted Neuroplasticity Training’ program aims to accelerate learning ‘beyond normal levels’ (3/23/16), they state:

DARPA already has research programs underway to use targeted stimulation of the peripheral nervous system as a substitute for drugs to treat diseases and accelerate healing*, to control advanced prosthetic limbs**, and to restore tactile sensation.

But now DARPA plans to take an even more ambitious step: It aims to enlist the body’s peripheral nerves to achieve something that has long been considered the brain’s domain alone: facilitating learning — specifically, training in a wide range of cognitive skills. …

The program is also notable because it will not just train; it will advance capabilities beyond normal levels — a transhumanist approach. …

The engineering side of the program will target development of a non-invasive device that delivers peripheral nerve stimulation to enhance plasticity in brain regions responsible for cognitive functions.

Obviously the military is interested in the potential of brain stimulation, they say to train super-spy agents to rapidly master foreign languages and cryptography. If this works (a big if right now), it likely would go much further than that. What would a commando unit of super-quick learners look like? Could they beat robots (another DARPA project)? I hope we never find out.

DARPA_Robots

Ineuro_stimulation_BRAINf TNT neurostimulation is really able to enhance learning, as DARPA thinks, then it could have many non-military applications too. What if anybody could study law for just a few months, or a week, and pass the Bar exam? What if the same applied to most PhD programs? What if you could learn to speak a new language in a week? Write in a new software code? New martial arts moves as in The Matrix? What if you could learn anything you wanted, when you wanted, really really fast? Or, what if it was just fast, say half the time, or a tenth the time, that it would normally take to learn a complex skill?

What if electro-stimulation (or some other method) could hack your brain into a super high-gear that was once the exclusive province of rare geniuses? If genius becomes commonplace, could a knowledge society be far off? The TNT project has the potential to accelerate our transition to a knowledge based society very rapidly, especially if there is wide-spread distribution of this new technology. The twists and turns that could come out of this are mind-boggling. Let’s just hope we do not become overwhelmed with idiot-savants.

To be honest, the whole theory of simple nerve stimulation triggering freak learning abilities sounds more than a little ridiculous to us. Too easy. Nevertheless, the DAPRA funding and Doug Weber give it credibility. One of DARPA’s past projects included ARPANET that later became the Internet. Indeed, many common place things once seemed ridiculous, such as a computer in every home.

Four Predictions on Social Media and Dissemination of Expertise

2. Some of the new types of social media sites will be environments where subject matter experts (SME) are featured, avatars and real, cyber and in-person, shifted and real-time. There will also be links to other sites or rooms that are primarily information sources.

Pope_InstagramThe Pope is now on Instagram. What more need we say? There has been real progress in this area, although we still have a long way to go. See egWhat Do These Top Industry Experts Use Social Media For?How Social Media Can Help Students StudyConnecting a Classroom: Reflections on Using Social Media With My Students. Still, when a Pope like Francis use media for educational, inspirational purposes, we have made real progress.  Everyday people are doing it too in their own way, even us. See the Team community growing on Twitter.

3. The new SME environment will include products and services, with both free and billed aspects. 

Slow and steady development, but, as expected, has not taken off yet. See Eg. PrestoExperts (online hook-up to experts in many fields); www.experts.com; Experts Exchange; and the site for legal services, AVVO.

4. The knowledge nest community environments will be both online and in-person. The real life, real world, interactions will be in safe public environments with direct connections with cyberspaces. It will be like stepping out of your computer into a Starbucks or laid-back health spa.

Shaw_academyUniversities with old-timely, all too linear professors still rule the roost. Although some colleges are becoming more online and digital oriented, real innovation is still a few years off. Penn Study: Massive Open Online Courses Not a Threat to Traditional Business SchoolsedX – Free online courses from the world’s best universities; The 30 Most Innovative Online CollegesCOURSERA

Most of the professors and other professionals, including law and medicine, have yet to step out of their comfort zone and into cyberspace, much less non-traditional education zones. As the technologies improve we expect that they will be more motivated to do so. Real progress and innovation will follow after that happens. We do note, however, that Amazon has just opened its first physical bookstores and see this an encouraging step. It may seem retro, but it is really a step forwards toward knowledge based communities. We may see more high-tech libraries constructed soon that also fill that purpose. We expect they will be more about space than books.

5. The knowledge focused cyberspaces, both those with and without actual real-words SMEs, will look and feel something like a good social media site of today, but with multimedia of various kinds. Some will have Oculus type VR enhancements like the StarTrek holodeck. All will have system administrators and other staff who are tireless, knowledgable, and fair; but most will not be human.

This prediction depends in large part on the actualization of the first four. These kind of mature multidimensional cyberspaces will come later, when the other predictions come true, and when AIs are more developed as discussed next.

Predictions on AI

Robot_with_HeartSeven of our predictions as to how society will likely transition from an Information Age to a Knowledge Age involved the use of new and improved kinds of artificial intelligence entities. Although this was a big year for AI PR, there were no major break throughs. Not yet.

Google_AI_win_at_GOThe big news this year in AI is that Google created a deep learning based AI system for playing the world’s most complicated game. The AlphaGo software was able to beat a reigning Grand Master in GO in four out of five games. AlphaGo, Lee Sedol, and the Reassuring Future of Humanity (The New Yorker, 3/15/16). Many thought that it would take a decade for a computer to learn how to beat a Grand Master at the world’s most complex game.

It was an impressive victory. Still, Google’s AlphaGo, which used deep learning algorithms, can only do one thing, play GO. AlphaGo and the Limits of Machine Intuition (Harvard Business Review, 3/18/16). To overuse the word, the fact that this was the big news in AI development this year, shows that we still have a long way to go. Moreover, no AI yet born, much less conceived, would appreciate why you are now snickering, or annoyed, or both.

It may be that new hardware development was the big news last year, computers designed to help run AI code. See Nvidia announces a supercomputer aimed at deep learning and AI, (TechCrunch, April 5, 2016). The new Nvidia computers are designed to run deep learning systems a/k/a neural networks. They are due to be released in June 2016 and will sell for $129,000. These Nvidia supercomputers could also become the gold standard in VR machines.

Coldewey in his Tech Crunch article explains that:

These are programs that simulate human-like thought processes by looking very closely at a huge set of data and noting similarities and differences on multiple levels of organization.

This is how Nvidia explains the new technology: (emphasis added)

Computer programs contain commands that are largely executed sequentially. Deep learning is a fundamentally new software model where billions of software-neurons and trillions of connections are trained, in parallel. Running DNN algorithms and learning from examples, the computer is essentially writing its own software. This radically different software model needs a new computer platform to run efficiently.

Nvidia claims to have created a supercomputer designed to fill that platform need. It uses what they call GPUs instead of CPUs. I think this will soon be a crowded field.

Here are the seven AI related predictions made last year. Again, we do not expect to see these advances for at least five years, and as many as twenty.

6. The admins, operators and other staff in these cyberspaces will be advanced AI, like cyber-robots. Humans will still be involved too, but will delegate where appropriate, which will be most of the time. This is one of my key predictions.

The only development I am aware of along these lines is on Facebook. It now has an AI that is automatically writing photo captions. If you hear of anything more, please let me know. It would not seem that difficult to do on at least a rudimentary level, so I still expect to see this advance soon. Much easier than an adult Turing test. See Edge.org contributors discuss the future of AI.

7. The presence of AIs will spread and become ubiquitous. They will be a key part of the IOT – Internet of Things. Even your refrigerator will have an AI, one that you program to fit your current dietary mood and supply orientation.

The IOT is spreading fast as expected, but not yet the communicative AI. Since our cybersecurity is so poor, we are not so sure that is a bad thing. Still, the recent advances in Amazon’s Alexa are promising, and do doubt Siri will get also get lot smarter in the next few years, so too will Google Now and Cortana, so too might a new personal assistant startup called Viv. There are many like this in the works. See Virtual Personal Assistants: The software secretaries (The Economist, 9/12/15).

8. The knowledge products and services will come in a number of different forms, many of which do not exist in the present time, but will be made possible by other new inventions, especially in the area of communications, medical implants, brain-mind research, wearables, and multidimensional video games and conferences.

See our prior comments to the related predictions two through five. Until the AI improves, and/or human inventors take off with great new ideas and products, this prediction of innovation remains conjecture. The creative diversity here predicted requires a developed market that is still several years out. Still, we are seeing early forms of this in things like online mental health counseling using video connections and the like.

9. All subject areas will be covered, somewhat like Wikipedia, but with super-intelligent cyber robots to test, validate and edit each area. The AI robots will serve most of the administrator and other cyber-staffing functions, but not all.

This kind of super-librarian AI still seems decades away. But, we recently found out that Wikipedia is already working on something like this. Artificial intelligence introduced to improve Wikipedia edits (“The Wikimedia foundation is embracing machine learning to make the editing process more streamlined and forgiving for new contributors.”) That is a good start.

10. The AI admins will monitor, analyze, and screen out alleged SMEs who do not meet certain quality standards. The AI admins will thus serve as a truth screen and quality assurance. An SME’s continued participation in an AI certified site will be like a Good Housekeeping Seal of Approval.

We see nothing like this yet on the horizon, although we do see some physician and attorney ranking systems that work on crowd-sourcing. We do, however, remain confident that this prediction will come true within our outside time range of twenty years.

11. The AI admins will also monitor and police the SME services and opinions for fraud and other unacceptable use, and for general cybersecurity. The friendly management AIs will even be involved in system design, billing, collection, and dispute resolution.

The use of AI in general fraud detection, credit scoring and all types of financial analysis, including stock trading, is already well underway. But our prediction here was oriented to AI administration and monitoring of SME services. When these new social media type SME services are developed, the AIs will be well equipped to service the sites and protect users.

12. Environments hosted by such friendly, fair, patient, sometimes funny, polite (per your specified level, which may include insult mode), high IQ intelligence, both human and robot, will be generally considered to be reliable, bona fide, effective, safe, fun, enriching, and beautiful. They will provide a comforting alternative to information overload environments filled with conflicting information, including its lowest form, data. These alternative knowledge nests will become a refuge of music in a sea of noise. Some will become next generation Disney World vacation paradises.

This twelfth prediction is built on all of the rest. It will necessarily be one of the last to come true.

Conclusion

crystal-ball.ESCHER_VRThe development of VR and education is proceeding very rapidly, well ahead of our minimum five year projections. AI is also making steady progress, especially with deep learning algorithms. D. Scott PhoenixHow artificial intelligence is getting even smarter (World Economic Forum, Aug. 2015); Clark, Jack, Why 2015 Was a Breakthrough Year in Artificial Intelligence (Bloomberg, 12/8/15). Although we do not think 2015 was a breakthrough year for AI, we remain confident that their day will come. When the breakthrough year does in fact arrive, it will be quite momentous.

We remain hopeful that artificial intelligence will help usher in a Golden Age of Knowledge, then ultimately of Wisdom. This is not to deny the possibility of dark futures with human subjugation by robot overlords or all-too-human political despots, etc. In order to avoid these dystopias we need to know and understand the real dangers we are now facing, including, without limitation, AI, and act accordingly. The AI dangers of unethical robots is another area where lawyers could work with scientists and others to make valuable contributions to the future of humanity.

In closing I leave you with a question, who would you rather hang-out with, a well informed person, a knowledgeable person, or a wise one? Here are my thoughts. One important thing I forgot to mention in my video is that the wise are always funny. If they sound wise, but are very serious, you know you are in the presence of a merely knowledgable person who has pretensions of wisdom. Run.

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Document Review and Predictive Coding: Video Talks – Part One

March 1, 2016

predictive_coding_3.0This is the first of seven informal video talks on document review and predictive coding. These short videos share my thoughts on the e-Discovery Team’s eight-step work flow for document review, shown above. I explain predictive coding and the Team’s Hybrid Multimodal Method. This first video addresses the big picture, why it is critical to our system of justice for the legal profession to keep up with technology, including especially active machine learning (predictive coding).

The flood of data now all too often hides the truth and frustrates justice. Cases tend to be decided on shadows, smoke and mirrors, because the key documents cannot be found. The needles of truth hide in vast haystacks in the clouds. Justice demands the truth, the full truth, not some bastardized twitter version.

Lady JusticeThe use of AI in legal search can change that. It can empower lawyers to find the needles and decide cases on what really happened, and do so quickly and inexpensively. It can usher in a new age of greater justice for all, blind to wealth and power. The stability of society demands nothing less.

4-5-6-only_predictive_coding_3.0The videos after this introduction are more technical. They delve into details of the work flow and show that it is easier than you might think. After all, only two of the eight steps (four and six) are unique to document reviews that use predictive coding. The others are found in any large scale review project, or should be.

For a more systematic explanation of the methods and eight-steps see Predictive Coding 3.0. Still more information on predictive coding and electronic document review can be found in the fifty-six articles published here on the topic since 2011.

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