ai | e-Discovery Team

More Additions to AI-Ethics.com: Offer to Host a No-Press Conference to Mediate the Current Disputes on AI Ethics, Report on the Asilomar Conference and Report on Cyborg Law

September 24, 2017

This week the Introduction and Mission Statement page of AI-Ethics.com was expanded. I also added two new blogs to the AI-Ethics website. The first is a report of the 2017 conference of the Future of Life Institute. The second is a report on Cyborg Law, subtitled, Using Physically Implanted AI to Enhance Human Abilities.

AI-Ethics.com Mission
A Conference to Move AI Ethics Talk from Argument to Dialogue

The first of the three missions of AI-Ethics.com is to foster dialogue between the conflicting camps in the current AI ethics debate. We have now articulated a specific proposal on how we propose to do that, namely by hosting a conference to move AI ethics talk from argument to dialogue. I propose to use professional mediators to help the parties reach some kind of base consensus. I know we have the legal skills to move the feuding leaders from destructive argument to constructive dialogue. The battle of the ethics robots must stop!

In arguments nobody really listens to try to understand the other side. If they hear at all it is just to analyze and respond, to strike down. The adversarial argument approach only works if there is a fair, disinterested judge to rule and resolve the disputes. In the ongoing disputes between opposing camps in AI ethics there is no judge. There is only public opinion. In dialogue the whole point is to listen and hear the other side’s position. The idea is to build common understanding and perhaps reach a consensus from common ground. There are no winners unless both sides win. Since we have no judges in AI ethics, the adversarial debate now raging is pointless, irrational. It does more hard than good for both sides. Yet this kind of debate continues between otherwise very rational people.

The AI-Ethic’s Debate page was also updated this week to include the latest zinger. This time the dig was by Google’s head of search and AI, John Giannandrea, and was, as usual, directed against Elon Musk. Check out the page to see who said what. Also see: Porneczi, Google’s AI Boss Blasts Musk’s Scare Tactics on Machine Takeover (Bloomberg 9/19/17).

The bottom line for us now is how to move from debate to dialogue. (I was into that way before Sedona.) For that reason, we offer to host a closed meeting where the two opposing camps can meet and mediate.It will work, but only when the leaders of both sides are willing to at least be in the same room together at the same time and talk this out.

Here is our revised Mission page providing more details of our capabilities. Please let me know if you want to be a part of such a conference or can help make it happen.

We know from decades of legal experience as practicing attorneys, mediators and judges that we can overcome the current conflicts. We use confidential dialogues based on earned trust, understanding and respect. Social media and thirty-second sound bites, which characterize the current level of argument, will never get us there. It will, and already has, just exasperated the problem. AI-Ethics.com proposes to host a no-press allowed conference where people can speak to each other without concern of disclosure. Everyone will agree to maintain confidentiality. Then the biggest problem will be attendance, actually getting the leaders of both sides into a room together to hash this out. Depending on turn-out we could easily have dozens of breakout sessions and professional mediators and dialogue specialists assigned to each group.

The many lawyers already in AI-Ethics.com are well qualified to execute an event like that. Collectively we have experience with thousands of mediations; yes, some of them even involving scientists, top CEOs and celebrities. We know how to keep confidences, build bridges and overcome mistrust. If need be we can bring in top judges too. The current social media sniping that has characterized the AI ethics debate so far should stop. It should be replaced by real dialogue. If the parties are willing to at least meet, we can help make it happen. We are confident that we can help elevate the discussion and attain some levels of beginning consensus. At the very least we can stop the sniping. Write us if you might be able to help make this happen. Maybe then we can move onto agreement and action.

Future of Life Institute Asilomar Conference

The Future of Life Institute was founded by the charismatic, Max Tegmark, author of Life 3.0: Being Human in the Age of Artificial Intelligence (2017). This is a must-read, entry level book on AI, AI ethics and, as the title indicates, the future of life. Max is an MIT professor and cosmologist. The primary funding for his Institute is from none other than Elon Musk. The 2017 conference was held in Asilomar, California and so was named the Asilomar Conference. Looks like a very nice place on the coast to hold a conference.

This is the event where the Future of Life Institute came up with twenty-three proposed principles for AI ethics. They are called, as you might have guessed, the Asilomar Principles. I will be writing about these in the coming months as they are the most detailed list of principles yet created.

The new web page I created this week reports on the event itself, not the principles. You can learn a lot about the state of the law and AI ethics by reviewing this page and some of the videos shared there of conference presentations. We would like to put on an event like this, only more intimate and closed to press as discussed.

We will keep pushing for a small confidential dialogue based event like this. As mostly lawyers around here we know a lot about confidentiality and mediation. We can help make it happen. We have some places in Florida in mind for the event that are just as nice as Asilomar, maybe even nicer. We got through Hurricane Irma alright and are ready to go, without or without Musk’s millions to pay for it.

Cyborg Law and Cyber-Humans

The second new page in AI-Ethics.com is a report on Cyborg Law: Using Physically Implanted AI to Enhance Human Abilities. Although we will build and expand on this page in the future, what we have created so far relies primarily upon a recent article and book. The article is by Woodrow Barfield and Alexander Williams, Law, Cyborgs, and Technologically Enhanced Brains (Philosophies 2017, 2(1), 6; doi: 10.3390/philosophies2010006). The book is by the same Woodrow Barfield and is entitled Cyber-Humans: Our Future with Machines (December, 2015). Our new page also includes a short discussion and quote from Riley v. California, 573 U.S. __, 189 L.Ed.2d 430, 134 S.Ct. 2473 (2014).

Cyborg is a term that refers generally to humans with technology integrated into their body. The technology can be designed to restore lost functions, but also to enhance the anatomical, physiological, and information processing abilities of the body. Law, Cyborgs, and Technologically Enhanced Brains.

The lead author of the cited article on cyborg law, Woody Barfield is an engineer who has been thinking about the problems of cyborg regulation longer than anyone. Barfield was an Industrial and Systems Engineering Professor at the University of Washington for many years. His research focused on the design and use of wearable computers and augmented reality systems. Barfield has also obtained both JD and LLM degrees in intellectual property law and policy. The legal citations throughout his book, Cyber-Humans, make this especially valuable for lawyers. Look for more extended discussions of Barfield’s work here in the coming months. He is the rare engineer who also understands the law.

1 Comment | AI Ethics, informaton, knowledge, Technology, wisdom | Tagged: ai, borg, ethics, science | Permalink
Posted by Ralph Losey

New Draft Principles of AI Ethics Proposed by the Allen Institute for Artificial Intelligence and the Problem of Election Hijacking by Secret AIs Posing as Real People

September 17, 2017

One of the activities of AI-Ethics.com is to monitor and report on the work of all groups that are writing draft principles to govern the future legal regulation of Artificial Intelligence. Many have been proposed to date. Click here to go to the AI-Ethics Draft Principles page. If you know of a group that has articulated draft principles not reported on our page, please let me know. At this point all of the proposed principles are works in progress.

The latest draft principles come from Oren Etzioni, the CEO of the Allen Institute for Artificial Intelligence. This institute, called AI2, was founded by Paul G. Allen in 2014. The Mission of AI2 is to contribute to humanity through high-impact AI research and engineering. Paul Allen is the now billionaire who co-founded Microsoft with Bill Gates in 1975 instead of completing college. Paul and Bill have changed a lot since their early hacker days, but Paul is still into computers and funding advanced research. Yes, that’s Paul and Bill below left in 1981. Believe it or not, Gates was 26 years old when the photo was taken. They recreated the photo in 2013 with the same computers. I wonder if today’s facial recognition AI could tell that these are the same people?

Oren Etzioni, who runs AI2, is also a professor of computer science. Oren is very practical minded (he is on the No-Fear side of the Superintelligent AI debate) and makes some good legal points in his proposed principles. Professor Etzioni also suggests three laws as a start to this work. He says he was inspired by Aismov, although his proposal bears no similarities to Aismov’s Laws. The AI-Ethics Draft Principles page begins with a discussion of Issac Aismov’s famous Three Laws of Robotics.

Below is the new material about the Allen Institute’s proposal that we added at the end of the AI-Ethics.com Draft Principles page.

_________

Oren Etzioni, a professor of Computer Science and CEO of the Allen Institute for Artificial Intelligence has created three draft principles of AI Ethics shown below. He first announced them in a New York Times Editorial, How to Regulate Artificial Intelligence (NYT, 9/1/17). See his TED Talk Artificial Intelligence will empower us, not exterminate us (TEDx Seattle; November 19, 2016). Etzioni says his proposed rules were inspired by Asimov’s three laws of robotics.

An A.I. system must be subject to the full gamut of laws that apply to its human operator.
An A.I. system must clearly disclose that it is not human.
An A.I. system cannot retain or disclose confidential information without explicit approval from the source of that information.

We would certainly like to hear more. As Oren said in the editorial, he introduces these three “as a starting point for discussion. … it is clear that A.I. is coming. Society needs to get ready.” That is exactly what we are saying too. AI Ethics Work Should Begin Now.

Oren’s editorial included a story to illustrate the second rule on duty to disclose. It involved a teacher at Georgia Tech named Jill Watson. She served as a teaching assistant in an online course on artificial intelligence. The engineering students were all supposedly fooled for the entire semester course into thinking that Watson was a human. She was not. She was an AI. It is kind of hard to believe that smart tech students wouldn’t know that a teacher named Watson, who no one had ever seen or heard of before, wasn’t a bot. After all, it was a course on AI.

This story was confirmed by a later reply to this editorial by the Ashok Goel, the Georgia Tech Professor who so fooled his students. Professor Goel, who supposedly is a real flesh and blood teacher, assures us that his engineering students were all very positive to have been tricked in this way. Ashok’s defensive Letter to Editor said:

Mr. Etzioni characterized our experiment as an effort to “fool” students. The point of the experiment was to determine whether an A.I. agent could be indistinguishable from human teaching assistants on a limited task in a constrained environment. (It was.)

When we did tell the students about Jill, their response was uniformly positive.

We were aware of the ethical issues and obtained approval of Georgia Tech’s Institutional Review Board, the office responsible for making sure that experiments with human subjects meet high ethical standards.

Etzioni’s proposed second rule states: An A.I. system must clearly disclose that it is not human. We suggest that the word “system” be deleted as not adding much and the rule be adopted immediately. It is urgently needed not just to protect student guinea pigs, but all humans, especially those using social media. Many humans are being fooled every day by bots posing as real people and creating fake news to manipulate real people. The democratic process is already under siege by dictators exploiting this regulation gap. Kupferschmidt, Social media ‘bots’ tried to influence the U.S. election. Germany may be next (Science, Sept. 13, 2017); Segarra, Facebook and Twitter Bots Are Starting to Influence Our Politics, a New Study Warns (Fortune, June 20, 2017); Wu, Please Prove You’re Not a Robot (NYT July 15, 2017); Samuel C. Woolley and Douglas R. Guilbeault, Computational Propaganda in the United States of America: Manufacturing Consensus Online (Oxford, UK: Project on Computational Propaganda).

In the concluding section to the 2017 scholarly paper Computational Propaganda by Woolley (shown here) and Guilbeault, The Rise of Bots: Implications for Politics, Policy, and Method, they state:

The results of our quantitative analysis confirm that bots reached positions of measurable influence during the 2016 US election. … Altogether, these results deepen our qualitative perspective on the political power bots can enact during major political processes of global significance. …

Most concerning is the fact that companies and campaigners continue to conveniently undersell the effects of bots. … Bots infiltrated the core of the political discussion over Twitter, where they were capable of disseminating propaganda at mass-scale. … Several independent analyses show that bots supported Trump much more than Clinton, enabling him to more effectively set the agenda. Our qualitative report provides strong reasons to believe that Twitter was critical for Trump’s success. Taken altogether, our mixed methods approach points to the possibility that bots were a key player in allowing social media activity to influence the election in Trump’s favour. Our qualitative analysis situates these results in their broader political context, where it is unknown exactly who is responsible for bot manipulation – Russian hackers, rogue campaigners, everyday citizens, or some complex conspiracy among these potential actors.

Despite growing evidence concerning bot manipulation, the Federal Election Commission in the US showed no signs of recognizing that bots existed during the election. There needs to be, as a minimum, a conversation about developing policy regulations for bots, especially since a major reason why bots are able to thrive is because of laissez-faire API access to websites like Twitter. …

The report exposes one of the possible reasons why we have not seen greater action taken towards bots on behalf of companies: it puts their bottom line at risk. Several company representatives fear that notifying users of bot threats will deter people from using their services, given the growing ubiquity of bot threats and the nuisance such alerts would cause. … We hope that the empirical evidence in this working paper – provided through both qualitative and quantitative investigation – can help to raise awareness and support the expanding body of evidence needed to begin managing political bots and the rising culture of computational propaganda.

This is a serious issue that requires immediate action, if not voluntarily by social media providers, such as Facebook and Twitter, then by law. We cannot afford to have another election hijacked by secret AIs posing as real people.

As Etzioni stated in his editorial:

My rule would ensure that people know when a bot is impersonating someone. We have already seen, for example, @DeepDrumpf — a bot that humorously impersonated Donald Trump on Twitter. A.I. systems don’t just produce fake tweets; they also produce fake news videos. Researchers at the University of Washington recently released a fake video of former President Barack Obama in which he convincingly appeared to be speaking words that had been grafted onto video of him talking about something entirely different.

See: Langston, Lip-syncing Obama: New tools turn audio clips into realistic video (UW News, July 11, 2017). Here is the University of Washington YouTube video demonstrating their dangerous new technology. Seeing is no longer believing. Fraud is a crime and must be enforced as such. If the government will not do so for some reason, then self- regulations and individual legal actions may be necessary.

In the long term Oren’s first point about the application of laws is probably the most important of his three proposed rules: An A.I. system must be subject to the full gamut of laws that apply to its human operator. As mostly lawyers around here at this point, we strongly agree with this legal point. We also agree with his recommendation in the NYT Editorial:

Our common law should be amended so that we can’t claim that our A.I. system did something that we couldn’t understand or anticipate. Simply put, “My A.I. did it” should not excuse illegal behavior.

We think liability law will develop accordingly. In fact, we think the common law already provides for such vicarious liability. No need to amend. Clarify would be a better word. We are not really terribly concerned about that. We are more concerned with technology governors and behavioral restrictions, although a liability stick will be very helpful. We have a team membership openings now for experienced products liability lawyers and regulators.

4 Comments | AI Ethics, Lawyers Duties, Technology | Tagged: ai, AI Ethics Principles, machine learning, robots, science, technology | Permalink
Posted by Ralph Losey

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

April 5, 2016

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.

The 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.

socrates3 The 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_VR Bottom 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.

Although 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).

We 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 sensors, animated 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.

Facebook’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.

The 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.

On 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 Immersion. VR 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.

The 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.

The 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.

The use of implants that is part of the first prediction is also progressing rapidly. See Eg. Grinders, Cyborgs & Transhumanists; Scientists propose ‘cortical modem’ implant; DARPA is sending brain implants on a voyage round the body to power artificial limbs; Do-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_future New 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:

“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.”

DAPRA chart by Dr. Weber

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

Nerves_Vagus In 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.

I neuro_stimulation_BRAIN f 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.

The 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 eg. What Do These Top Industry Experts Use Social Media For?; How Social Media Can Help Students Study; Connecting 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.

Universities 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 Schools; edX – Free online courses from the world’s best universities; The 30 Most Innovative Online Colleges; COURSERA.

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_Heart Seven 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_GO The 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 Devin Coldewey, 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

The 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 Phoenix, How 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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3 Comments | informaton, knowledge, Lawyers Duties, Technology, wisdom | Tagged: ai, information, knowledge, knowledge; wisdom, predictions, too much information, virtual reality, wisdom | Permalink
Posted by Ralph Losey

Information Governance v Search: The Battle Lines Are Redrawn

February 8, 2015

There is a battle in the legal tech world between Information Governance and Search. It reflects a larger conflict in IT and all of society. Last year I came to believe that Information Governance’s preoccupation with classification, retention, and destruction of information was a futile pursuit. I challenged these activities as inefficient and doomed to failure in the age of information explosion. Instead of classify and kill, I embraced the googlesque approach of save and search.

I became wary of the whole approach of governing information as hostile to individual privacy rights and liberties. In my experience IG rules only seemed to serve the large entities who made them. For instance, IG rules typically state that employees have no reasonable expectation of privacy to any communications they may have at work, that all of their email accounts, even personal, can be searched at will. Their every keystroke can be monitored and recorded. Old school records policies seemed to encourage these draconian approaches. Under current U.S. law, these rules are usually enforceable.

Although I appeared to be a lonely searcher-voice in the legal technology world, which is, after all, not too surprising, since law itself is an attempt to govern, I had plenty of good company in the general technology world. There is not only Google, whom you would expect, but also EMC, GE, and a host of others. The debate is part of larger issues surrounding Big Data.

I took up arms against IG as I then knew it, which I understood to be an activity primarily designed to classify, control and delete records. I knew this conflict of approaches in how to treat information was important, and I felt compelled to speak out. Govern or Search is not just a legal issue. It is a cultural issue.

When I first spoke out with a contrarian voice, it created a controversy. Most in the legal establishment thought I was just plain wrong. Many wrote articles respectfully opposing my position. Many more were ready to argue, to fight even. Some did. I was even yelled at once at a CLE speakers dinner by a distinguished leader of IG who bristled at my challenges (some might say baiting). She insisted that everyone in her very large corporation could easily comply with her lengthy retention schedules. Oh brother.

The more thoughtful members of the IG leadership responded to the opposition with dialogue. This requires listening and trying to understand the points of the other side. I understand and favor dialogue, which is what attracted me to Sedona back in the day. I learned from this dialogue that IG, like Search, is not a monolith, that there are various factions and groups within IG.

After months of dialogue with the modern camp of IG, I have come to see that the contest between Search and IG need not be a fight to the death. I came to see a potential win/win outcome to this struggle. To those followers of IG who, like Jason R. Baron, have already transcended the old roles of traditional records keepers, there is no need to fight at all. My quarrel is, instead, with the old-liners, the Records Manager strata of IG who are obsessed with ESI classification and killing. To those who have let go of that traditional role, and already been reborn as multimodal, AI-enhanced Information experts, I have no quarrel. You could say that a partial settlement has been reached by a realignment of the parties.

My opposition continues only with the old-time record keepers with their long complex retention schedules and harsh top down rules. I will continue to oppose these caterpillars, no matter what smoke they may blow my way, unless and until they bow to the inevitable electronic metamorphosis. There has been no settlement with them. Trial in the world court of public opinion continues. I will oppose them for their own good. The librarians should relax, perhaps inhale a bit, cocoon, learn the new tech ways, and reemerge.

The battle against the new age Information Governors is, however, over; although I will remain watchful. Why? Because they in fact have already embraced the search and technology ways of “my side.” As Sun Tzu said: “The supreme art of war is to subdue the enemy without fighting.” Search and technology have won. Information has won. They are all one.

Underneath the superficial differences, and the annoying tendency of IG to claim every other field, including Search, as a subset of its own, both sides share almost all of the same values and concerns. Members of both sides are committed to cybersecurity and privacy, and do not see them as an either or choice. That is critical. We must not sacrifice all of our privacy and individual rights in the name of security.

Where are the rights to both privacy and security in the challenge of too-much-information? I am a strong proponent of privacy, and so are many in the IG world. I am also a strong proponent of cybersecurity. I think it is possible to have both. In both the Search and IG camps their are people who agree with me on these points, and others who disagree. Many see it as one or the other, especially people in government. They take extreme views favoring either security or privacy. Many in both tech and government simply dismiss the importance of privacy, and say just get over it. Advocacy for individual privacy is a separate battle in both worlds, IG and Search. The same is true over cybersecurity. I favor a balanced approach, and so do many in the IG world.

The real battle is not between new IG and Search, it is between the extreme positions that can be found in both camps on the issues of privacy and security. I advocate for a middle ground, privacy and security, and so do many in the IG world. I am also apprehensive of the emergence of Big Brother from Big Data, but, as it turns out, so are many in the IG world. Our common ground is far greater than our differences. Thus a realignment of the parties to our common foes.

Death of a Caterpillar

The traditionalists in the IG world whom I continue to oppose, the ones who are glorified records managers, have another five years, at best, before complete obsolescence. The classify and control lock-down approach of records management is contrary to the time. It cannot withstand the continuing exponential growth of data, nor the basic entropy forces aligned against all attempts to govern by all-too-human rules and compliance. Records managers are caterpillars waiting to be reborn. They should withdraw into a cocoon and embrace the change.

My prediction is that within five years the traditional records management activities, specifically the classification, filing and obsessive deletion of data, will no longer be worth the effort. (I concede that some deletion is necessary and will continue.) It will be far more efficient to rely on advanced Search, than classify and kill. This five-year projection assumes continued exponential growth and complexity of ESI. Breakthroughs in search in the next five years would be nice too, but my prediction does not depend on that. It assumes instead a slow, steady improvement of search technologies. They are already awesome, when used properly. The caterpillar record managers will grow big and fly high with search if they will only allow themselves to have new eyes.

Alas, as of now the old-school IG’ers still see the world through paper glasses. They think that Information Governance is like paper records management, just with more zeros after the number of records involved. The file-everything librarian mentality lives on, or tries to. Yawn. There is a reason nobody in the C-Suite ever took records managers seriously. Dressing them up with new titles is not going to change anything. They have to really change and be reborn into the digital world. They need to learn to fly with search, instead of creeping along with filing rules. They need to embrace the new high-tech world of IG 2.0.

ESI Grows and Changes Too Fast for Traditional Governance

Electronic information is a totally new kind of force, something Mankind has never seen before. Digital Information is a Genie out of the bottle. It cannot be captured. It cannot be managed. It certainly cannot be governed. It cannot even be killed. Forget about trying to put it back in the bottle. It is breeding faster than even Star Trek’s Tribbles could imagine. Like Baron and Paul discussed in their important 2007 law review, ESI is like a new Universe, and we are living just moments after the Big Bang. George L. Paul and Jason R. Baron, Information Inflation: Can the Legal System Adapt? 13 RICH. J.L. & TECH. 10 (2007).

Ludwig Wittgenstein

What many outside of Google, Baron, and Paul fail to grasp is that Information has a life of its own. Id. at FN 30 (quoting Ludwig Wittgenstein (a 20th Century Austrian philosopher whom I was forced to study while in college in Vienna): “[T]o imagine a language is to imagine a form of life.”) Electronic information is a new and unique life form that defies all attempts of limitation, much less governance. As James Gleick observed in his book on information science, everything is a form of information. The Universe itself is a giant computer and we are all self-evolving algorithms. Gleick, The Information: a history, a theory, a flood.

Many claim that information wants to be free. It does not want to be governed, or charged for. Information is more useful when free and when it is not subject to transitory restraints. Still, it must also be respected and safeguarded.

Stuart Brand of Whole Earth Catalogue fame is credited with originating the phrase information wants to be free, but in fact his quote is taken out of context. His whole quote from the Whole Earth Review, May 1985, actually was:

On the one hand information wants to be expensive, because it’s so valuable. The right information in the right place just changes your life. On the other hand, information wants to be free, because the cost of getting it out is getting lower and lower all the time. So you have these two fighting against each other.

Regardless of the economic aspects, and whether information really wants to be free, as a practical matter Information itself cannot be governed, even if some of it can be commoditized. Information is moving and growing far too fast for governance. But not too fast for search or security, at least I hope not. There are promising tech methods on the horizon that should guaranty privacy. See eg.: Entangled Photons on Silicon Chip: Secure Communications & Ultrafast Computers, The Hacker News, 1/27/15 (quantum entanglement encryption as the ultimate privacy solution).

Digitized information is like a nuclear reaction that has passed the point of no return. The chain reaction has been triggered. This is what exponential growth really means. In time such fission vision will be obvious. Even people without Google glasses will be able to see it. Just look at the extent of ESI proliferated during any minute of the world today as shown by the chart below. And the volume of ESI stored doubles at least every two years.

In the meantime we have records managers running around who serve like heroic bomb squads. Some know that it is just a noble quest, doomed to failure. Most do not. Some helicopter in and out of corporate worlds like wannabe Brian Williamses. They take flack (for real). They attempt to defuse ticking information bombs. They build walls around it. They confidently set policies and promulgate rules. They inventory it, map it, delete it. They talk sternly about enforcement of rules. (Of course, that never happens, which is one reason the whole effort is futile.) They automate deletion. They also try to automate filing. Some are even starting to make robot file clerks. But is it worth the effort? Might the time and money be better spent to protect our data from black hat hackers? To protect our privacy and individual rights?

The old school IG’ers are all working diligently to try to solve today’s problems of information management. But, all the while, ever new problems encroach upon their walls. They cannot keep up with this growth, the new forms of information. The next generation of exponential growth builds faster than anyone can possibly govern. Do they not know that the nuclear bomb has already exploded? The tipping point has already past?

Information retention policies that are being created today are like sand castles built at low tide. Can you hear the next wave of data generated by the Internet of Things? It will surely wash away all of today’s efforts. There will always be more data, more unexpected new forms of information.

IG Through the Eyes of an AI-Enhanced Butterfly

I used to endorse the old ways myself. I used to be a caterpillar. ESI feared me. I was all about killing data as soon as you no longer had a business need for it. I was all in favor of short retention schedules. But, that was then. That was before I really mastered predictive coding, which in my version means active machine learning. That was before I understood much better than I used to, that we are living in a whole new world of Big Data Analytics.

I now realize that is possible to dramatically reduce the costs of document review. I now realize the incredible power of AI enhanced search. I am starting to realize the potential value of large pools of seeming worthless data. These realizations change everything. I have been reborn as a butterfly with digital wings of AI.

Old school IG, by which I mean e-dressed-up records management, is not the way to deal with today’s all digital world. We are all suffering from information overload. We are all looking for a solution. Will we cope by Search and advanced technology, or by vertical forces of governance and man-made laws? This is an important question for everyone.

My understanding and experiences with Big Data analytics over the last few years have led me understand that more data can mean more intelligence, that it does not necessarily mean more trouble and expense. I understand that more and bigger data has its own unique values, so long as it can be analyzed and searched effectively.

This change of position was reinforced by my observing many litigated cases where companies no longer had the documents they needed to prove their case. The documents had short retention spans. They had all been destroyed in the normal course of business before litigation was ever anticipated. I have seen first hand that yesterday’s trash can be tomorrow’s treasure. I will not even go into the other kind of problems that very short retention policies can place upon a company to immediately implement a lit-hold. The time pressures to get a hold in place can be enormous and thus errors become more likely.

There is a definite dark side to data destruction that many do not like to face. No one knows for sure when data has lost its value. The meaningless email of yesterday about lunch at a certain restaurant could well have a surprise value in the future. For instance, a time-line of what happened when, and to whom, is sometimes an important issue in litigation. These stupid lunch emails could help prove where a witness was and when. They could show that a witness was at lunch, out of the office, and not at a meeting as someone else alleges.

Who knows what value such seemingly worthless data may someday have? Perhaps millions of emails of ten thousand employees about lunch could be used someday to prove or disprove certain class-action allegations. Outside of the little world of litigation, perhaps the information could help management make smarter business decisions. For instance, they could help a company to decide whether to open a company cafeteria, and if so, what kind of food its employees would really like to have served there. Information can prove what really happened in the past and can help you to make the right decisions. With smart search, there can be great hidden value in too much information. Businesses are starting to see this now where Big Data mining is all the buzz. We lawyers need to start doing the same.

The point is, with the never-ending uncertainties of tomorrow, you can never know for sure that information is valueless and should be destroyed, and what information has value and should be saved. There may be an unimaginably large haystack of information, and you may think it only has a few valuable needles. But, you never really know. Today’s irrelevant straw could be tomorrow’s relevant needle. With the AI based search capacities we already have, capacities that are surely to improve, when you need to find a needle in these near infinite stacks, you will be able to. The cost of storage itself has become so low as to become a negligible factor for most large corporations. Why destroy data when you can effectively search it and mine it for value? That is the butterfly view.

Information Technology View on Records Management v. Search

The general IT world is also struggling between whether to go all-in with Search, or keep trying to solve the problem of too much information with records management. Unlike the legal world, where my vote for Search is still a new and small minority, in the IT world search is already a strong voice. Many in IT see attempts at information governance as a knee-jerk reaction from those still transitioning into the digital world. In the last year it seems to me that those favoring search over filing are gaining ground in the technology world. From what I see, the retain and search solution is surging ahead of the old-fashioned govern and destroy approach.

Consider, for instance, the policy of search stated by hot new companies like Pivotal, which is a joint venture between EMC, VMware, and GE. Pivotal’s public mantra is: Store Everything. Analyze Anything. Build the Right Thing.

Pivotal urges its customers to store everything, not just its organized databases, such as financial records. It provides the ability to store all types of data, including especially disorganized data, such as employee emails and texts, and do so in the same place. That is the new gold standard. Pivotal explains the value of store everything this way:

Store everything to create a rich data repository for business needs. With unlimited, supported Pivotal HD enterprises never have to worry about data growth constraints or runaway license costs.

Its suite of Big Data software is designed to allow a company to store all data types in the same place, which it, along with EMC, and others, have started calling a Data Lake. All types and formats of ESI become readable, searchable, in the Data Lake. They do not have to be stored separately, nor searched and analyzed separately. The Data Lakes are also infinitely expandable. Unlike real lakes, they cannot flood. They can instead grow unhindered in cyberspace. All they need are more servers.

These are major breakthroughs and mean the inevitable end of separate data silos by format type and size. This allows you to, in Pivotal’s words, leverage all your data, forever, and place it all in a centralized Business Data Lake. You can analyze multiple data sets and types that live in the Business Data Lake. This allows you to determine the integration value of multiple data sets and types. It also makes storage of Big Data much less expensive.

Bottom line, when all of your data is saved forever, and subject to advanced search analytics, you are empowered to build the right thing. In Pivotal’s words, building the right thing means to deliver a transformative solution to meet today’s demanding business needs. For business that means creation of new products, new advertising, new sales and business methods. For law it means building your case, finding evidence, and creating new legal methods. The promise of Big Data is changing everything in the tech world. Some in IG are also aware of these facts and are adapting ESI management accordingly.

AI-Enhanced Big Data Search Will Greatly Simplify Information Governance

The key problem all large organizations face is the challenge to find the information they need, when they need it, and do so in a cheap and efficient manner. Information needs are determined by both law and personal preferences, including business operation needs. In order to find information, you must first have it. Not only that, you must keep it until you need it. To do that, you need to preserve the information. If you have already destroyed information, really destroyed it I mean, not just deleted it, then obviously you will not be able to find it. You cannot find what does not exist, as all Unicorn chasers eventually find out.

This creates a basic problem for old-school IG because the whole system is based on a notion that the best way to find valuable information is to destroy worthless information. Much of old IG is devoted to trying to determine what information is a valuable needle, and what is worthless chaff. This is because everyone knows that the more information you have, the harder it is for you to find the information you need. The idea is that too much information will cut you off. These maxims were true in the pre-AI-Enhanced Search days, but are, IMO, no longer true today.

In order to meet the basic goal of finding information, old-school IG focuses its efforts on the proper classification of information. Again, the idea was to make it simpler to find information by preserving some of it, the information you might need to access, and destroying the rest. That is where records classification comes in.

The question of what information you need has a time element to it. The time requirements are again based on personal and business operations needs, and on thousands of federal, state and local laws. Information governance thus became a very complicated legal analysis problem. There are literally thousands of laws requiring certain types of information to be preserved for various lengths of time. Of course, you could comply with most of these laws by simply saving everything forever, but, in the past, that was not a realistic solution. There were severe limits on the ability to save information, and the ability to find it. Also, it was presumed that the older information was, the less value it had. Almost all information was thus treated like news.

These ideas were all firmly entrenched before the advent of Big Data and AI-enhanced data mining. In fact, in today’s world there is good reason for Google to save every search, ever done, forever. Some patterns and knowledge only emerge in time and history. New information is sometimes better information, but not necessarily so. In the world of Big Data all information has value, not just the latest.

The records life-cycle ideas all made perfect sense in the world of paper information. It cost a lot of money to save and store paper records. Everyone with a monthly Iron Mountain paper records storage bill knows that. Even after the computer age began, it still cost a fair amount of money to save and store ESI. The computers needed to buy and maintain digital storage used to be very expensive. Finding the ESI you needed quickly on a computer was still very difficult and unreliable. All we had at first was keyword search, and that was very ineffective.

Due to the costs of storage, and the limitations of search, tremendous efforts were made by record managers to try to figure out what information was important, or needed, either from a legal perspective, or a business necessity perspective, and to save that information, and only that information. The old idea behind IG was to destroy the ESI you did not need or were not required by law to preserve. This destruction saved you money, and, it also made possible the whole point of IG, to find the information you wanted, when you wanted it.

Back in the pre-AI search days, the more information you had, the harder it was to find the information you needed. That still seems like common sense. Useless information was destroyed so that you could find valuable information. In reality, with the new and better algorithms we now have for AI-enhanced search, it is just the reverse. The more information you have, the easier it becomes to find what you want. You now have more information to draw upon.

That is the new reality of Big Data. It is a hard intellectual paradigm to jump, and seems counter-intuitive. It took me a long time to get it. The new ability to save and search everything cheaply and efficiently is what is driving the explosion of Big Data services and products. As the save everything, find anything way of thinking takes over, the classification and deletion aspects of IG will naturally dissipate. The records life-cycle will transform into virtual immortality. There is no reason to classify and delete, if you can save everything and find anything at low cost. The issues simplify; they change to how to save and search, although new collateral issues of security and privacy grow in importance.

Recent Breakthroughs in Artificial Intelligence
Make Possible Save Everything, Find Anything

The New York Times in an opinion editorial in late 2014 discussed recent breakthroughs in Artificial Intelligence and speculated on alternative futures this could create. Our Machine Masters, NT Times Op-Ed, by David Brooks (October 31, 2014). The Times article quoted extensively another article in the Wired by technology blogger Kevin Kelly: The Three Breakthroughs That Have Finally Unleashed AI on the World. Kelly argues, as do I, that artificial intelligence has now reached a breakthrough level. This artificial intelligence breakthrough, Kevin Kelly argues, and David Brook’s agrees, is driven by three things: cheap parallel computation technologies, big data collection, and better algorithms. The upshot is clear in the opinion of both Wired and the New York Times: “The business plans of the next 10,000 start-ups are easy to forecast: Take X and add A.I. This is a big deal, and now it’s here.”

These three new technology advances change everything. The Wired article goes into the technology and financial aspects of the new AI; it is where the big money is going and will be made in the next few decades. If Wired is right, then this means in our world of e-discovery, companies and law firms will succeed if, and only if, they add AI to their products and services. The firms and vendors who add AI to document review, and project management, will grow fast. The non-AI enhanced vendors, non-AI enhanced software, will go out of business. The law firms that do not use AI tools will shrink and die. The same goes for IG.

The three big new advances that are allowing better and better AI are nowhere near to threatening the jobs of human judges or lawyers, although they will likely reduce their numbers, and certainly will change their jobs. We are already seeing these changes in Legal Search and Information Governance. Thanks to cheap parallel computation, we now have Big Data Lakes stored in thousands of inexpensive, cloud computers that are operating together. This is where open-sourced software like Hadoop comes in. They make the big clusters of computers possible. The better algorithms is where better AI-enhanced Software comes in. This makes it possible to use predictive coding effectively and inexpensively to find the information needed to resolve law suits. The days of vast numbers of document reviewer attorneys doing linear review are numbered. Instead, we will see a few SMEs, working with small teams of reviewers, search experts, and software experts.

The role of Information Managers will also change drastically. Because of Big Data, cheap parallel computing, and better algorithms, it is now possible to save everything, forever, at a small cost, and to quickly search and find what you need. The new reality of Save Everything, Find Anything undercuts most of the rationale of old paradigm of Information Governance, but not the new. The new paradigm of IG gets it, and relies on AI technology.

The save everything forever AI search model of new IG will create a variety of new legal work for lawyers, but they will be the next generation of tech lawyers. The cybersecurity protection and privacy aspects of Big Data Lakes are already creating many new legal challenges and issues. Big Data breaches already mean Big Money for the law firms who offer curative services. That is happening now. In the future lawyers will play a larger role in preventative security issues. More legal issues are sure to arise with the expansion of Big Data, AI, and development of the next generation of IG. From what I have seen technology creates new jobs as fast as it eliminates old ones. The real challenge is keeping up with the changes.

Conclusion

Ralph_Losey_2013_aba

Preservation is far less difficult when you are anyway saving everything forever. With this approach the challenging task remaining in e-discovery is really just search. That is why I say, only slightly tongue in cheek, that Information Governance is actually a sub-set of Search, not visa versa. In so far as e-discovery is concerned, that is true; but IG is a concern that goes beyond e-discovery.

In the IG now emerging – IG 2.0 – Information Governance serves as a kind of umbrella organization for all things information. It is not just a hyped up version of records management. It is a center of a high-tech wheel built around information. That image has traction for Search advocates such as myself, just so long as search is not considered to be just another spoke in the Wheel. Search has a much more important position. It is the tire around the wheel, where the rubber meets the road. In today’s world you are likely to get lost without it.