Recently Daniel Linna, Professor of Law and the Director of The Center for Legal Services Innovation at Michigan State University, published the first iteration of The Legal Services Innovation Index (LSII) The first part of this ambitious project is the Innovation Catalog of innovative products, legal services and consulting services offered by large law firms. It appears that the already impressively large catalog will be primarily managed by Linna’s law student support team and other volunteers based on their own research efforts and communal submissions. The second part of the project is the Law Firm Index (LFI) of ten innovation categories devised by Linna and his team and scored by applying a standardized set of keyword and key phrase searches of large law firm websites utilizing Google Advanced Search and recording the results counts in the LFI. The premise here is that innovative law firms will use innovation-related terms more frequently on their websites compared to non-innovative firms. The hope is that the Google search results counts will provide a reasonably objective means of measuring large law firm innovation across various temporal and demographic dimensions. Good idea…but a deeply flawed implementation.

Granted, Linna is quick to caution against reading too much into this first generation of the index. He dedicates a large portion of the site to the various limitations and challenges posed by relying on Google search results counts generated from what is basically law firm-generated propaganda. Nevertheless, he seems to be comfortable enough with the fundamental premise to release the details into the “wild” via an online Tableau-based data visualization tool that allows anyone to perform rudimentary grouping and sorting of the index. Already, we are seeing the first interpretive fruits of this initiative. See, for instance, here. Professor Linna himself mostly refrains from engaging in the fun and games of data interpretation. Instead, his message is more along the lines of an appeal for feedback on the effort. It is in response to that appeal that I offer my comments here. [Note: I want to emphasize that my specific criticisms of the methodology used to construct the LFI  are also identified in the Introduction and Methodology section that accompanies the LFI itself. Please refer to comment section below for Professor Linna’s response to this post and my reply to Professor Linna.]

Applying the Knowledge Management Smell Test

KM is one of the ten innovation categories tracked by the LFI. The specific Google search used in the measurement is: “knowledge management” OR “knowledge engineering.” The number of times I’ve personally used the term “knowledge engineering” or personally heard it used by a legal KM peer I could count on the fingers of one hand and still have enough fingers left over to flip the bird at anyone who claims to be a “knowledge engineer.” We’ll let that one slide because its almost universal irrelevance to the topic of legal KM has no meaningful effect on the results. Below is a screen grab of the KM index sorted by search result count (only the “top” 46 firms are shown here). The numbers shown above represent the number of pages on the law firms’ websites that purportedly refer to “knowledge management or “knowledge engineering.” Do those posted numbers pass your smell test? They certainly do NOT pass mine. Sure, I would expect to see Littler and Ogletree ranked high. They share two of the five most recent ILTA KM Professional of the Year Award winners (Susan Woodhouse and Patrick DiDomenico); but by that standard White & Case (Oz Benamram) is nowhere to be found, and Wilson Sonsini (Chris Boyd) and Debevoise (Steven Lastres) only make it into the lower half of the top 46. What I see is a mix of firms that legitimately belong somewhere near the top but also quite a few firms that I rarely or never come across as KM leaders and innovators. Just as importantly, quite a few of the firms I would expect to see in the top 46 are not listed. I strongly suspect that any random selection of 46 of the largest 263 firms with a weighting bias added based on firm (and website) size would yield a top 46 that “feels” about as valid as this one.

Over 5000 Pages that Refer to KM…Really?

One thing that should be immediately obvious to any legal KM practitioner is the absurd number of KM hits reported for many firms.  There is simply no way that KM is substantively referenced on more than, say, 10-15 pages for any given law firm website (a few very large firms with an extraordinary number of KM professionals may exceed that number due to posted biography pages). Indeed, show me a firm that actually dedicates more than one single substantive website page to its KM efforts, and I’ll show you a very rare exception to the rule. Despite that harsh reality, according to the LFI over 50 of the monitored firms have more than 15 KM pages. And then there’s Shearman’s and Ogletree’s 2000+ pages and Littler’s 5000+ pages!

Consistent with my skeptical expectations, I found that none of the dozen or so sites that I manually checked legitimately match the number of hits returned by Google. By cross-checking search results from Google with the individual websites’ internal search engines and by examining obvious false-hit pages returned by Google, I found four primary reasons for the gross search hit inflation:

• Some sites with the biggest hit inflation (e.g., Shearman, Ogletree and Littler) include either visible or hidden HTML code in page headers or footers that reference “knowledge management.”
• Some sites are structured to repeat the same page a number of times. For instance, a lawyer bio page may end up being counted as multiple hits because it appears in multiple practice or office subsites. Thus, a KM lawyer page may be counted multiple times and Google does not necessarily exclude the duplicates.
• Google’s Advanced Search page count is NOT based on exact matches of searched phrases. It is not uncommon for the words “knowledge” and “management” to appear somewhere on a page posted on a law firm website and Google will usually include those pages in its count. It will even include pages that have only one of the words. (Note: Using the “Verbatim” option in Google restricts results to the exact phrase specified in the search but does not return a total page count and, thus, was not used in the LFI measurement.)
• A KM lawyer (co)authors and posts numerous substantive legal alerts/articles on a firm’s website. Knowledge Management appears in the author title or credits included in the article but not substantively in the alert/article itself.

With these considerations in mind, and by way of example, let’s take a closer look at Littler’s numbers:

The inflated number reported for Littler in the LFI is almost completely due to the presence of knowledge management in (non-visible) HTML script that probably appears on every page on the site. When that site structuring issue is removed, Littler’s numbers fall in line with the rest of the pack. To me, the page counts highlighted in red above are the meaningful ones for Littler. To be sure, Littler is a widely recognized KM leader and innovator. As already noted, the firm deserves to appear at or near the top of any law firm innovation index. However, the fact that the chosen methodology for scoring the LFI happens to place Littler at the top is really just a lucky accident of how the firm’s website is structured and not because the specific LFI analytics strategy works. Littler is an extreme case, but many, if not all, of the other firms that ended up toward the top of the heap also benefited from some combination of the noted artificial boosts to their numbers, while other deserving firms are buried because they simply chose not to deploy similar website design and style decisions.

Knowledge Management-to-Noise Ratio

Even the most innovative firms are likely to reference their KM efforts, projects and awards relatively few times on their public websites. As noted, some larger firms with big KM staffs will also have more KM professional biography pages, but that only marginally signifies innovation and will perhaps inappropriately bias the index in favor of larger firms simply because they are larger and not because they are more innovative. Thus, the fundamental problem here is that this website search-based strategy generates a very low “signal” in relation to the “noise” generated by false hits from uses of these common words in unrelated contexts and magnified by duplicate pages and varying website structuring/design strategies. The result is an untrustworthy and largely random ordering.

What About the Other Categories?

KM is only one of the ten innovation categories tracked by the LFI, and it is the only one that I looked at in depth. However, even a cursory examination of the other categories reveals similar problems related to false hits caused by coincidental website structuring and styling, page duplication and over-inclusion based on Google’s miscounts of phrase searches that contain words that commonly appear in multiple legal website contexts. Consider, for example, the case of Berwin Leighton Paisner (BLP) in the artificial intelligence category. BLP is widely recognized for its pioneering AI work with RAVN, so it is hardly surprising that it cracks the top 15 in the AI category with a reported total of 269 webpage hits. Likewise, when I run the specified Google search (“machine learning” OR “deep learning” OR “artificial intelligence” site:blplaw.com) I get 277 results. However, by simply adding “-oil” to the search string, the hit count plummets to just nine results.  What does oil have to do with AI? As it turns out, both Artificial Intelligence and Oil and Gas are filters in the press release section of BLP’s website. Both of those terms appear on several hundred posted press release pages as selectable filters but neither appears in the (substantive) body of the press releases. In fact, only one posted press release appears to have the Artificial Intelligence tag applied; and as best I can tell, only about 12 pages on the BLP site actually relate to or substantively describe or promote BLP’s AI systems and services.

A search strategy that claims 1000+ results from individual law firm websites for ANY topic (let alone law firm operational topics) is obviously flawed. Nevertheless, 1000+ law firm results are reported for eight out of ten of the categories. In short, the same kind of signal-to-noise problem I saw in my more extensive review of the KM category appears to infest the other categories as well. You simply cannot assume that any individual law firm result is valid, which means that the index, as a comparative tool, is unreliable as well.

Shhhhhh…Don’t Tell the Law Firm Business Development and PR People About This

The worthy purpose behind the LSII is to stimulate large law firm innovation and ultimately to improve the delivery of legal services generally. An objective benchmark for comparing law firms will arm clients with better information and enable them to select more progressive firms. This could trigger a virtuous innovation improvement loop where law firms pay more attention to new legal service delivery models and competitively respond to improvements implemented by other firms. Sounds great…just one problem though. The index measures words, not deeds. Worse, it measures the words primarily generated by the PR function of law firms. Thus, the more attention and success the LSII achieves, the greater the risk that law firms will respond with SEO strategies targeted at raising their scores in the LFI rather than genuine (but far more expensive and difficult to implement) innovations. With no good way to validate the measurement itself and no way to distinguish between innocent PR padding and abusive optimizations, the credibility of the project will remain highly questionable.

The Not So Fatal Flaw?

Getting law firms to pay more lip service to innovation is a step in the right direction even if the methodology is flawed to begin with and vulnerable to being gamed, right? That seems to be argument some are making in support of the LSII undertaking, but I disagree. As things stand now, the LFI portion of the LSII project is rather obviously broken and untrustworthy. Setting aside the risks of SEO manipulation in the future, the clear and present danger is that the whole undertaking will reinforce the already hyper skepticism of the legal establishment toward virtually all of the “buzzwords” that comprise the search parameters at the core of the index. As an exercise in data analytics the index doubly fails: it fails to reasonably model the real status of law firm innovation efforts; and it fails to demonstrate the usefulness of data analytics itself as a tool to be embraced by lawyers. My advice here is to fail fast and move on to a better strategy for building a useful law firm index to supplement the otherwise worthwhile catalog portion of the project.

My working premise here is that many Biglaw firms experience a chasm effect when implementing new technology like the one described by Moore’s model. In this regard, different internal law firm groups generally behave consistently with the five stages of adoption described in the model. Specifically, when looking at enterprise search adoption in BigLaw firms, what we often see is a committed (but relatively small) collection of fans that swear by the power, flexibility and one-stop convenience of the technology. However, adoption stalls there, leaving a larger contingent of mostly indifferent and infrequent users and a smaller group of stragglers who give up, never try or become hostile to enterprise search. (Note that some enterprise search implementations have been structured to force adoption through replacement of previous search solutions. In those instances, an adoption measurement is less relevant than a user satisfaction measurement for determining the usefulness of my proposed application of Moore’s model.)

The Disclaimer Stuff

As far as I know, Moore’s chasm-based adoption model was neither devised for nor tested on adoption patterns inside of organizations. It is a model for adoption by businesses inside a market and basically takes a generalized macro perspective on what constitutes “adoption.” In later publications Moore also asserted that the chasm model works best for B2B use cases involving a purchasing decision and is less relevant to B2C technology adoption use cases in which the new technology is made available to the consumer at no (initial) cost. In this one important respect, at least, internal organizational adoption more closely resembles a B2C use case than a B2B one simply because the technology does not personally “cost” the internal individual user anything financially. This absence of a financial barrier may be an important one and, as noted, it may account for differences between uptake of new technologies by “consumers” inside of law firms and general adoption patterns at the law firm market level. Internal law firm adoption patterns may not repeat (recapitulate) what happens at the broader market level, but it probably rhymes…

The Innovation Adoption Lifecycle Model Revisited

As explained in Part 1, Rogers’ innovation adoption lifecycle model identifies five different adoption groups. The adoption lifecycle proceeds in a consistent way between the five groups and presents itself as a classic bell curve. Moore’s main contribution was to note that there are two minor cracks that impede progression between two sets of the groups and a major “chasm” that stalls progression at a critical stage. The adoption lifecycle graph presented in Part 1 is reposted below, but this time I have correlated each of the stages with the law firm groups that, in my estimation, best fit the model.

Before diving into the specific placements of the groups and how this affects technology adoption in law firms, a few general comments are in order:

• The attributes of a group as defined in Moore’s model will never match every member of a group defined by role/function in a law firm. At best, we would expect that a typical member of the specified law firm group will behave consistently with the corresponding model group. For example, my applied model predicts that a typical or average senior associate will behave consistently with the Early Majority group, but some senior associates will behave like Early Adopters and some will show up in Moore’s Late Majority and a few might even register as Laggards.
• The red line separates groups based on whether they are primarily focused on generating or managing legal content and legal services (above the line) or non-legal support services (below the line). It is a largely arbitrary divider for a number of the groups (KM, PSLs, Research Staff, LPM, and Paralegals) and does not signify a critical distinction in terms of adoption behavior. The specified groups, as labeled, are generalizations and do not represent all possible classes of lawyers and support functions in a typical BigLaw firm.
• The [Owner Function] and [Disrupted Function] are placeholders for the staff or administrative functions most directly involved in purchasing and supporting the new technology (“owner”) and negatively impacted (“disrupted”) by the new technology, if any.

With those qualifications in mind, let’s drill into the groups and positional placement in my applied model:

• Lawyer Distribution. Lawyer seniority and position plays a key role in technology adoption behavior. This should not come as much of a surprise to anyone involved in law firm technology implementations, and the model helps explain why. In general, as lawyers rise in seniority they become more comfortable with (resigned to) the existing technical infrastructure of the firm. Points of authoritative reference shift from external to internal sources. Over time lawyers invest considerable effort in mastering (or at least accommodating) the firm’s technology infrastructure and ossify into habits. This hard won assimilation of technology causes the lawyer’s attitude to shift from a willing openness toward new/unknown technologies as a junior associate to a cautious pragmatism as the associate achieves seniority. Some other factors that align lawyer career stage with the corresponding adoption model stage:
  • Junior Associates. Junior associates, already tech-savvy but inexperienced in substantive legal matters and practice, draw upon internal references for legal guidance but turn to their external experiences and expectations for technology-related behavior (i.e., horizontal referencing is expected of Early Adopters). For juniors discontinuous technology change is an attractive and promising force (the same applies to Early Adopters in Moore’s model).
  • Senior Associates/Attorneys. Diversity and individuality in behavior – prevalent in junior associates and a trait of “visionary” Early Adopters in Moore’s model – is weeded out over time as associates leave the firm. Those remaining become increasingly homogenous and herd-like in their skittishness toward the unknowns of new technology. They wait for others to test the waters but are anxious not to be culled out as stragglers either. This is exactly the kind of behavior that causes the chasm conundrum.
  • Partners and Counsel. This group is fully (in)vested in the firm status quo. Technology change must be safe and simple, requiring little effort and disruption of their busy schedules. As is the case for the Late Majority in the model, partners are strongly motivated by cost and economically provable benefits associated with committing to new technology.
  • Senior Partners. Long term economic or other benefits do not motivate this group. They are rightly skeptical of any benefits likely to accrue to them personally from technology change and fear the effort required to break entrenched habits and to learn new technologies.

• Staff/Administrative Function Distribution.  Some factors likely to influence where a specific staff/admin function falls within the adoption model include:
  • Owner and Disrupted Functions. Most software applications and hardware systems in law firms are purchased by or for the benefit of a staff/admin function. That function effectively “owns” the technology and is responsible for using and supporting it. (Note: many firmwide systems and the networking/hardware infrastructure are owned by the IT function.) A functional team or department “owner” becomes the de facto Innovator with respect to internal adoption of technology it “owns.” For instance, in most firms KM “owns” enterprise search and takes the lead when enterprise search is introduced into the firm. On the back end, new technology sometimes encroaches on, curtails or even eliminates an existing function. Any such “disrupted” function is likely to resist the adoption and behave like Moore’s Laggards.
  • Traditional vs Non-Traditional Functions. Traditional functions that have existed in law firms for a long time (e.g., accounting, records, HR) will generally skew toward the right side of the adoption model. They tend to be the keepers of the firm’s norms and enforcers of the firm’s rules and procedures. Conversely, non-traditional functions with less established roles and expectations will skew toward the left side of the adoption model.
  • Support Relationship to Lawyer Groups. Support functions will generally align with the adoption lifecycle position of the lawyer group they primarily report to and support. For instance, the business development function works most closely with partners. Of necessity, business development must be attuned to the technology adoption attitude and appetite of partners in the firm.

Implications for Crossing the Chasm

Assuming the general validity of my application of Moore’s model to BigLaw firms, we would expect to see lawyer-related technology adoption frequently stall after gaining some success with Early Adopters, usually dominated by junior lawyers, and struggle to penetrate the mainstream majority of lawyers, starting with senior associates. My perception (based on direct personal experience in one firm and anecdotal evidence collected from others) is that enterprise search adoption often encounters this exact problem, and I have seen it proceed in this manner with other technology implementations as well. Let’s consider a few implications of Moore’s “D-Day” beachhead strategy for crossing the chasm and see if they provide useful insight into innovation adoption strategies for law firms:

• Counterproductive Implementation Segmentation. According to Moore, one of the big mistakes innovators make is to push into the mainstream market with the same incomplete product, support level and marketing strategy that succeeded with Early Adopters. Law firms commonly commit a similar error by rolling out new technology by office, practice or even across the entire firm all at once. This almost guarantees that only the receptive Early Adopter subset of targeted users (typically, junior lawyers and some admin/staff functions) will fully adopt the technology. Crossing the law firm chasm calls for staging the rollout differently. After a successful pilot, identify a segment of the firm (practice group, client team, office, whatever) and specifically target and concentrate support to ensure successful adoption by the Early Majority of that one firm segment (typically, senior associates, senior attorneys and associated admin/staff). What is needed to pitch and promote to them, to train them and to deliver an appropriate UI/UX to them should be the primary focus at this stage. Concentrate implementation resources by limiting size of the “beachhead” (i.e., pick a manageable firm subsegment) and deliver the “whole product” to that one subsegment. Establish success before moving on to other segments of the firm.
• The Whole Product and Nothing But the Whole Product. You cannot expect to successfully cross the chasm if you do not have a “whole product” solution. That means a fully supported and well integrated solution that addresses all of the reasonable expectations of the target audience. With enterprise search, for example, the “whole product” means all data sources relevant to the target audience are crawled and included, not just some or most of them. It means the search interface is incorporated into the target audience’s familiar tools. It means results relevancy and displayed metadata is tuned to the target audience’s needs. Anything less will likely send them back into comforts of old habits.
• The 80/20 Success Trap. Early Adopters are satisfied with an 80% solution because they have the technical skills and willingness to provide the other 20% themselves. For example, Early Adopters of enterprise search are comfortable with and even relish the opportunity to construct complex search strategies using the new tool. Early Majority adopters expect something easier than their current search folders and Late Majority adopters expect Google-like simplicity. Do not let Early Adopter enthusiasm and positive feedback mislead you into believing that you can easily replicate their satisfaction across the chasm. Resist the temptation to kick off that (probably already delayed) firmwide rollout too soon!
• Beware of Innovative Partners. Having a partner champion to help you push forward a new technology initiative is a good, and even necessary, thing. But be careful. Partners that are enthusiastic supporters of new technology are – in terms of the model – two standard deviations from the typical partner adoption behavior. Their influences on the direction of the initiative may become a distraction from what is really needed to target the mainstream market of senior associates and partners in your firm.
• Product and Firm Adoption Lifecycle Misalignment. Consider what happens when a law firm tries to push its internal technology product adoption across the chasm before the product vendor has successfully traversed the chasm in the broader product market. Either the law firm’s effort will fail outright because the vendor has not delivered the “whole product” needed to achieve buy-in from pragmatically oriented and gun-shy senior associates on-up or the law firm will have to fill in the missing pieces through internal development and/or external consulting and integration assistance. The former option is costly to the project’s credibility. The latter is just plain costly. Especially for early law firm adopters of enterprise search, some combination of both of these outcomes occurred in mid 2000s. The adverse effects may still be lingering in those firms.
• Vertical Dissonance. A special case to consider is when a staff/admin function that is normally aligned with partners (Late Majority) takes on an innovation lead role because it “owns” the technology being introduced. The cognitive dissonance between what the staff/admin group is “selling” to the partner group and what that group normally requires for technology adoption is bound to be a large and challenging one to begin with. And if the product offering itself is not a mature mainstream-accepted and cost-effective “whole product” solution that Late Majority adopters expect, it is almost certain to flop with this critical partner cohort. This will be true regardless of how smoothly adoption proceeds within the owner department’s internal team and regardless of strong support of “visionary” partners championing the project. (CRM rollouts by business development teams come to mind here.)
• Revenge of the Disrupted Laggards. The introduction of new technology in law firms often disproportionately disrupts one of the groups noted in the adoption lifecycle. The disruption can adversely affect the project even if it does not result in actual job losses. More commonly it appears as a shift in control, dependency, expertise or functional authority. In short, when new technology empowers lawyers as end users (as it often does), it also marginalizes the staff that previously supported the function. Whether it happens consciously or subconsciously, passively or aggressively, the affected staff will almost inevitably adopt the Laggard position. This might well come as a surprise to the Innovator lead team because these “laggards” behave in other contexts like Early Adopters or Early Majority pragmatists. For instance, the introduction of enterprise search can easily turn PSLs, research specialists and library staff into laggards if they see themselves losing control as gatekeepers to the firm’s intellectual resources. The obvious solution here (not always easily achieved) is to make the affected group a co-owner of the new technology. This must be done very early on at the Innovator adoption stage (i.e., vendor selection and proof of concept) and before Early Adopters start singing their praises of the technology, which will otherwise be perceived as a threat by the affected support staff.

Concluding Thoughts

As I hope you have perceived from the foregoing observations, Moore’s technology adoption lifecycle model and the related advice in his book, Crossing the Chasm – Marketing and Selling Disruptive Products to Mainstream Customers, offers a rich framework for analysis of technology adoption in BigLaw firms. Whether or not you agree with my specific application and structuring of the key law firm factors involved, the exercise is a worthwhile one to undertake. It puts a stake in the ground for validating what works and does not work in your own innovation efforts. Take note that Moore’s books cover a lot more stimulating ground than what I have emphasized here. Check them out, starting with Crossing the Chasm.

If nothing else, the 2017 edition of Altman Weil’s Law Firms in Transition Flash Survey confirms that law firm innovation continues to merit prime coverage and legal management mindshare. While the survey finds that over 50% of the surveyed law firms are “actively engaged in creating special projects/experiments to test innovative ideas or methods,” that actually represents a slight downward tick from the 2016 survey response. Undaunted by the non-increase in activity, AW’s 2017 survey analysis highlights the innovation findings, making room in the results to do so by dropping its analysis of all other previously covered “strategic groundwork” topics. Greater mindshare is a good thing, I suppose, but until we start talking about how to establish and spread real innovation and not just “special projects/experiments,” the discussion will continue to perpetuate low expectations and fixate on missed opportunities and structural impediments. What is missing is a good conceptual framework and shared vocabulary for analyzing innovation adoption in the legal domain, but that is starting to change. In particular, Bill Henderson’s LegalEvolution.org  looks like a promising platform for exploration of the complex dynamics of innovative legal operations, practices and technologies based on innovation adoption theory. By way of supporting that effort, in this blog post I provide a brief summary of the best known innovation adoption lifecycle model and describe a well-established strategy for overcoming a critical structural obstacle to innovation. To illustrate and test the model I discuss how enterprise search technology established itself in BigLaw over the course of the past 15 years. In my next post I will show how the theory can offer useful guidance for successfully innovating inside of BigLaw firms.

The BigLaw Enterprise Search Story

Back in the early 2000s large law firms were beginning to experience a proliferation of content search challenges:

• Document management libraries were growing in size and dispersal across firm offices. Especially in international firms, WAN-based global searching of all document libraries was cumbersome, slow or otherwise impractical. Users tended to settle for limiting search scope to local libraries.
• Collaboration and content management tools like Microsoft SharePoint and Lotus Notes were being deployed in law firms and beginning to accumulate valuable content. However, these tools lacked sophisticated search functionality and provided no practical way to search all relevant content repositories.
• Personal and shared email+attachment archives were simultaneously becoming a management problem and a rich source of content. Again, search functionality was limited.
• Law firms were beginning to systematically collect valuable firm data in relational databases, including useful information about clients, matters and timekeepers. This mostly isolated data had unrealized potential to directly answer end-user queries and to facilitate searches of all the other content noted above.

When enterprise search vendors like Recommind, Verity and Autonomy started knocking on the legal market’s door shortly after the turn of the century, they found a few innovation geeks and “visionaries” (like me and several other law firm KM leaders) who were willing to “experiment” and then deploy a universal/unified search solution. Those of us who were early adopters of enterprise search encountered extensive problems related to user interface and system performance and significant limitations in connecting to and ingesting source data. In turn, this made the task of “selling” the solution to our internal users that much harder. Consequently, the initial results were mixed at best for early adopters. We were effectively forced to double-down on our innovation investment by cycling through challenging upgrades (recrawling millions of items and handholding users through multiple UI/UX changes). In short, early adopters of enterprise search technology led the battle to slay the BigLaw content monster but paid a heavy price for the privilege.

Meanwhile, later adopters experienced fewer implementation stumbles and benefitted from enhanced features and functionality developed from early adopter feedback, but they also paid a heavy price for their delaying strategy in terms of ever-growing user frustrations and inefficiencies associated with unbounded content growth and siloing. Even today, though, some BigLaw holdouts still refuse to implement enterprise search. How is it possible that there is a such a wide adoption spectrum within a relatively homogeneous market?

Rogers’ Innovation Adoption Model

The basic innovation adoption model originally described by Everett Rogers is well established and a good way to frame the issue. No doubt, you have come across it before:

The table below describes the attributes of the five stages of the model (left column) as it has been applied generally to technology use cases and instantiates them (right column) to the adoption of enterprise search in BigLaw firms with a focus on the leading legal enterprise search vendor (Recommind).

The model nicely fits the history of enterprise search in the BigLaw market and explains how widely differing behaviors and adoption attitudes can exist in the same market.

Look Before You Leap

OK, so now we have a model that works in the legal market, but we need to consider an important finding made by Geoffrey Moore and described in his groundbreaking book, Crossing the Chasm – Marketing and Selling High-Tech Products to Mainstream Customers. Moore observed that the transition between innovators and early adopters (visionaries) and between early majority (pragmatists) and late majority (conservatives) posed minor marketing challenges (“cracks”), but the transition between visionaries and pragmatists was a much bigger and far more perilous discontinuity. He called it a “chasm” to emphasize the dramatic impact it has on adoption progress beyond the first two stages.  We need to adjust the graph:

Successful transition of the first crack (innovators → early adopters) requires that the technology be strategic and not just cool. Successful transition of the second crack (early majority→ late majority) requires that the technology be user-friendly and simple to adopt and not just productivity-enhancing. These are both problems within the power of the technology vendor to internally solve. Successful transit between early adopters and early majority would also be a vendor-controllable crack if it only required a refocus on productivity, stability and compatibility of the product. However, a far bigger challenge at this point in the adoption lifecycle is the marketing one caused by pragmatists’ distrust of visionary testimonials and references. Pragmatists look to market leadership and positive references from their market peers. Accordingly, new technology vendors looking to enter the market are stymied by a high reputational barrier that does not come down simply because the new technology is a better mousetrap.

It is a classic Catch-22 for technology vendors looking to grow beyond their early installed base. They typically (and wrongly) respond to the encountered resistance by expanding the markets “served” in search of new sales and by trying to incorporate too many early adopter development/support requests. The resulting 80% solution for all and a 100% whole product solution for none is exactly what scares pragmatists away. Again, Recommind serves as case study for this behavior. While Recommind eventually crossed the chasm by concentrating exclusively on the legal market segment, it was hampered for a number of years by its failure to build out a robust, bulletproof backend with a full suite of administration tools and templates for quick implementation. Pragmatic IT managers were frightened by the daunting effort required to get the system up and running even while visionaries were applauding Recommind’s front-end features like Matters & Expertise.

Moore’s rules for crossing the chasm requires the technology vendor to concentrate all of its efforts on creating a D-Day like beachhead:

• Target a specific market segment as your point of attack. Make yourself the big fish in a small pond.
• Assemble the invasion force by creating a whole product (includes all system requirements, integration, installation, training and support). Match the product/solution to the market/problem you have targeted. Utilize “allies” (other vendors with compatible products and platforms, integrators and professional support services) to appear bigger and more complete.
• If your technology is a platform make it look like an application (e.g., hook up a search engine to user-facing systems like SharePoint or other intranet solutions). When you are attacking the early majority/pragmatist stage, application end-users (e.g., KM managers and practice support personnel) are easier to convert into sponsors than are IT managers.
• Define the (marketing/selling) battle with a highly focused message (the elevator pitch) that not only explains the specific market segment problem you solve but also differentiates your solution from who you (realistically) define as the competition.
• Launch the invasion with skilled direct sales supported by technical staff capable of working with targeted prospects to identify their needs. Propose solutions that work well for the target’s specific business problem.

Yes, it comes down to discipline and focus, which seems like the obvious thing to do, but technology companies fall into the chasm and never dig out with surprising frequency. Consider, for instance, the numerous standalone enterprise search vendors who have flirted with selling into the legal market over the years. Excluding the recent entrants like Ravn and Sinequa all of the previous players have abandoned the market, save for two. Autonomy only “succeeded” by being absorbed into an established legal market platform. The other exception, Recommind, succeeded in becoming the preeminent legal enterprise search solution precisely because it focused exclusively on the legal market during its chasm-crossing phase of existence. Ironically, its loss of momentum and decline can be directly traced to its shift of focus into other markets and other offerings.

Again, this technology-specific version of the model and associated adoption strategy appear to hold up nicely. Next up, a look at how this conceptual framework can assist us innovators and visionaries to time our innovation adoption efforts and successfully execute them in the BigLaw environment.

Deal Structuring and Advising

Law firm partners get paid the big bucks for structuring transactions that maximize desirable outcomes for their clients while minimizing risks. The more unique the situation, the more important the legal structuring and advice, but even commoditized transactions can be traced back to predecessors that were novel at the time and required some amount of lawyering. New modes of human social interaction, new markets and new laws/regulations trigger at least a temporary flurry of lawyering of the structuring and advisory variety and the same will be true with respect to emerging blockchain-based technologies. Beyond the first-mover benefits, however, long-term expectations regarding blockchain transaction structuring and advising need to be tempered. Disintermediation, process automation and elimination of escrows, agents and back office functions are common themes in almost all blockchain initiatives. Crypto-pragmatists might be doing it to increase efficiency, and crypto-purists might be doing it to reduce dependence on centralized authorities, but either way, the result is likely to be lots of commoditized, highly-templatized blockchain transactions and relatively few uniquely coded ones.

The efficiency advantages of commoditized business processes conducted on blockchains like those described in the World Economic Forum report are what excite the banks and other crypto-pragmatists. Remove the economic benefits of standardization and volume, however, and even the lowest cost and most lawyer friendly crypto-pragmatist blockchain is hard to justify as a preferred platform over traditional off-chain means of structuring, executing and recording legal transactions. It follows that low-volume, one-off asset sales, financings, M&A and other complex deals that require the most intensive legal expertise at the structuring stage are the least likely transaction types to show up on crypto-pragmatic blockchain platforms. In sum, there will likely be an inverse relationship between the usefulness/benefit of crypto-pragmatic blockchains and the complexity/uniqueness of of the real world assets, obligations and parties involved. As a corollary, legal structuring work will spike as new transaction types are brought on-chain but will quickly flatten once automated/templatized smart contracts are successfully launched. 

As for crypto-purist initiatives, the same efficiency factors affecting legal transactions on crypto-pragmatic platforms will, likewise, apply to smart contracts conducted on crypto-purist platforms. Furthermore, crypto-purist projects (like TheDAO) gain additional efficiencies from bypassing most, if not all, legal costs and overhead associated with the creation, acquisition and management of real space entities and assets. This additional efficiency opens up all sorts of possibilities for totally new types of transactions feasible only on crypto-pure platforms but also severely limits the usefulness for transactions that require financial covenants or other legal prose not expressible as computer code, identification of the parties involved or off-chain performance or transfer of assets. In sum, there will likely be an inverse relationship between the types of transactions that work well on crypto-purist platforms and the types of transactions that benefit from or require traditional forms of legal structuring and advice.

Due Diligence

In big deals a substantial amount of (primarily associate and paralegal) time is spent conducting corporate colonoscopies – a/k/a due diligence reviews – of corporate actions, leases, material contracts, patents and trademarks, executive compensation, labor, environmental and litigation issues, tax matters, etc. Professionalized review of public and private transactional records, contracts, filings, etc. is typically undertaken to confirm the value of an entity or assets being acquired or the capacity of a contractual party to perform its obligations under the contract. Today, information concerning the assets and liabilities of even “public” companies is obscured, widely dispersed and often untrustworthy. But imagine a future in which a target company’s internal financial and transactional history (including all substantive contracts with third parties) is readily accessible online to permissioned legal counsel and financial auditors, fully traceable back to their sources, immutable and completely trustworthy. Also imagine a future in which the current status and filing history of the target company with all relevant governmental institutions is available online with cryptographic certitude. That’s the promise of a world based on blockchains, and in such a world the need for traditional lawyer-based diligence reviews and “comfort” for prospective transactions largely goes away. Terms like “due diligence,” “title search” and “audit” become quaint artifacts of the papered past.

Of course, the gulf between today’s reality and this grand vision of all business and governmental activity conducted on-chain is a huge one. Government bureaucracies are slow to adopt new technologies and standards, and many corporate transactions and business operational processes will remain off-chain indefinitely. Legacy records and many recordkeeping processes are still paper-based and still dependent on human review and approval and will continue to exist in analog mode or antiquated digital mode for a long time. Even in a best case scenario for the acceptance and growth of blockchain usage for all types of formal business messaging and data management, we will be living in a rolling state of disruption as the world transitions over time from conducting business largely off-chain to largely on-chain.

The good news here for lawyer pocketbooks is that disruptive conditions almost always add complexity and uncertainty during the transition, and complexity usually means more time and specialization and higher legal fees. In the interim, the demand for transactional due diligence will live on. Just bear in mind that, if the true believers are correct about all of the long-term possibilities for blockchain-based business transactions, governmental filings, registrations, bookkeeping, etc., then there will be an inevitable corresponding decline in the need for traditional legal due diligence activities. [Note: Some commentaries have described smart contract beta testing by lawyers as an important new form of “due diligence.” Due diligence, as I’m referring to the term here, relates to validation of content related to or provided by the client, whereas checking the contract code generated by the law firm itself is an internal drafting/review exercise as discussed in the next section.]

Drafting and Review

Many years ago (more than I’d care to specify) “document assembly” was widely touted as the first legal technology killer app. The evangelists of the era predicted that it would revolutionize the practice of law, and I was one of the eager acolytes who jumped on board. I even developed my own document assembly system based on the WordPerfect scripting language and offered it to the world as an open source application. My Lawgical Document System was free, functional and easy to learn even for lawyers with no programming skills, but it languished unused like so many other similar document assembly tools over the years. The reason? Lawyers love precedent and hate forms and checklists. Consider it axiomatic that if an experienced lawyer is given the choice to use prior work product that is “close enough” or a Q&A-based automated template system that cranks out a near-perfect first draft, the prior work product option will invariably get the nod. This seemingly irrational, inefficient and risky behavior is deeply ingrained and difficult to overcome even in today’s increasingly cost-conscious and tech-savvy legal environment. Despite the fact that powerful document automation technology has been around for over thirty years and is inexpensive and proven, it has had a relatively minor overall impact on how law is practiced. Bear this in mind as we look at how making contracts “smart” completely changes the traditional drafting and review workflow.

Drafting. Legally well-formed smart contracts will consist of computer code and prose. What’s clear is that the computer code must be highly formalized and well structured. What’s not clear is how the associated legal prose will be generated and whether the drafting cycle will proceed along typical computer programming lines (waterfall, agile, etc.) along typical legal drafting lines (prior work product editing, drafting from templates, etc.) or some hybrid. Regardless of the particulars, it’s difficult to imagine the process not being strongly influenced by what works best for generating the computer code. Drafting based on the CommonAccord framework, for instance, is highly structured and borrows heavily from open source computer coding practices, and it looks like creating smart contracts in the R3 Corda environment will be template driven.

Review. Because well-formed smart contracts must be verbose enough to be read and understood by lawyers and formalized enough to be read and understood by machines, final review of a smart contract before it goes on-chain should determine that:

• The legal prose accurately summarizes in human readable form all material inputs and outputs of the computer code,
• The computer code will properly execute on-chain as specified (and only as specified) in the legal prose,
• Legal prose for any contractual terms to be applied off-chain is correct and complete.

Even assisted by testing tools, the final review will likely require some combination of legal and programming skills and experience. Whether the final review and sign-off is performed by one (extraordinary) individual with combined skills or a coordinated group effort of lawyers and programmers, the ultimate financial risk still falls on the law firm’s partner(s) who are likely to be the least code-savvy and the least comfortable with promoting the use of smart contracts in novel ways or for complex transactions that require customized coding.

Template Development and Support. If, as appears likely, much of smart contract drafting will become template-driven, then the task of template development and support becomes a critical lawyer/programmer undertaking. As most of us in the legal KM biz understand, getting lawyers to develop and maintain simple text-only forms is really tough and getting them to engage in the development and support of document automation applications is even harder. This is true despite progress made by vendors in simplifying template authoring. Technology is the least of the issues. Obtaining partner consensus and approval of preferred text and usage and juggling all of the legal, terminological and stylistic differences in multiple jurisdictions and practices is extraordinarily difficult. The real killer, though, is maintenance: sustaining user interest and feedback, continually identifying and correcting technical errors and updating to reflect changing laws and practice norms. It never ends, and these very same challenges will also apply to smart contract template development and maintenance. Looking to communal models (e.g., CommonAccord’s proposed use of Github to manage smart contract code/prose as open source content) is an intriguing idea and commercial solutions may also emerge, but both of these support options are generally counter to the proprietary approach that law firms have followed since the dawn of time. Dependence on generic “open source” or purchased legal code/prose also raises problematic professional, ethical, business and liability questions that may limit their attractiveness to many lawyers.

Entity Formation and Authorization

Lawyers are often called on to set up new corporate entities and arrange corporate authorizations. While the relevance and volume of these lawyering tasks is not likely to change much with crypto-pragmatic smart contracts, crypto-purist smart contracts are a different matter. That’s because non-pseudonymous contractual parties can be subjected to regulatory control by real space authorities, and counterparties can seek legal recourse against them as well. A lot of “purist” energy and effort is expended to protect digital pseudonymity through cryptographic and other computer coding tricks. However, lots of transactions require interaction with identifiable real space entities, in which case some form of real space pseudonymity may be a necessary evil for a crypto purist transaction. In these instances lawyers might be called upon to create real space pseudonymity by forming corporate entities or setting up agency arrangements that buffer the ultimate party from identification to counterparties or state authorities. The propriety and effectiveness of taking such steps will vary from deal to deal and will depend on the willingness of some jurisdictions to sanction such efforts (e.g., some Swiss cantons apparently already have options for crypto-friendly entity formation).

Regulatory Compliance and Associated Filings/Approvals

“Regulatory compliance” implies that we are operating in a real space sovereignty and pragmatically accepting its authority over transactional activity in cyberspace. It should come as no surprise, then, that we are already seeing considerable efforts by various cyber-pragmatic initiatives (e.g., R3, tO, Chain and Digital Asset Holdings) to embrace and promote efficient regulatory oversight as a key feature of their respective platforms. Crypto-purists, on the other hand, tend to seperate blockchain design, structure and operation (viewed as strictly “alegal” and beyond regulation) from the transactions and users of the blockchain (permitting but not necessarily requiring pseudonymity). The crypto-pragmatic approach is integrative, holistic and accommodating to regulatory authorities; the crypto-purist approach is segregated, ad hoc and distrustful of regulatory authorities. Expect lawyers to be actively engaged in the growing number of crypto-pragmatic fintech initiatives on private blockchains aimed at making financial transactions more cost-effective for the parties involved and more compliant with regulatory oversight. The prospects for non-coercive regulated transactional services on public blockchains is less certain, but I would expect that those efforts that succeed will be embraced by lawyers and their clients pursuing the potential efficiency benefits of doing business on-chain.

Opinion Giving

If processes associated with due diligence reviews, entity formation/authorization, contract execution and regulatory compliance change as a result of business transactions going on-chain, then the supporting facts, levels of reliance and qualifications on which legal opinions are given at deal closings will surely shift as well. More interesting is the question of whether the legal substance of the opinions will also have to change, especially with respect to enforceability of the terms of a smart contract that may have no explicit legal prose at all or that contains overt or unforeseeable conflicts between the terms described in embedded legal prose and the actual smart contract code that executes on the blockchain. I am certainly not qualified to speculate in detail on how opinion-giving will need to change as smart contracts become a significant reality, but it seems likely that the challenges of evolving this incredibly cautious and standards-bound element of transactional law practice will be significant and perhaps a major drag that holds back deals that normally require opinions (and normally generate lots of legal fees).

Documenting, Closing and Recording

Documenting terms, collecting signatures and organizing, distributing and filing the essential and ancillary materials of a transaction in a permanent form is central to the function of lawyers. These are the essential contract form and formation activities that are missing from Szabo’s original conceptualization of smart contracts (as I explained in Part 1). Let’s briefly look at how these non-smart elements could be managed on-chain:

Documentation. In a smart contract that lacks explicit legal prose, all terms are either inferred by decompiling the explicit computer code into human/legal readable form or from application of legal concepts (common law, UCC, etc.). In that respect, a proseless smart contract possesses many of the same qualities and limitations of a traditional oral contract. Integrating explicit legal prose with smart contract code addresses the following critical needs:

• Source Code/Annotations. Control of unintended and unforeseen outputs due to computer coding errors and inadequacies,
• Functions. Access to useful contract functions (e.g., financial covenants, reps & warranties, choice of law, remedies) that are impractical or impossible to model in deterministic computer code,
• Values. Incorporation by reference (e.g., schedules and exhibits) of factual states and conditions that exist off-chain and are not otherwise accessible on-chain through trusted oracles.

Closing. Traditional forms of contract acceptance by means of manual signing of paper documentation is dying out and being replaced by end-to-end digital creation and execution of contracts. Digital signature solutions that lock the documents and establish provable acknowledgement by the signing party are already commonplace. What is lacking (and what blockchains enable) is permanent access to the documentation in provably unchanged form. Logistically speaking, the possibility of coordinating and conducting transactional closings completely online saves time and costs for the law firms and clients involved.

Recording. Some blockchain platforms, like Bitcoin, have extremely limited text storage capabilities, but options will become increasingly available for utilizing blockchains and related peer-to-peer content storage for immutably preserving contractual documentation, metadata and supplemental content. The contracts themselves can be either “smart” or “dumb” traditional text files and either private or publicly visible. This means that regardless of how your contractual transaction is documented and closed and regardless of how much of the transaction is performed on-chain or off, blockchain technology can become the solution for electronically binding the transaction with cryptographic certainty that’s as immutable and permanent as the blockchain platform itself. The utility of this blockchain binding for all types of transactions is compelling. I expect that law firms will play a central role in promoting and supporting this elegant solution.

Are We There Yet?

Yes, finally! It’s been a long journey (and if you’ve stuck with me the whole way, I’m duly impressed). We’ve discovered that what makes smart contracts “smart” also makes them incomplete as contracts. We’ve seen that this shortcoming of smart contracts can lead to chaos as it did with TheDAO. We’ve learned that addressing the legal deficiencies of smart contracts compromises their usefulness for some applications. And we’ve explored how transactional lawyering itself must change to accommodate the unique challenges and opportunities presented by smart contracts and blockchains.

I’ll leave you with one final thought: the emergence of the internet over the past twenty years changed so much…and yet, so little…about the practice of law. Over the next twenty years I expect smart contracts and blockchains to have the same impact!

The $60 Million Bug That Was Also a Feature

Our story begins with the launch of “The DAO” (TheDAO),  an ambitious project to create the first large-scale distributed autonomous organization on the Ethereum smart contract blockchain. TheDAO was intended to automate crowdfunding of submitted project proposals from a collected pool of “Ether” (the Ethereum cryptocurrency that is exchangable with Bitcoins, US Dollars or other fiat currencies).  All governance and funding decisions were based on proportional participant voting without further human intervention (except for one special case not relevant here). As explained in TheDAO wiki:

[TheDAO] is represented by smart contracts on the Ethereum Blockchain. It contains functions which, as a whole, have analogies to a crowdfunding vehicle governed by participants’ votes, to seek out and fund proposals. Because [TheDAO] consists of computer code, it interacts with the physical world through Contractors. The creators of these proposals act similar to a contractor, with [TheDAO] as its client. [TheDAO] therefore does not “invest” in these proposals, because it does not acquire equity in the contractors. Instead, in return for receiving a funding by [TheDAO], contractors deliver services, infrastructures or products yielding a return to [TheDAO].

TheDAO was wildly successful in raising funds. In the single month of May, over 10,000 participants contributed Ether equal to over $160 million USD, and project funding proposals started rolling in. While some experts raised alarms about the code itself, questioned the validity of TheDAO as a legal entity, worried that the launch represented the sale of unregistered securities or imposed general partner liability for TheDAO participants, others praised the project and called it a revolutionary leap forward. It didn’t take long for disaster to strike…

In mid June, one of TheDAO participants exploited a vulnerability built into a particular withdrawal function in TheDAO’s smart contract and seized control of approximately one third of its Ether-based assets (worth about $60 million USD). Restrictions coded into the smart contract locked up the drained Ether for a specified period of time (about a month) and prevented a completely irreversible and potentially untraceable withdrawal by the participant/attacker during the lock-up period. Likewise, other coded restrictions prevented other “white hat” participants from fully retrieving the Ether as well. Stalemate? Not quite. Influential members of the Ethereum community initially proposed a solution known as a “soft fork” that requested all of those involved in operating (a/k/a “mining”) the peer-to-peer network of servers that constitute the Ethereum blockchain to, in effect, ignore the problematic transaction and treat all subsequent transactions on the blockchain as if it never happened. This rewriting-of-history proposal was withdrawn after further testing revealed that the soft fork was vulnerable to hacks. In it’s place a “hard fork” solution was proposed that required participating miners to change the software they used to maintain the blockchain.

Approximately 85% of the Ethereum miners adopted the hard fork, but because the remaining miners pledged to continue with the old code, Ethereum split into parallel crypto universes, identical in most respects with identical account balances and account holders of Ether (designated as ETH in one and ETC in the other) with one critical difference: the hard-forked Ethereum universe essentially treated TheDAO’s smart contract as rescindable by all participants due to mutual mistake, and the non-forked Ethereum universe continued to treat the attack as a valid transaction within the terms of TheDAO’s smart contract. In the former instance, TheDAO participants were placed in a position to recover the Ether (ETH) they owned just prior to the June attack. In the latter instance, the attacker continued to control a large amount of Ether (ETC) at the expense of the rest of TheDAO participants.

Having trouble following this? Here’s an analogy that might make more sense to lawyers: A soft drink company is reorganized into two separate entities in an effort to fend off a hostile and (some would argue) illegal takeover by an insurgent shareholder. Both of the successor companies get rights to the magic soft drink formula, but one receives 85% of the bottling facilities and distribution capacity and the other receives the remaining 15%. Through some questionable changes in the original company’s bylaws proposed by the company’s lawyers and adopted by the board of directors, the original shareholders are issued stock in the larger successor in proportion to their ownership prior to the attempted hostile takeover and issued stock in the smaller successor in proportion to ownership of-record as of the reorganization date. These changes leave the insurgent shareholder with a tiny stake in the larger successor and a big stake in the smaller successor. When shares in the new companies start trading on exchanges, the price of shares in the larger successor is bolstered by the extra assets and perception of market domination but tempered somewhat by residual concerns surrounding the dubious corporate governance manipulations. The opposite applies to the value of shares in the smaller successor. Thus, depending on whether you are a shareholding executive of the original company, the insurgent shareholder, an institutional shareholder, a speculative trader or just an individual with a few shares, you might be relieved, indifferent or outraged and considering legal action.

In the physical world as governed by the sovereignty of laws, regulations and courts (hereinafter, “real space”), the process for determining the validity of the corporate actions taken to repel a hostile takeover like the dubious one described above is well understood. Likewise, the advisory and advocacy roles of lawyers in that process is well established and critical. Lawyers are the tour guides through the sovereign institutions in which real space contracts are formed, executed, performed and adjudicated when disputes arise. All well and good, but what about the virtual world of “cyberspace” in which things like DAOs and smart contracts exist? When smart contracts go awry as happened with TheDAO, isn’t there an important role for lawyers to play in resolving the issues? Isn’t there also an important role for lawyers to play in preventing those problems from arising in the first place? Not surprisingly, an increasing number of lawyers have stepped forward to answer in the affirmative. See, for instance, here.

The affirmative answer that lawyers (and not just programmers) need to be involved in smart contract preparation makes sense and works well only when talking about one kind of blockchain-based decentralized cyberspace (the kind that banks are playing with). It does not work so well when applied to the kind of cyberspace that many envision Ethereum to be. This is important! Structural differences between permissioned/consortium blockchains like the ones favored by banks vs. permissionless/public platforms like Bitcoin and Ethereum reflect two dramatically different visions (“ideologies” even) at play here. The meaning and function of smart contracts and the role of lawyers with respect to them will vary dramatically depending on which vision is applied. The remainder of this post outlines these competing visions and sets the stage for further discussion in my next post on the implications for lawyering in the brave new cyberspace(s) of blockchains.

Code is [Not] Law 

As noted in my prior post, Nick Szabo showed how [computer] code is contract (albeit only partially so as I explained). Lawrence Lessig in his book Code is credited with showing how [computer] code is law:

In real space, we recognize how laws regulate – through constitutions, statutes, and other legal codes. In cyberspace we must understand how a different “code” regulates – how the software and hardware (i.e., the “code” of cyberspace) that make cyberspace what it is also regulate cyberspace as it is. As William Mitchell puts it, this code is cyberspace’s “law.” “Lex Informatica,” as Joel Reidenberg first put it, or  better, “code is law.” L. Lessig, Code 2.0, at 5.

Taken together, these two powerful concepts define how privately created transactions like smart contracts become their own private sovereignty in cyberspace, but also one that Lessig insisted should not be immune to public constraints of laws, economics and social norms:

[Contract rights and obligations in cyberspace] are not conditioned by the public values that contract law embraces. Its obligations instead flow automatically from the structures imposed in the code. These structures serve the private ends of the code writer; they are a private version of contract law. But as the Legal Realists spent a generation teaching, and as we seem so keen to forget: contract law is public law. “Private public law” is oxymoronic…To the extent that these code structures displace values of public law, public law has a reason to intervene to restore these public values.  L. Lessig, The Law of the Horse: What Cyberlaw Might Teach, at 530.

Thus, for Lessig the term “code is law” acknowledges the deterministic nature of smart contract performance/execution, but not its finality. This “weak” version of the term “code is law” permits a communal (“public law”) override of explicit but “buggy” code like the withdrawal function in TheDAO smart contract. It follows that the equitable recission solution generated by the hard fork adopted by 85% of the Ethereum miners was the right course of action and consistent with what Lessig meant by “code is law.”

However, when Lessig wrote Code, cyberspace was not so isolated from real space and much of his attention was focused on the interplay between the two spaces and the continuing power of state authorities over cyberspace. Things have changed considerably in the “architecture” of cyberspace since Lessig first wrote about it at the turn of the century. In effect, cyberspace has become more anarchic and resistant to the reach of sovereign authorities. The emergence of decentralization, censorship resistance and trustless interaction on Bitcoin and other public blockchain platforms like Ethereum has resulted in a reinterpretation of “code is law” by many blockchain enthusiasts:

For the first time in history, citizens can now reach consensus and coordination at global level through cryptographically verified peer-to-peer procedures, without the intermediation of a third party. The blockchain technology ushers in a new era of decentralization on large-scale, in which human factor is minimized and trust shifts from the human agents of a central organization to an open source code. In such distributed architecture, “code is law”: the protocol is open-source and it can be reviewed by anyone; the network is not owned nor controlled by any single entity; data are simultaneously kept by all nodes, thus ensuring proper redundancy. Neutrality of the code, distributed consensus and auditability of transactions can significantly reduce or overcome frictions and failures inherent in decision-making process of centralized organizations (e.g. lack of transparency, corruption, coercion, etc.). Many new decentralized governance models and services can therefore be implemented and experienced through the blockchain, without the oversight of governments. From Blockchain. Blueprint For a New Economy, by Melanie Swan, as quoted in M. Atzori, Blockchain Technology and Decentralized Governance: Is the State Still Necessary?, at 7 [emphasis added].

In other words, the resiliency of peer-to-peer networks, the normative power of game theory and the cloak of pseudonymity, all wrapped in high levels of cryptographic certainty, make it possible to sever most (if not all) of the lingering regulating power of real space authorities over cyberspace participants. The Lex Informatica of Lessig’s cyberspace era gives way to the alegality or Lex Cryptographia of the blockchain era:

The advent of Lex Cryptographia may force us to reevaluate the interaction between these regulatory levers  [laws, norms, economics and architecture]. One of the key consequences of the blockchain could be a rapid expansion of what Lawrence Lessig referred to as “architecture”—the code, hardware, and structures that constrain how we behave—or at a minimum a redefinition of how laws and regulations are designed, implemented, and enforced. A. Wright & P. De Filippi, Decentralized Blockchain Technology and the Rise of Lex Cryptographia at 50.

To the true believers of public blockchain technology, the ascendancy of this new cyberspace “architecture” means that “code is law” can now be read quite literally and with finality. They see DAOs and other smart contracts transacted on public blockchains as self-defining, self-regulating and immune from ordinary legal processes.  It follows that a strict “code is law” reading of TheDAO’s smart contract permitted the so-called attacker to utilize the withdrawal “feature” to drain assets contributed by other participants. To these true believers, the Ethereum miners who stayed the course of the original blockchain protocol were righteous defenders of the sovereignty and integrity of the Ethereum cyberspace. As for the other participants in TheDAO…well, any losses they suffered were caused by their own inadequate reading/testing of the smart contract and failure to heed the warnings of those who predicted problems. That is what “code is law” now means to this audience. Ironically, the term has drifted so far from Lessig’s original meaning that “code is NOT law” is becoming the rallying cry for those who argue along the same lines advanced by Lessig when he originally wrote that “code is law.”

The Schism

As I see it, these diametrically opposed interpretations of “code is law” reflect the deep schism that exists between two blockchain technology camps: the “crypto-purists” and the “crypto-pragmatists,” as I’ll label them. Both camps are simply talking past each other due to their conflicting assumptions about the purpose and core architecture of blockchain-enabled cyberspace and the function of smart contracts within them.

The Crypto-Purists. Let’s start with the strict interpreters of “code is law” (e.g., the Ethereum “classic” proponents who opposed any extraordinary efforts to rescue TheDAO). For these crypto-purists (or “crypto anarchists” as some refer to them), the perfect cyberspace is characterized by total independence from all state-based authorities and their coercive regulatory activity. Crypto-purists seek to achieve a complete break by means of decentralization of governance based on trustless, self-interested behavior among participants in the space. Maximizing pseudonymity of participants (including miners) minimizes the risk of interference by state authorities and manipulations by other participants. The public (permissionless) blockchains like Bitcoin and Ethereum come closest to achieving this ideal, but none of them fully realize the ideal (yet) for various technical and practical reasons. Crypto-purists tend to distrust and avoid real space authorities and regulation even when they might be helpful (e.g., formation/registration of TheDAO as a legal entity). Likewise, crypto-purist norms are spawned from what works best under ideal conditions of a fully decentralized and alegal cyberspace. In this mode of thinking, real space legal conventions of “intent,” “fairness,” “reasonableness,” “equity,” etc. have no long-term usefulness and are tolerated, if at all, only as a temporary crutch until the architecture of the space is fully implemented. Use of such terms to rationalize fixes like TheDAO hard fork is not countenanced.

The Crypto-Pragmatists. This “code is NOT law” contingent is driven by pragmatic considerations of how to utilize blockchain technologies to address real space inefficiencies. Crypto-pragmatists embrace – or at least accept – laws and regulations as necessary conditions or benefits of working within real space sovereignties. With that in mind, confirmable identity of blockchain participants and transparent access by state authorities to immutable on-chain transactions are viewed as conditions for protection against collusion, fraud, hacks and other destructive/anti-social behavior that can never be fully solvable by (computer) code alone. Crypto-pragmatists generally prefer permissioned/consortium blockchain platforms, partly because they circumvent some of the algorithmic inefficiencies associated with public/permissionless blockchains like Bitcoin and Ethereum, and partly because they do not scare away real space institutions like banks. For crpyto-pragmatists, computer code is parol evidence, not law, because smart contract transactions are ultimately subject to judicial/arbitral review governed by applicable legal prose and real space laws. Thus, pairing human readable legal prose with smart contracts is critical for fully forming a real contract that captures intent, establishes mutual assent and provides direction for resolving disputes. From the crypto-pragmatist perspective, TheDAO was fatally deficient from the get-go because it was not a fully formed and enforceable contract and its pseudonymous structuring invited attacks. These deficiencies led to disaster and forced the Ethereum community to take drastic, confidence-shaking measures in pursuit of an equitable on-chain solution in lieu of more appropriate options for enforcement of remedies (or even criminal sanctions) off-chain.

Lawyers to the Rescue?

As already noted, no lawyers (as far as I can ascertain) were involved in the planning and coding of TheDAO. The sole legal step taken was to set up of a Swiss SARL company (DAO.Link) as a real space intermediary between TheDAO and contractors. TheDAO project raised a very large amount of capital and initiated operations with virtually no lawyer fees, accountant fees, regulatory filing fees, taxes, administrative overhead, and no associated time delays. From the crypto-purist perspective, the actions of TheDAO organizers to skip virtually all traditional lawyering and related activities was perfectly rational (and extraordinarily efficient). The problem was inadequate computer coding, not inadequate lawyering. From the crypto-pragmatist perspective, traditional lawyering might have avoided the disaster by incorporating legal prose (to establish the legal intent of the withdrawal function) and basic KYC/accreditation procedures (to identify the participants, including the eventual attacker). It might have…but it also might have made the project financially unviable, unmarketable and untimely.

As TheDAO story nicely illustrates, the relevance and value of lawyers to the production of smart contracts and the support of blockchain technology is far from obvious. It will depend, of course, on the overall progress and adoption of blockchain technology but also on the relative success of projects based on the two competing approaches. Grand pronouncements and sweeping predictions that fail to account for the differences are suspect. Proceed with caution! (But proceed anyway to my next post on how smart contracts will affect different aspects of transactional lawyering.)

In the Beginning There Was the Vending Machine

Let’s step back and get our bearings. Credit for the term “smart contract” is usually attributed to computer scientist, Nick Szabo, who first used the term in his 1994 article, Formalizing and Securing Relationships on Public Networks. As described by Szabo, smart contracts are a way of automating traditional (common law) contract concepts and applying them to transactions that occur primarily or exclusively in the digital domain (ideally with no manual human intervention). Arguably, his chief insight and contribution was the outline of a formalized, potentially machine-readable language for writing and executing these so-called smart contracts. See here. Szabo used the simple vending machine as an example of how contracts can be reified in the real world and then further abstracted to the digital world:

The basic idea behind smart contracts is that many kinds of contractual clauses (such as collateral, bonding, delineation of property rights, etc.) can be embedded in the hardware and software we deal with, in such a way as to make breach of contract expensive (if desired, sometimes prohibitively so) for the breacher. A canonical real-life example, which we might consider to be the primitive ancestor of smart contracts, is the humble vending machine. Within a limited amount of potential loss (the amount in the till should be less than the cost of breaching the mechanism), the machine takes in coins, and via a simple mechanism, which makes a freshman computer science problem in design with finite automata, dispense change and product according to the displayed price. The vending machine is a contract with bearer: anybody with coins can participate in an exchange with the vendor. The lockbox and other security mechanisms protect the stored coins and contents from attackers, sufficiently to allow profitable deployment of vending machines in a wide variety of areas. Smart contracts go beyond the vending machine in proposing to embed contracts in all sorts of property that is valuable and controlled by digital means. Smart contracts reference that property in a dynamic, often proactively enforced form, and provide much better observation and verification where proactive measures must fall short.

Anyone who has sat through a contracts class in the first semester of law school will notice something amiss in the bolded text above, but before we examine that particular application of the term contract more closely below, let’s take a brief look at how Szabo took a vending machine transaction and formally expressed it as a smart contract:

sellCandy(candyPrice = $0.90) =
    variable moneyAmount = $0.00 
    then 
        # coins also fall into a temporary till tempTill
    when choiceOf(Counterparty, nickel)   
        to TempTill nickel 
        then to Counterparty add(moneyAmount, $0.05) 
        then to Counterparty display(moneyAmount)
    when choiceOf(Counterparty, dime) 
        to TempTill dime
        then to Counterparty add(moneyAmount, $0.10) 
        then to Counterparty display(moneyAmount)
    when choiceOf(Counterparty, quarter) 
        to TempTill quarter 
        then to Counterparty add(moneyAmount, $0.25) 
        then to Counterparty display(moneyAmount)
    when choiceOf(Counterparty, moneyReturn)
        to Counterparty dropCoins(tempTill, returnTill)
        with moneyAmount = $0.00 
        then to Counterparty display(moneyAmount)
    when threshold(moneyAmount, candyPrice) 
        to Holder (nickel | dime | quarter) 
            to CounterParty redirectNewCoinsTo(returnTill)
        also display("ready to dispense -- please select candy")
        then when (candySelection) 
            to Counterparty dropCandy(candyRacks, candySelection) 
            with to PermanentTill dropCoins(TempTill)
            with moneyAmount = $0.00
    continue

There you have it: a smart contract! Now, that might not seem like much of anything worth getting excited about. To be fair, a lot of what’s really interesting and important in Szabo’s early work relates to his conceptualizations of how cryptographic techniques could be used for the generation of digital cash and virtualizations of other forms of value and rights of parties that are common in real world commercial transactions but tricky to recreate in the digital domain. He recognized the importance of security (in both senses of the term) and noted how distributed computing strategies could be used to build a decentralized digital economy based on smart contracts. In short, much of what was eventually implemented in Bitcoin and alternative distributed ledger systems can be traced back to Szabo’s insights of two decades ago.

Despite the fact that Bitcoin transactions are really just simple smart contracts (per Szabo’s meaning of the term) and pretty sophisticated contract-like transactions can be modeled and executed as Bitcoin transactions, real interest in the legal sphere didn’t really pick up until the Ethereum project appeared on the scene. It’s easy to understand why. Bitcoin has always been used primarily as a cryptocurrency. Alt uses of Bitcoin have been generally focused on specialized applications and cryptocurrencies, and most of the private (also known as “permissioned”) blockchain projects have been narrow-gauged platforms for derivatives trading and other fintech applications. See, for instance, the platforms being developed by R3, Digital Asset Holdings, Chain.com and Symbiont.io among many others. Ethereum, on the other hand, was promoted from the get-go as a public (permissionless) platform that features a general purpose programming language for constructing “smart contracts” like Szabo envisioned. In fact, the original Ethereum white paper is entitled, A Next-Generation Smart Contract and Decentralized Application Platform. Whether or not it was the cause or merely an effect of a growing recognition of and interest in smart contracts in the legal community, Ethereum has become the poster child for the term itself.

The Pitch is Made to Lawyers

As things stand today, smart contracts are typically introduced to lawyers in conference presentations, articles, blog posts, etc. with no real definition of what they are, what they do and where they live. At most, they are “defined” by giving specific examples such as lease agreements, loan agreements, real estate transfers and registries, trade financing and payment arrangements, IP permissioning and, of course, a variety of banking transactions and other financial services. Drawing from these real world examples already familiar to lawyers keeps things simple but also tends to downplay some of the radical breaks in how things work in the blockchain world. It also downplays the fragmented and fast-changing landscape of the blockchain world that is still full of huge “TBD” infrastructure holes with respect to contractual transactions. Most of all, an example-based approach disguises how the same kind of real world contractual transaction can be (partially) modeled in fundamentally different ways on a blockchain, with very different legal implications and completely different impacts on the role of lawyers in the (smart) contract creation and execution.

The problem originates from the incomplete nature of a smart contract as the term was originally used by Szabo. Getting back to our law school contracts class concern, the vending machine in Szabo’s proto-smart contract example only explicitly models the performance stage of a contract. The form and formation stage is mostly just implied and assumed by our prior knowledge and experience with these machines, and thus, the term is infused with more conceptual weightiness than it really deserves. Would any lawyer ever characterize an unmarked black box with a slot at one end and a hole at the other as a “contract” knowing nothing else about it? No, of course not. What fundamentally differentiates a soda machine from an automobile is the implicit presence of the legal concept of a “meeting of minds” associated with the insertion of a coin in the coin slot but not with the insertion of a key in the ignition slot. Clearly, what makes a contract uniquely a contract and not some other form of interpersonal or automated activity is largely frontloaded in the form and formation stage of a contract and must be taken as an a priori condition in any deterministic form of human/machine interaction.

This problem with smart contracts has not gone unnoticed. Ian Grigg, for instance, describes it as a “semantic” weakness of smart contracts. His “Ricardian contract” proposes a way to model the contract form and formation stage online by specifying methods for tamper-proof recordation and validation of human-readable/natural language contracts with provable assent by the parties involved. Others, like the CommonAccord project, also focus on the form and formation stage with an emphasis on templatization and formalization of the contract terms. All of these contract form/formation efforts have jumped onboard the blockchain train, recognizing that this relatively new technology represents an increasingly legitimized business platform for hosting contracts/contract artifacts online in a reassuringly neutral and secure way. Not surprisingly, these form/formation efforts tend to be much more lawyer-friendly and lawyer-led because they generally leverage familiar legal concepts and protocols. By contrast, smart contract work has been done primarily by computer programmers based on leveraging concepts from computer science, cryptography and game theory.

The potential benefits of blockchain-based recordation of contracts should not be underestimated, just as the potential for automated contract performance via smart contracts is huge. However, as long as efforts to model contract formation and performance remain disconnected from each other, the broader issue of how blockchain-based transactions (including the numerous examples noted above) are to be interpreted and treated legally remains unresolved. Eris Industries was an early proponent of integrating the recordation of legal prose with the execution of smart contracts. R3, which is now touting the ability of its Corda platform to holistically capture legal prose and executable smart contracts, appears to recognize the value of supporting a more rigorous analysis of blockchain-based contracting. The success of these efforts remains to be determined, but it seems likely that the role to be played by lawyers and law firms in this new environment will be closely tied to how well drafting, formation and recordation processes (the traditional purview of lawyers) are integrated on-chain with the automated/smart execution processes (the programmers’ purview).

Up Next

Before we explore the lawyering impact further in part 3 of this series of posts, we need to dig a little deeper into another dimension of smart contracts not touched on above. It starts with a riddle that should be of considerable interest to lawyers: When is a $60 million breach of contract not a breach? For the answer, check out my next post…

• BigLaw offspring are produced by nearly exclusive recruitment of blueblood law schools. The incestuous plucking of the best-and-brightest of the top law schools by the preceding generations of the best-and-brightest of those same schools creates a baby-boom of summer associates who then (with relatively few exceptions) pupate into first-year associates.
• Far more associates are hatched than can possibly survive the arduous journey-of-BigLaw-life to partnership or other permanent position. A sort of primogeniture is required to avoid dilution of the wealth and power of the partnership. However, these days it is done based more on skills matched to firm needs demonstrated over the course of associatehood than on factors like class and connections already in place the day the first-years walk through the door.
• The winnowing process may occasionally have Darwinian overtones of associate competition, but BigLaw firms generally strive to create a patrician-style “family” environment defined by physical comforts, gadgets and other firm resources, scripted entertainment and other cool perks. Loyalty and identity are nurtured more by trappings of privilege and exclusivity than by deep personal bonding with and mentoring from those who might eventually be cutting the associates’ umbilical cords.
• The associates who (un)willingly drop off the partner track are not simply abandoned. Far from it! They are groomed for strategic marriages with other BigLaw, MidLaw or BoutiqueLaw families or sent out to colonize the in-house world. Some atone for their BigLaw sins by entering the judicial or academic clergies while others become advisors to the princely powers of governmental agencies. Regardless of the destination, the future success of these second-borns continues to reinforce the BigLaw estate almost as much as the efforts of the privileged first-borns who take up permanent residence at the familial manor.

You probably haven’t thought about the strategy in these primogeniture terms, have you? That’s because the strategy is most often described as a pyramid scheme where the purpose of the large numbers of associates cycled through the big firms is to provide financial leverage for the relatively few partners at the top of the heap. The need to allow a few to successfully run the gauntlet to partnerhood is just a necessary evil for keeping the scheme going. In this particular characterization the long-term benefits derived from the network effect of the BigLaw associate diaspora are completely ignored. Consequently, the focus is exclusively on the vulnerability of the pyramid scheme to the changing market conditions in which clients increasingly resist packing their matters with junior associates and in which LPOs, staff attorneys and technology-based solutions undercut the short-term financial value of the base of the pyramid.

Here’s a different but perhaps less crass way to think about the strategy. Pundits frequently decry BigLaw’s built-in structural and cultural barriers that result in the annual siphoning off of all profits in the form of partner compensation with virtually none of it plowed into R&D and other long-term investments in the institution. Critics are quick to point out BigLaw’s predilection for short-term profits and disinterest in R&D, but they rarely offer a coherent argument for how BigLaw R&D should work (or even why efforts like Dentons’ NextLaw Labs should be “owned” by law firm partnerships). All this misses the fundamental point that BigLaw actually invests heavily in R&D. It’s just not in the form you typically see in the corporate world, and its value differs from how corporate R&D generates value. BigLaw’s version of R&D is the time and money it spends to recruit, pay, train/support and entertain the hordes of unproven law school graduates brought in and then run through the BigLaw “development labs” over a period of years. Of course, many of these investments don’t really pan out (hey, that’s what happens with R&D), but some are ongoing fee-earning winners in the near-term and maybe even “blockbuster” winners as partners in the long-term. The others can still pay long-term dividends in the form of business referrals and reputational support of the law firms.

Thinking of R&D in these terms helps to explain why BigLaw hasn’t already switched to a model of permanent staff lawyers for the low-end stuff and experienced lateral hires for replenishing/growing the partner ranks. As pricing pressures continue to rise and the ability to shift these R&D costs to clients declines, BigLaw’s dedication to this strategy will surely be tested.  Acceptance – i.e., severe curtailment of the top-of-class/top-law-school pipeline – could very well spell the beginning of the end of the age of BigLaw.

What got me thinking about this topic was a fascinating guest blog comment on the UK-based Legal Business website by Clifford Chance’s London managing partner. Citing the challenge posed by AI tools like the IBM Watson-based Ross and Riverview Law’s Kim system, David Bickerton asked this important question:

[I]f the apprentice style of learning at the expert’s knee is going to be overtaken by Kim and Ross, how will the profession generate the experienced advisers that clients seek to consult?

Setting aside the fact that Kim is designed for use by managing level in-house counsel and not law firm lawyers, one might expect Bickerton to answer his own question by recommending that BigLaw embrace these emerging technologies and use them to leverage junior associates into resources valued instead of shunned by clients. Nope, Bickerton went a different direction. After a tentative call for partners to lead by example with technology, he reverted to the standard BigLaw playbook for recruiting “the best” by “tak[ing] pay off the table” and providing “exceptional facilities” (referencing swimming pools, squash courts and gyms) and “training” (not elaborated on). Annual reviews and ad hoc feedback, a diverse and accepting work environment with pro bono opportunities were all duly noted as well. As I said…standard BigLaw playbook stuff and a step back from looking more deeply into the chaos.

But Bickerton’s original question still begs to be answered. Will AI be the final nail in the coffin of the BigLaw primogeniture strategy by making junior associates totally redundant? If so, does it herald the end times for BigLaw? Let’s start answering this more directly by getting one thing straight: the “apprentice style of learning at the expert’s [i.e., partner’s] knee” is already largely a relic in BigLaw. Hands-on mentoring of juniors by partners has been in decline for years as the pressure for billing and business-generation by partners has ratcheted up at the same time as client resistance to associate shadowing at meetings, calls, hearings, etc. has increased. Associate leverage has also played it’s part in reducing the frequency of partner contact for individual associates. In fact, one of the primary reasons for the rise of KM and other functions like professional development in BigLaw is this change in the dynamics of partner/associate apprenticeship. If, of necessity, partner/associate interaction has become much more selective and targeted to formalized activities like group training sessions and mandated reviews, this means that the traditional iterative learning process frequently lacks realtime input and correction by a human expert (i.e., a partner or other senior lawyer). Associates either flounder (unhealthy), turn to each other (dangerous), or move onto the next task without feedback on the last (unproductive).

Functions like KM and professional development can provide some context and might jumpstart an associate task with background materials, templates, models, etc., but they seldom offer substantive feedback, corrective guidance, and validation later in the process and particularized to the task. This is where AI can help by, in effect, filling some of the mentoring vacuum left by the absence of real human mentoring. Thus, AI is less of a threat to Biglaw primogeniture than imagined and might even reinforce it. The answer to Bickerton’s question, then, is not to dread or avoid AI and related technology but, rather, to genuinely embrace it as a critical component of your associate “research and development” infrastructure. The good news for BigLaw here is that AI generally improves with scale, so bigger firms with more associates cycling through should have greater success with AI than smaller firms or in-house legal departments.

Of course, all the AI hype might turn out to be just that…hype…in which case the benefits of AI described in the preceding paragraph won’t actually materialize. That would be a shame, but if the benefits of AI don’t materialize, it’s also pretty unlikely that the risks of AI will materialize either. In short, if AI doesn’t work well to assist, correct and guide (human) associates, it’s hard to imagine that it will replace them altogether and become that final nail in the coffin of BigLaw primogeniture.

The Kodak moment case against BigLaw was made recently in the 2016 Report on the State of the Legal Market published by The Center for the Study of the Legal Profession at the Georgetown University Law Center and Thomson Reuters Peer Monitor:

The reactions of the law firm market to the rapidly changing environment in which firms operate parallels in some respects the story of Kodak. The current challenge in the legal market is not that firms are unaware of the threat posed to their current business model by the dramatic shift in the demands and expectations of their clients. Instead, as in the case of Kodak, the challenge is that firms are choosing not to act in response to the threat, even though they are fully aware of its ramifications. There are many reasons that may lead firms to make this choice, but one of the primary ones is surely that, like Kodak, many law firm partners believe they have an economic model that has served them very well over the years and that continues to produce good results today. They are consequently reluctant to adopt any changes that could put that traditional business model at risk. While that might appear to be a viable short-term strategy, the danger is – again like Kodak – that this effort to preserve their past and current success could result in law firms failing to respond to trends that over time could well challenge their traditional market positions. There is already growing evidence that those trends are well underway. It remains to be seen whether most firms will be able to avoid the dangers posed by their own success.

Ron Friedmann in his post, Is Big Law Having Its Kodak Moment? responds to the Georgetown/Peer Monitor report by arguing that the velocity of change in the legal market, while real, is not sufficient to justify dire proclamations of private law firms facing an extinction level event. I completely agree with Ron that the threat is exaggerated, but I also think that there is a different lesson to be learned from the Kodak story – one that has been continually missed in the Kodak moment morality play.

First, some historical context about Kodak that was not provided in the version of the Kodak story depicted in the Georgetown/Peer Monitor report: George Eastman didn’t invent photography or the basic light sensitivity chemical processes used for his film and paper. Nevertheless, he was a quintessential disruptor because his film-based solution was vastly more portable and cheaper than the glass plate solution it replaced. Kodak’s core (existential) business was always light-sensitive emulsion bonded to film and paper and associated development chemicals rather than camera production and sales. Although it was necessary for Eastman to develop (no pun intended) the Brownie camera in order to initially sell his real products, the inevitable competition and disruption in camera types, sizes, cost, etc. was actually a very positive thing for Kodak throughout the film era. While Kodak’s core business faced active competition from Agfa, Fuji, Ilford and others, it was never particularly disruptive and was never an existential threat to Kodak’s business. Even the Polaroid process (which Kodak helped develop and supported early on) was more of a market expansion than a disruption.

It is a mistake to think that digital cameras were the ultimate disruptors that tripped up Kodak and, therefore, that Kodak’s “moment” was failing to jump on the digital camera bandwagon that it’s own employees helped invent. In fact, Kodak halfheartedly produced digital cameras just as it had, for many years of its existence, halfheartedly produced analog (film) cameras. Even if Kodak had more vigorously committed to digital camera production, chances are very good that it still would have failed. Indeed, there’s a good chance it would have failed even faster than it actually did. That’s because it lacked any advantage at the high-end of the market (no established interchangeable lens mount and profit-generating lens catalog compared to Nikon, Canon, etc.), and the digital point-and-shoot low-end of the market pretty quickly became commoditized, viciously competitive and unprofitable similar to what happened in the personal computer sector. More importantly, the bottom of the digital camera market has been almost completely disrupted by camera phones. Today, the high-end DSLR market is in bad shape too, with some players, like Samsung, failing outright in the market and most of the others either losing money or treading water only because lens sales buoy camera R&D and marketing costs.

Kodak’s actual “moment” and true disruptive nemesis was the advent of digital display, storage and sharing of photographic images. If it weren’t so damn easy to upload, share and view photographic images online and photographic consumers still depended on paper-based prints, chances are good that Kodak would not have gone bankrupt. Yes, the blow from its loss of film sales would have been significant but it could have continued to compete in the print and processing business at its core and maybe even expanded, especially if increases in digital image-making in the consumer market resulted in increased print demand. In short, blaming Kodak’s demise on its failure to get fully behind digital camera production is not only wrong, it probably actually extended Kodak’s corporate lifespan!

What’s really telling here is that nobody faults Kodak for failing to get into the digital monitor business or the social web application business. The obvious reason is that the technological underpinnings of the hardware and software related to digital image display, storage and sharing are so unrelated to Kodak’s core competencies and the technology itself relates to so many more types of content than just photographic images that it’s just silly to think that Kodak could have applied its specific market advantages in photographic chemicals, paper and films in these completely different technical spaces. Quite simply, Kodak has taken a bum rap for its strategic inaction, considering that nothing short of abandonment of its core business would have saved it. Kodak’s real sin here is its failure to diversify away from photographic imaging altogether like Agfa (and a few others) did.

With all that in mind, let’s reconsider how the Kodak story really relates to the present state of Biglaw. What can we really learn from the Kodak moment? The answer depends on what you view as BigLaw’s existential core (akin to the photographic film, paper and chemicals part of Kodak’s business) and whether the technological and business environment changes referenced in the Georgetown/Peer Monitor report and elsewhere are directly striking at those core legal services and products. If the disruptions are primarily occurring in the secondary and support products, functions and revenue sources of BigLaw, then it’s questionable to even label them as “disruptive,” which is basically the argument Ron makes in his blog post. But…and this is the big gotcha: If the disruptions are so significant that the only solution is for BigLaw to essentially abandon its core identity and stop doing whatever it does best, then we’re really talking about something like institutional mass extinction and not just “disruption.” The answer is not, “Get better, faster, leaner!”  The answer is, “Get out!”

The real Kodak moment would imply that BigLaw’s core services – i.e., legal structuring, advocacy, risk mitigation, advice giving, etc. – are unneeded or completely replaced by something else (the pure libertarian bliss of everything transacted on blockchains perhaps?) In this scenario the only chance of survival for BigLaw is to diversify away from actually providing legal services! Sounds pretty ridiculous or pretty depressing, depending on how you choose to look at it, but it’s not totally unprecedented. Consider what happened to the big accounting firms. They didn’t actually abandon their core accounting and auditing services and therefore didn’t have a genuine Kodak moment as I’ve reframed it, but they certainly added a whole bunch of other consulting services. Is diversification into ancillary consulting services (with some related online products) and a shrinking dependence on traditional legal services the answer to BigLaw’s supposed existential crisis?

Lawyers with their specialized skill sets and cumbersome partnership and revenue generation models appear to be poorly positioned to compete in broader consulting, publishing and other knowledge services. Like Kodak with no digital display expertise or other compelling competitive advantage, the notion of BigLaw successfully pivoting into other markets is hard to fathom. In fact, it’s SO difficult to conceptualize that it makes the much maligned laissez faire attitude of BigLaw partners both understandable and perhaps even rational. Keep that in mind the next time you read about some looming Kodak moment and the push for change. The conservative response is not always the wrong one.

In my post about analytics here, I noted that the challenge of performing certain analytics tasks in the legal domain is simplified by the well-defined and publicly accessible caselaw source data used in the analysis:

The cases themselves are uniquely named and codified, as are the jurisdictions, courts and judges. Parties/roles and names of counsel, litigants and other participants have been vetted. Even softer metadata like issues, actions, and outcomes have been successfully extracted and disambiguated. Of course, all of this high quality data is continuously supported by a stable court system and a large private publishing infrastructure. The result is a target-rich content environment for analytics and one that accommodates relatively simple user interfaces. Unfortunately, the same does not hold true for legal work not directly or completely circumscribed by court filings (and to a lesser extent, certain regulatory proceedings). Factor in all of the ancillary activity inside of the law firms related to this sometimes rich but more often impoverished external data, and you have the kind of complexity that can’t be untangled by analytics alone. 

Let’s explore this observation a bit further in the context of how law firms manage matters by starting with a rather philosophical question: What is a matter? The answer depends on which part of the elephant you’re blindly feeling, but generally speaking there are two ways to answer the question:

• The Legal Event Definition. A matter models a legal event in the real world such as disputes; deals; creation, dissolution or change in legal status of individuals or entities; actions by regulators, etc. The matter primarily serves to structure and group content, activities and information collected by the firm and to facilitate professional and firm processes related to the legal events.
• The Billable Event Definition. A matter models the work expended by firm timekeepers based on units of time and related metadata. It primarily serves to group together these units of time to facilitate client billing and internal firm financial reporting and management.

Of course, the billable event definition is dependent to some extent on the legal event one. Law firms do not expend time ad hoc for clients and arbitrarily create matters that have no correlation to real legal events and the actual legal projects being worked on. The key point here, however, is that structures expedient for billing and reporting do not always correlate with structures that work best for managing legal events and related content. The tension between these two approaches to structuring matters results in significant breaks in how matters are defined and tracked. Frequently, the billable event definition prevails either because of system limitations or for the sake of billing or procedural convenience. Some examples that come to mind:

• Separate matters opened to simplify bill splitting between multiple clients;
• Separate matters opened to address differing tax implications in multiple jurisdictions;
• Separate matters opened for different practices or different offices to simplify reporting and billing partner control;
• A single matter maintained for shelf offerings with multiple takedowns or other kinds of multi-part financings to simplify timekeeping and billing;
• A single matter maintained for periodic or other forms of repeating or cookie cutter work or as a “general matter” catch-all to avoid the hassle of new matter openings;
• Projects parked in preexisting matters to game or circumvent firm procedures or optimize partner financial credits and client relationship control;
• Matters opened to accommodate client-specific special billing requirements.

The tension between billable and legal events is not the only problem for structuring matters. Legal events are often complex and messy and lack well-defined borders, beginnings and endings. They morph and evolve over time. We frequently see problems arising from inconsistent handling of litigation cases (i) brought in separate jurisdictions but related by subject matter, (ii) split or consolidated during the course of the matter, or (iii) appealed to a higher court. Likewise, complex M&A matters can spawn bank financing, securities issuances, advisory work, asset transfers, regulatory approvals, litigation, etc., and each can be treated as independent legal events worthy of their own matter structure or as part of a whole. And all of these problems just scale up in BigLaw because bigger law firms tend to generate more matters that span offices, practices and legal jurisdictions and tend to encounter more matter integration challenges from firm mergers and lateral hires.

The bottom line here is that matters – the presumed atomic units around which all substantive legal work revolves in law firms – are really more like atomic clouds that don’t behave as expected when observed! (Shout out here to quantum physics geeks.) The strength (usefulness) of that atomic bond will vary in complex and largely uncontrollable ways, but virtually all mission critical law firm systems are built around a unitary matter concept that neither recognizes the tension between the billable and legal event definitions nor accommodates the ambiguity and complexity that inheres within matters. The brittleness of the matter concept in law firms is propagated across applications that are all based on a singular matter ID used as a (unique) key in all of the firm’s matter-related systems. Since most law firm systems use common matter IDs as their keys and are built on the relational database model, they can be integrated for querying and data-sharing purposes. That’s nice, but these dependencies remove flexibility and effectively force all systems (regardless of unique internal features) to be constrained  by the specific requirements and limitations of the most “critical” of the mission critical matter-based systems.

Time (and Billing System) Critical

We all know that the 1000 pound system gorilla in Big law is the time and billing system (TBS). Care and feeding of the TBS drives how and when new matters are opened even if it doesn’t host the matter opening workflow or push matter metadata to others systems. Chances are very good that what’s most convenient or addresses a limitation in the TBS will prevail over what’s most convenient or addresses limitations in other matter-specific systems. It’s safe to say that in most BigLaw firms the TBS is the privileged first-born whose peculiar eating habits are indulged, and the matter-based KM systems in particular are the abused stepchildren left to scrounge for table scraps left by the TBS! The indigestion that KM folks experience as a result of the previously noted accommodations made for TBS-driven matter management includes:

• Misleading or erroneous (dynamic) joins between matter level metadata and documents in enterprise search applications;
• Difficulty collecting an accurate and complete set of closing documents or pleadings;
• Matter level templates for matter pages and folder structures that require modification when applied;
• Problems with trying to generate all kinds of matter-level reports for practice management purposes;
• Difficulties creating and updating experience lists for business development that accurately reflect work done by the firm on different types of matters;
• Too many exceptions and inconsistencies in how matters are managed to implement standardized or automated workflows for things like matter opening and closing, after-action reviews, matter team staffing, application of document retention rules, etc.

The schizophrenic way in which law firms define matters will also impede the successful BigLaw adoption of big data and cognitive computing technologies for analysis of matters and things like automated extraction of matter metadata and predictions of costs of different types of matters. The initial effort to train/learn will likely go up and the usefulness of the analytics will likely go down relative to the messiness and “noise” inherent in all those poorly defined matter structures.

Circling back to the quoted observation at the beginning of this post, we can better see now why the success of the emerging caselaw analytics tools will not be easily transferable to matter-based analysis inside of law firms. Even though these caselaw tools deal with judicial decisions that are mostly unstructured text, those decisions are nevertheless contextualized and supported with well-defined metadata about the cases, the judges, parties, courts, related documents, etc. The critical takeaway here is that online caselaw collections, as tapped into by analytical tools, are complete and carefully curated artifacts of a highly formalized class of legal events. Firm matters at first blush look a lot like what’s tracked in these commercial systems and, indeed, may arise from the same legal events and associated content, but in the end are less formalized and subject to frequently competing definitions of what is inclusive to a specific matter. This fundamental matter definitional problem exists before we get to additional confounding issues like incomplete content capture and inconsistent application of naming and tagging conventions (to say nothing of security and access issues that don’t apply to public court filings).

What Can KM Do About the Problem?

Unfortunately, KM is not in a great position to fix the conflicting matter definition problem. That’s because, as noted, KM generally lacks the clout required to insist on any kind of rigid standardization that eliminates the TBS exceptions. Furthermore, KM applications are generally dependent on an overly-simplistic unitary matter model. There’s not a lot of hope of overcoming either of these limitations in the short-run, but you can still take some positive steps toward minimizing the problem. I’d be interested to hear about solutions others have come up with, but here are a few of my own experience-based suggestions:

• Educate the finance function in your firm about the problem. You’d be surprised at how unaware finance staff can be about the unintended consequences of their jerry-rigged TBS fixes. That’s not to say that your appeal will be acted on, but sensitizing finance staff to the ripple effect of their actions can potentially redirect thinking toward solutions that are less disruptive to the KM function or provide more advance warning of impending changes. The more quid pro quo you can offer (e.g., sharing with the finance function useful matter metadata being collected by KM), the more sympathy and cooperation you’ll likely receive.
• Educate the IT function as well. Matters are just a vague legal abstraction for lots of IT staff and they often need assistance in understanding the complexities and ambiguities of how legal and billable events come together as matter entities. It certainly doesn’t help that virtually all of the vendor systems and tools IT deals with only support a unitary matter framework wherein one matter is presumed to have a single set of data points (descriptions, values and tags, participants, activities/events, documents, etc.) that all link to each other equally or in rudimentary relational ways. By working closely with your IT team, you can help them to understand the problems that spool from overly simplistic matter-centric applications. Fixing these problems can be hard, especially if you’re stuck with off-the-shelf solutions with limited configurability, but IT-types love a technical challenge and, together, you might be able to devise strategies for minimizing the negative impact of poorly designed matter applications.
• Ally with the business development, risk management, conflicts and records functions in your firm. These functions generally “get it” when it comes to understanding that the ideal relationship of matters to legal events is often broken in matter-based systems. Like KM, they confront the consequences of the problem every day when trying to track experience, review conflicts, security and other matter risks, file documents, etc. They can help you lobby for process and system changes that might otherwise be unpopular with or under-prioritized by IT, finance and firm administration.
• (With IT assistance) assess your options for uncoupling matter tracking from the TBS.  Determine if your matter management infrastructure is rigidly tied to a “flat” model or allows for submatters or related/sibling matters that you can activate without adversely affecting billing and reporting processes. Alternatively, determine if you can develop a legal event tracking solution in SharePoint or some other general purpose tool and use that as a KM-controlled “shadow” matter hub. (Just bear in mind that alternative systems and workarounds may gain you much-needed flexibility but will burden you with updating/maintenance responsibilities.)
• In your document management system explore ways of using profiling, tagging and foldering to subdivide content within a matter-centric space. A well-defined and consistent foldering or tagging schema can minimize problems created by “general” and other reused matters. Alternatively, copy or link documents from your work-in-progress DMS libraries to a KM repository (perhaps a separate DMS library or SharePoint) that is associated with your shadow matter tracking solution.
• Do not rely exclusively on the main matter ID as the means for integrating/joining content in your enterprise search system. Work with IT and your search vendor to crawl content based on the shadow matter profiling, foldering or tagging. There are ways to do this so that the matter filter in your search system functions as if you have virtual submatters or sibling matters. Your main matter management system doesn’t have to be changed to support this.

Educational efforts and band-aid system fixes can only go so far, and they inevitably bump up against change-resistant lawyers, administrators and staff. The duplicative impact of matter shadowing solutions can add to confusion at the same time they are addressing ambiguity and complexity. The boogeyman of security overlies everything and rears its ominous head particularly when the solution involves duplication of content into alternative collections not based (solely) on a firm’s standard matter management workflow. Indeed, we are still a long way from the ideal, rational environment in which matters – the fundamental atomic units of law firms – reinforce useful analytics rather than blur their effectiveness.

The good, or at least intriguing, news is that the world is changing in ways that are working in through the seams of BigLaw. The cracks are getting bigger as the ironfisted rule of the billable hour loses its grip. Perhaps as the service model transforms in BigLaw and billable hours become less important, the corresponding dependency on the billable event definition of matters will also lessen along with the potential for conflict with the legal event definition. Likewise, new technologies are emerging that may supplant today’s matter systems built on conventional relational/SQL platforms. Document-based NoSQL and graph databases with more flexibility for modeling complex legal events and data lakes with powerful ingestion, data transformation, search and analytics capabilities for exploring BigLaw big data may help us fix the problem at the atomic level. Who knows? Maybe someday soon we’ll be able to split a matter or fuse two of them together without blowing up the whole law firm!

What is it about dabbling that makes it so irritating and yet so strangely irresistible to those of us involved in knowledge management? Think about it. Dabbling is in some respects a precursor or catalyst for KM. You might even say that the purpose of KM is to harness the curiosity and confidence that compels one to dabble and to guide it in a structured way toward just-in-time understanding. In short, knowledge management is supervised dabbling!

Left unattended, dabbling sometimes results in genuine knowledge acquisition and even insight but it too often results in unjustified (i.e., lucky) true belief or even false belief. The former will eventually lead to misapplication of the belief and associated expense or embarrassment, and the later will just accelerate that eventuality. Knowledge management, done correctly, constructs an environment in which “dabblers” can achieve successful outcomes and appear to others to have expertise even if the dabblers themselves remain non-experts. Conversely, KM done incorrectly or incompletely can turn ordinarily cautious individuals into disinhibited dabblers who make poor decisions and give inexpert advice. In the absence of a good KM structure, dabbling is constructive only so long as the outcomes are inconsequential and the conclusions drawn are provisional and not promoted to others as knowledge-based. (If you would like to dabble in a bit of related philosophy, click here.)

In this Internet Age when so much content is frictionless and readily accessible (e.g., the Wikipedia link in the preceding paragraph), dabbling becomes something of a social necessity; and with everyone dabbling, our faculty for discriminating between mere dabblers and real experts is over-burdened to the point of exhaustion. We too easily accept the pseudo-knowledge of dabblers who toss around impressive jargon and too readily reject the guidance of experts just because we’ve turned to generalized skepticism and rejection of traditional authorities. I was reminded of this problem at LegalTech last week. It’s exhausting to go booth-to-booth, session-to-session and event-to-event trying to converse intelligently with friends and strangers alike on so many technical products and topics. Let’s face it, most of us there were often just dabbling and that includes many of the individuals staffing the vendor booths (and a good share of the session panelists I’d presume).

Am I being too cynical here? Consider this: a LegalTech News article covering one of the sessions described a blockchain as “based on an algorithm that records data in a hatch…” It doesn’t require much dabbling in blockchain technology to know that the term is “hash,” not “hatch.” The error is now corrected in the article, but it’s still obvious that the writer simply wasn’t familiar with this fairly obscure corner of technology. To be fair, the legal technology community (including the press) has only very recently begun to consider the potential for smart contracts and other blockchain-based legal applications. I didn’t attend the session itself, but I wonder just how much genuine understanding of this specialized and rapidly evolving topic was present in the room and how much of it was just a generalized exercise in dabbling? How many of these conference events are more than excuses for collective dabbling by attendees, self-promotion or product marketing by presenters and socializing for all?

So, yes, we’ve become a society of dabblers and without proper adult supervision – i.e., access to real subject matter experts, formal education or the kinds of authoritative knowledge resource KMers are often involved in managing – we are all at risk of ever-wider but ever-shallower intellects. I see this as the next great challenge (or opportunity, depending on your perspective) of the emerging (post) Web 3.0 era. Dabbling is on the rise and reliance and trust of traditional modes of authority is on the wane. As the various forms of artificial and augmented intelligence are added to the Web 3.0 mix, will dabbling itself become even more compelling and useful or will it just scale up collective expectations and magnify the detrimental consequences when our dabbling goes awry?

Dabble on it and let me know what you think…

[Note: My apology for anyone expecting this post to be the previously promised one about a major BigLaw metadata challenge. Stay tuned for that upcoming post.]