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# Articles for Final Review - Release 1.0
First round of articles for Editorial Board
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# A Perspective on Legal Algorithms
## Legal Algorithms
Code is law, and law is increasingly becoming code. This change is being driven by the growing need for access to justice and the ambition for greater efficiency and predictability in modern business. Most laws and regulations are just algorithms that human organizations execute, but now legal algorithms are beginning to be executed by computers as a function of human bureaucracies. Already, computer tools are commonly used to help humans make legal determinations in areas such as finance, aviation and the energy sector, most of the logic is computerized and subject only later to human oversight. Moreover, the execution of legal algorithms by computers is likely to dramatically expand as digital systems become more ubiquitous. Even court proceedings are becoming increasingly reliant on computerized fact discovery and precedent, which will likely lead to more and more cases being settled out of court.
As evidenced by the intrigue and engagement that young lawyers and visionary legal scholars have shown, the legal profession is quietly seizing upon the opportunities provided by the transition from bureaucracies to computers. It may surprise readers to learn that several law schools have established entrepreneurship programs and incubators focused on legal technology, including Suffolk University Law School and Brooklyn Law School. Faculty of both law schools are among the founders of this Computational Law Report. Young lawyers in training are similarly engaged. I was pleasantly surprised to see that the recent "[Blockchain for Open Music](https://github.com/mitmedialab/OpenMediaLegalHack/tree/master/docs)" hackathon, organized by the founders of this Report, was hosted by nine law schools on four continents. The legal profession is beginning to go fully digital!
Nevertheless, as legal algorithms transition to being executed by computers, we must be careful not to lose the guardrails of human judgment and interpretation ensure that the legal algorithms improve justice in our society. We must continue to safeguard, and even substantially increase, human oversight of our legal algorithms.
We must also recognize that current legal and regulatory systems are often poorly designed or out-of-date. As we transition to computer execution of legal algorithms, we have a unique opportunity to make laws more responsive and precise. Relatedly, we should recognize that many legal algorithms fail to achieve their intended aims, or have unintended consequences, and we must ask if there is a better method of ensuring the performance and accountability of each legal algorithm.
## Computational Law
How can we achieve greater oversight and accountability of legal algorithms while harvesting their potential to provide greater efficiency, ease of access, and fairness? The obvious answer is to learn from the [human-machine systems framework](https://journals.sagepub.com/doi/full/10.1177/0018720817695077?url_ver=Z39.88-2003&rfr_id=ori%3Arid%3Acrossref.org&rfr_dat=cr_pub%3Dpubmed) which has evolved over the last century to become the standard practice in designing and fielding of human-machine systems across the world. Leading examples of this framework include Amazon's fulfillment and delivery systems and internet connectivity systems.
> [Figure 1](https://journals.sagepub.com/doi/full/10.1177/0018720817695077?url_ver=Z39.88-2003&rfr_id=ori%3Arid%3Acrossref.org&rfr_dat=cr_pub%3Dpubmed#_i8)
The stunning efficiency and reach of these systems comes, perhaps unsurprisingly, from modesty: the idea that you can't ever build human-machine systems that "just work." Instead, you will have to continually tweak, reiterate, and redesign them. Once you accept the limitations of the human intellect, you realize that the system must be modular, so you can revise the algorithms easily; the system must be densely instrumented, so you can tell how well each algorithm is working; and, less obviously, the design of the system *and each of its modules* has to be clearly and directly connected to the goals of the system so that you know *what* modules to redesign when things go wrong and *how* to redesign them.
To be clear: some "modules" are software, but others are people or groups of people, all working to execute the algorithms that make up the human-machine system. "Redesigning" human "modules" means reorganizing and perhaps retraining the people, a process familiar as "[Kaizen](https://archive.org/details/kaizen00masa)" in manufacturing and as "[Quality Circles](https://archive.org/details/qualitycirclesha00hutc)" in business generally. Note that for the quality circle process to work, the people in the system must clearly understand their connection to the overall goals of the system.
A key element of this design paradigm is testing. We simply cannot design a complex human-machine system that works without extensive testing, field piloting, and evaluation. Testing always begins with a simulation of key components, then the entire system, and concludes with pilot deployments with representative communities as an experiment in which participants give informed consent. Moreover, this testing and evaluation is not just as part of creating the system, it must also happen continuously after large-scale deployment of the system. Things change, and in order to adapt, we must continue to tweak and reengineer the system.
The ability for workers (or regulatory staff members) to critique and revise their jobs (e.g., the Quality Circle process) is key to the success of the overall system. In traditional legal systems, the task of auditing and revising modules based on performance feedback is the role of senior regulators and the courts. The task of auditing and revising the overall system architecture is traditionally the role of legislators.
When the legal system process is compared to more successful human-machine systems it becomes clear that our current legal processes give insufficient thought to instrumenting modules (e.g., why did it take a decade to evaluate broken windows policing?), and insufficient thought to designing systems that are modular and easy to update (e.g., the health care system or tax code). A subtler problem is that the current legal algorithms are insufficiently clear about the goals they are intended to achieve, and about what evidence can be used to evaluate their performance.
## Simple Examples of Computational Law Systems
Some simple examples of using this design framework to build successful legal algorithms may help illustrate these ideas. The first example is a government setting up an automatic, algorithmic legal system -- specifically a traffic congestion taxation system. This system, implemented in Sweden, reads car license plates and charges drivers for use of roads within Stockholm. We can see each of the components of proper legal algorithm design in the [Wikipedia description of the system](https://en.wikipedia.org/wiki/Stockholm_congestion_tax).
* The motivation of the congestion tax was stated as the reduction of traffic congestion and the improvement of certain air quality metrics in central Stockholm. Consequently, the ***goals*** of the system were clear, and the ***measurement criteria*** for system performance were well understood.
* Following seven-months of ***testing*** during a trial period, the tax was implemented permanently.
* After initial deployment, the system design was ***adopted and revised*** to obtain better performance by charging higher prices for the most central part of Stockholm.
* The system was ***audited*** for the first 5 years of operation and demonstrated a decrease in congestion, with some motorists turning to public transport.
While the elements of algorithmic design may seem quite obvious in this example, such considerations are often not present in the creation and operation of algorithmic legal systems. Sweden's congestion tax system has since been used as a model by city governments and urban planners around the world.
The second example is commercial and drawn from my personal experience helping guide Nissan to create an autonomous driving system for their cars. This system design is now the largest deployed autonomous driving system in the world (at level 2). The development of the system began with specifying the design objective:
* The ***goal*** of the car navigation system should be to achieve safer driving without distracting the driver. It should feel like you are just driving the car as usual, but the car just naturally does "the right thing." The human is always fully engaged and in charge.
* Laboratory ***testing*** of the system revealed that the car's idea of "what to do" must match the judgment of human drivers, so that the car never does anything the driver does not expect or understand.
* The system was ***adapted and revised*** through pilot deployments that determined when the car could usefully help the driver, and when it should not try to help. The system was also improved iteratively as new sensing technologies became available.
* Following commercial deployment, the system has been continuously ***audited*** for safety and customer satisfaction, and is continuously updated.
The consequence is that driving has become much safer, and people love the system... although sometimes they fail yo appreciate just how much the system is doing. For instance, drivers often fail to appreciate how the system subtly teaches them to be better drivers. Instead of functioning merely as a tool that replaces humans or human reasoning, these types of systems are more akin to training wheels or guide rails. In fact, the original name for the system was "magic bumper."
## Missing Components of Successful Computational Law
Unfortunately, several of the elements highlighted above are underdeveloped or even missing from current legal and regulatory system processes. These include: specification of system performance goals, measurement and evaluation criteria, testing, robust and adaptive system design, and continuous auditing.
### Specification of system performance goals
The creation of a new system of legal algorithms (e.g., a law and associated regulation) requires a debate among citizens and legislators concerning objectives and values which results in a clear specification of the overarching goals of the systems' objectives. The failure to specify objectives increases the likelihood that the resulting legal systems will fail to provide good governance and may produce negative unintended consequences.
### Measurement and evaluation criteria
To have any chance of determining whether or not something is a success, we need to have an appropriate point of comparison. For example, how do we know when the system is performing well? How do we know when each module (individual algorithm) within the system is performing well? The connection between the measurements and objectives must be clear and very broadly understood by citizens. Without this understanding, the informed debate demanded by our governance system, and the informed consent of the governed, is unlikely.
### Testing
Currently, laws proposed by the United States Congress undergo simulation testing by the Office of Budget Management, and often regulations are subject to simple cost-benefit and environmental evaluation. Helpful as this testing may be, it is inadequate if we are to build responsive and adaptive algorithmic legal systems. More seriously, there is almost no tradition of testing new legal algorithms (whether executed by human bureaucracies or by computers) on a representative (and consenting) sample of communities. This failure to test is hubris, tantamount to believing that we can build systems that are perfect *ab initio*. It is a recipe for creating low-quality legal systems.
### Robust adaptive system design
The system of legal algorithms (e.g., a law and associated regulations) must be modular and continuously auditable, with a clear connection between measurement criteria and system goals, such that it is easy to revise or update modules (legal algorithms) and module organization. A failure to implement modern system design tools makes it likelier that the resulting legal system will be opaque, unresponsive to harms, and difficult to update.
### Continuous auditing
Systems of legal algorithms (e.g., a a law and associated regulations) must have an operational mechanism for continuous auditing of all modules and overall system performance. Such auditing requires involvement and oversight by all human stakeholders, and must include, by default, the capacity of those stakeholders to modify algorithms or system architecture so that the system meets specified performance goals. The failure to audit ensures that we will have serious failures of our legal system as society and our environment evolve. I suggest that ability to modify algorithms be accomplished by requiring regulators, legislators, and courts (as appropriate) to respond promptly to stakeholder concerns.
## Implications for the Practice of Law
What does this mean for lawyers and legislators? Historically, legal careers have begun with the drudgery of wordsmithing and searching through legal documents. In the manner as happened with spell check and web search, this work is now being streamlined by AI-driven document software which searches large document stores to find relevant clauses and suggest common wordings.
These trends are often seen as reducing the demand for legal services, but there are also new opportunities for developing legal agreements using tools originally intended for creating large software systems. These tools are beginning to allow lawyers and legislators to design much more agile, interpretable, and robust legal agreements.
As a consequence, the legal profession has the opportunity to transition from being a cost center and a source of friction, to a center for new business and opportunity creation. The goal of this Computational Law Report is to help seize this opportunity, to support new legal scholars in their enthusiasm for using new digital technologies, and to improve our systems of contracts and governance.
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# The Future of Law and Computation: Two Sides of the Same Coin
Daniel W. Linna Jr.
The rapid advancement of artificial intelligence (“AI”) introduces opportunities to improve legal processes and facilitate social progress. At the same time, AI presents an original set of inherent risks and potential harms. From a Law and Computational Technologies perspective, these circumstances can be broadly separated into two categories. First, we can consider the ethics, regulations, and laws that apply to technology. Second, we can consider the use of technology to improve the delivery of legal services, justice systems, and the law itself. Each category presents an unprecedented opportunity to use significant technological advancements to preserve and expand the rule of law.
The deployment of AI raises many interesting questions about the application of existing law and regulation. AI also presents an opportunity to improve our existing approaches to fundamental principles of justice, including the ways that we approach fairness, accountability, and transparency. Computational technologies offer the distinctive capability to embed law, regulations, respect for human rights, and democratic principles directly into processes, products, systems, and platforms by design and default. Equipped with this knowledge, our mission ought to be to use law and regulation to guide the development, deployment, and maintenance of AI toward improving society, without unnecessarily impeding innovation.
Technology has also demonstrated the potential to revolutionize legal-services delivery, thus improving access to law and legal services for everyone. In the United States, estimates are that more than 80% of the impoverished, and more than 50% of the middle class, lack access to legal services, according to findings from the [Legal Services Corporation](https://www.lsc.gov/what-legal-aid/unmet-need-legal-aid) and cited in [Access to Information, Technology, and Justice: A Critical Intersection](https://books.google.com/books?id=MF8nDwAAQBAJ&pg=PA4&lpg=PA4#v=onepage&q&f=false). Even the legal needs businesses can go unmet. Computational technologies hold great promise to automate the delivery of various legal services for this wide spectrum of recipients. For basic legal needs, access to legal services might come in the form of smartphones or other devices that are capable of providing users with an inventory of their legal rights and obligations, as well as providing insights and solutions to common legal problems. Better yet, AI and pattern matching technologies can help catalyze the development of proactive approaches to identify potential legal problems and prevent them from arising, or at least mitigate their risk.
As legal technologies advance, savvy lawyers will use them to augment their services. Innovative lawyers will embrace emerging technologies as a way to replace low value, repetitive tasks with increased efficiency, reduced costs, and greater value for their clients. By doing so, lawyers can also aim to play increasingly important roles as part of interdisciplinary teams that focus on solving some of society’s most “wicked problems.” One obvious area in which lawyers can begin to demonstrate this value is through updating laws, regulations, and governance frameworks for new technologies and our rapidly emerging digital society.
But history shows that innovation in the delivery of legal services has been slow. The lack of innovation in legal-services delivery stems, at least in part, from regulations that prohibit lawyers from sharing fees with, and receiving investment from, anyone who is not a lawyer. The practical result of this is that lawyers and technologists rarely collaborate on legal services delivery projects.
But change is underway. Today’s sophisticated legal-services clients demand demonstrable efficiency, quality, and better outcomes. An increasing number of lawyers work strategically with allied professionals to improve processes, better manage projects, embrace data-driven methods, and leverage technology to improve legal services and systems. Basic technologies and AI are slowly making their way into the legal industry, from legal aid organizations and courts to large law firms, corporate legal departments, and governments. Recognizing the failure of the existing legal market to produce adequate access to legal services, jurisdictions such as the United Kingdom have loosened legal-services and lawyer regulation. Likewise, several U.S. states, including California, Utah, and Arizona, have undertaken regulatory reform efforts.
We risk squandering abundant opportunities to improve society with computational technologies if we fail to proactively create frameworks to embed ethics, regulation, and law into our processes by design and default. Law, regulation, and ethical principles must be front and center at every stage, from problem definition, design, data collection, and data cleaning, to training, deploying, monitoring, and maintaining products, platforms, and systems.
In a fast-moving, digital world, law must exist closer to the action. Does a world in which “code is law” require law written in code? We shortchange our future when we fail to envision the possibilities. We must establish audacious goals and commit to overcoming the obstacles to achieve them.
To move forward, technologists and lawyers must radically expand current notions of interdisciplinary collaboration. Lawyers must learn about technology, and technologists must learn about the law. They must work together to develop a shared vocabulary. Multidisciplinary teams with a shared commitment to law, regulation, and ethics can begin to proactively address today’s AI challenges, and advance our collaborative problem-solving capabilities to address tomorrow’s increasingly complex problems. Lawyers and technologists must work together to create a better future for everyone.
### References
Michael Genesereth, Computational Law: The Cop in the Backseat, http://complaw.stanford.edu/readings/complaw.pdf
Gillian K. Hadfield, Rules for a Flat World: Why Humans Invented Law and How to Reinvent It for a Complex Global Economy (Oxford: Oxford University Press, 2017), https://books.google.com/books?id=TBYBDQAAQBAJ
Mireille Hildebrandt, Law As Computation in the Era of Artificial Legal Intelligence. Speaking Law to the Power of Statistics (June 7, 2017). Available at SSRN: https://ssrn.com/abstract=2983045
David Howarth, Law as Engineering: Thinking About What Lawyers Do (Edward Elgar Pub, 2014), https://books.google.com/books?id=_ALxHBwgW_QC
Lawrence Lessig, Code Is Law: On Liberty in Cyberspace, Harvard Magazine (January 1, 2000), https://harvardmagazine.com/2000/01/code-is-law-html
John O. McGinnis & Russell G. Pearce, The Great Disruption: How Machine Intelligence Will Transform the Role of Lawyers in the Delivery of Legal Services (May 13, 2014), 82 Fordham Law Review 3041 (2014) Available at SSRN: https://ssrn.com/abstract=2436937
George Siedel and Helena Haapio, Proactive Law for Managers: A Hidden Source of Competitive Advantage, (Routledge, 2011), https://books.google.com/books?id=fHFMuNfgj8QC
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# Reflexive Mutual Series - LLC (RMS-LLC)
Zero Carbon, Resilience, Affordability, and Evolvability through Generative Design and Autocatalysis
### From Inanimate to Animate Mechanisms for Autonomous Value Generation and Retention
The Industrial Revolution and Capitalism were remarkable in reducing poverty and transforming mankind’s relationship to Nature. However, the success of the extractive machines of industrialization transformed Nature from an adversary to be conquered to ally that must be cultivated.
We have discovered that we are of Nature, and that its diminishment is our diminishment. We understand that the extinction of its creatures—from biomes to mega fauna—presages our own extinction. We simply cannot continue to fuel the addictions of consumption and acquisition without literally destroying ourselves. For the addicted capitalist, such curtailment might be seen as a deprivation. Instead it is a liberation: a transition from addiction to generation, and from the inanimate to the animate.
Immediately, we will need to build social and economic forms of organization to be of Nature rather than over Nature. We need to transition from our current forms of social and economic ordering, derived from 17th century physics and mechanical principles, to those based on 21st century biological and generative principles.
Nature made this transition nearly 3.5 billion years ago, and in the course of that time, generated complex expressions of diverse and interdependent forms of life. Our engineering of complex systems, biology, and generative design are approaching the point where we can also make the transition from inanimate to animate forms of organization. There is a confluence of technological and scientific advancements making this feasible: self-organizing, self-deploying, self-healing networks, and IOT; crypto-tokens and blockchain, autonomous organizations and contracts; machine learning; synthetic biology; decentralized fintech, virtualization, and “digital twins.”
The ability of these technologies to regulate certain behaviors within a system through their architecture (e.g., their code), has opened up new possibilities for the ways that people collaborate and work together. Evidence of this change can be seen in the shift toward decentralized, agile, and evolving infrastructures across all sectors of society — from energy, transportation, finance, health and food to communication, architecture, and manufacturing. This is the benefit of computational law -- instead of law inhibiting innovation, the combined knowledge of law and technology can be used to create new forms of organizations and produce new forms of value that are based on data and code.
These new forms of organization cannot be shoehorned into the antiquated vessels of industrial capitalism, or into the governance structures of classic industrial democracies. They will require new legal, operational, economic and financial frameworks, and the RMS-LLC represents an initial attempt at providing such a holistic and animated approach to the organization of firms and finance
### Legacy of Free Market Capitalism
All ideas are creatures of their time. They are the offspring of the many intellectual and technological liaisons of their era; some of which were immediately seen as legitimate, and others of uncertain parentage. However, all necessary and transformative ideas in time, gain societal acceptance.
Market capitalism is such a child. In its inception, it was shunned as a blasphemous affront to the moral authority of the King and Church. Yet as both authorities began to waver and wane under the onslaught of fresh ideas and technologies, new principles of social and commercial organization emerged. These were imbued with the science and technologies of their time: the physics and calculus of Newton, and the pragmatic genius of Adam Smith in giving “natural explanations” to the commercial affairs of men and nations. Instead of the visible hand of King and Deity ordering commercial affairs, Adam Smith invoked a new authority: the “invisible hand” of the market. The reigning metaphors, then as now, are mechanical, borrowing from the pervasive and transformative technologies of steam and coal, to power mills and the massive engines of industrialization.
These transformations occurred nearly three hundred years ago. Science, technology, social and economic circumstances, as well as ecological challenges, are thoroughly different today. The science of the biological and behavioral basis of Human Nature has progressed dramatically, as have digital and computational technologies for energy, fabrication, transport, food, learning, communications, and control. And most pointedly, as a species, we are in entirely different circumstances - confronted by ecological and existential challenges entirely of our own making that must be addressed in relatively short order in order to avoid a cliff of ecological and societal catastrophe.
### From Price to Value, Nature by Design
The defining mechanism for free market capitalism is price. It is this sole signal that directs economic behavior and acts as the lever of economic incentives. Price encourages full fungibility, and in doing so, rewards those who ruthlessly recognize and exploit arbitrage opportunities across asset types and all social circumstances. It is a winner-take-all, zero-sum game that favors scale and oligopoly, rewards expeditious exits and externalizes risk and cost. As a repeating game, it pits player against player and leaves to the discretion of the winner the option of redressing social or ecological costs and imbalances. Absent the willingness of a winner to redress such costs, it falls upon a “third party” - the government - to redress the inequities or costs. Yet in so many cases, the surpluses of the winner are used to “capture” such third parties and enlist them to their own interests.
Harms at an ecological or global scale have no effective, post hoc mechanism of redress. There is no entity of sufficient scale, force, or jurisdiction to redress such costs and imbalances. In broaching this obstacle, we must design the values of ecological resilience and social equity into the very fabric and “fitness functions” of the instruments of capital creation, aggregation and distribution itself. So, in effect, no external party can exist that owns and potentially “exits” the “market,” but rather the firm or “organism” itself is a self-contained entity that solely owns itself, and captures the value generated. This is what living organisms do; with their own metabolism of energy conversion, production and retention, living organisms convert raw external forms of energy into internal fuel through chemical reactions to enable a wide range of adaptations within the confines of their own homeostasis. The next phase of capitalism must accomplish this same task.
If there is to be a rapid transition to a global social and economic ordering that is designed *ad initio* to be z-carbon, resilient, and equitable, then a legal form of socio-economic organization and associated investment vehicles must also emerge.
The rapidly evolving decentralization, tokenization, certification, virtualization, and *autonomization* of finance can provide the necessary technological infrastructures and platforms to accomplish this reframing. The challenge is to create the interim bridging mechanisms, institutions, and incentives that enable the transition at sufficient speed without calamitous side effects. Hence, the endeavor here is to create a new form of corporate organization that leverages existing corporate, legal, and capital structures, but at the same time, by design, makes use of biological and ecological principles of organization and evolution. This venture requires an appreciation of the difference between markets and niches.
### Alternative - Non-Correlated Asset Classes
A key factor in accelerating the transition to a z-carbon and equitable economy is the independent certification of asset classes and negative correlation with fossil fuel associated asset classes. By creating a broad market signal that verifiably identifies asset classes that are negatively correlated with fossil based industries and assets, investors gain the financially credible option for divesting themselves of fossil based assets and allocating portions of their portfolios to z-carbon and equitable asset classes.
The independent algorithmic certification of asset attributes and behaviors are rapidly maturing in blockchain applications for logistics, supply chain, renewable energy, and trading. These initiatives will pave the path toward z-carbon asset allocation options. As rating agencies, regulators, and insurance underwriters insist upon full environmental impact and risk accounting, the opportunity to direct investments into certifiably proven negatively correlated asset classes will represent a significant investment diversification and hedging opportunity for institutional investors.
### Purpose: Mutualistic Compounding VAlue Generation and Retention
The designed and encoded purpose of a RMS-LLC is to act in the best interest of all its members to generate goods, services and assets, that singly, or in combination, achieve stable and measurable value exchange within a member network furthering mutually agreed upon outcomes. In contrast to a C corporation or an LLC, which acquire investment capital to maximize shareholder value to achieve market liquidity, the RMS-LLC strives to *reflexively* generate value through internal liquidity and value generation within a mutual organization. The mutual organization defines the measurable outcomes it wants to achieve for different assets and services with respect to carbon emissions, affordability, equity, and resilience. RMS-LLCs can differ widely in their selection of assets and services, rights and permissions of members and non members, as well as outcome priorities.
To raise external capital the RMS-LLC sells *appreciation rights* to single asset classes - such as energy, housing, 5G, food, and mobility - for a market competitive rate of return, with an option to buy out such investors with a premium at the RMS-LLC’s discretion. The RMS-LLC internally invests such capital in *combinations* of asset classes, such as “housing, energy and mobility” on a cost plus basis, which in turn, yields higher rates of return, reduces cost and time reduction, and complements value creation.
Members of the RMS-LLC purchase *access rights* over time to different asset classes and services for a fixed price, which when fully vested, gives members perpetual access to such assets and services. Members can sell such rights to other members, borrow against them to invest in other asset classes and services, or upgrade to other asset/service types. As the RMS-LLC achieves ownership of more and more diverse assets, it is able to collateralize a “reserve” basket of asset “tokens” and thereby, reduce the cost of capital and internally finance its acquisition of new assets. With the increasing value of its reserve tokens, members are able to build financial equity and resilience over time, and at the same time increase appeal to “outside appreciation” investors. By increasing its reserves and precisely calculating member credit risks, the RMS-LLC reduces counter party risks and hence cost of capital.
Over time, it is anticipated that the value of the RMS-LLC’s reserve token will sufficiently appreciate in value and demonstrate stability and liquidity that outside investors will choose not to liquidate their appreciation rights tokens into fiat currencies, but instead convert into RMS-LLC tokens. These tokens can be thought of as a more stable and secure form of preferred stock, or a kind of debt with subordination rights designed to encourage the conversion of fiat into the tokens of the RMS-LLC.
By reflexively controlling the fungibility and flow of asset denominated tokens within its value exchange network, the RMS-LLC is able to capture, retain and leverage mutualistic value generation. This is unlike any standard C Corporation or LLC whose value is captured and controlled by major preferential share holders whose intent is exit and liquidation. It is also in contrast to a Benefit Corporation, a portion of whose profits are allocated to a designated social purpose. The RMS-LLC in *generatively designed* from the beginning as a *self-contained entity* to generate and retain value around its value proposition which is realized not through an exit or liquidation but through progressive participation.
### Computational Techniques
There are a variety of ways to approach the computational implementation of an RMS-LLC. The foremost consideration is representing its output or boundary condition, or in classic cybernetic terms, its “essential variables”. In all senses, an RMS-LLC is defined by a set of multidimensional constraints on its boundary or identity conditions. This teleological metric could be an “objective function” to be solved as in a case of evolutionary game theory, or it could be a Genetic Algorithm whose “fitness function’ selects for a set of attributes over successive generations of outcomes. It can also be thought of as a governance or control function, similar to those used in Monetary Policy for regulating Special Drawing Rights (SDRs) between the credit-debit accounts of different nations, or in the case of an RMS-LLC, asset types. Another candidate is the concept of “Spatial Contracts,” proposed by Verses (2019) and their Hyperspace Transaction Protocol. (HSPT). In all cases, the processes will be driven and regulated by machine learning and will entail a level of autonomy in the execution of smart contracts and the oversight of its processes. In some segments of the population, this allocation of oversight to a machine is seen as abhorrent (Zuboff, 2019) and an abdication of human responsibility. But the horse has left the barn long, long ago as autonomous aircraft, IOT, and automobiles are increasingly an everyday reality. There are well established processes for verifying processes and code that can and should be adopted and upgraded without having to involve humans. In many cases, inserting humans into the process introduces a security risk that itself has to be accounted for and defended against. One of the most challenging aspects of RMS-LLC design will be how to properly engage human oversight without introducing collusion and self-dealing. There are promising solutions to the “who guards the guards” problem which entails a combination of randomization and certification techniques for selection, participation and succession. Nevertheless, these solutions are in their infancy.
Another candidate technology are Non Fungible Tokens (NFTs). While much as been written about blockchain and smart contracts, the potential importance of NFTs has been overlooked, except for their use in the gaming world. As unique certifications of the proof of an attribute, permission or a right, NFTs could play an important role in the design of RMS-LLCs. Rather than sharing data or having fixed certifications, NFTs can leverage smart contracts that are linked to containers with set conditions, permissions, and limitations to define access rights in a highly dynamic and open manner. (Clippinger,2019)
### Member Rights and Capital/Token Structure
The RMS-LLC in many respects mimics traditional startup capital formation and liquidation. The principle distinction derives from the RMS-LLC’s incentives and controls being designed and exercised to the benefit of value creation and retention for the *entire* mutual organization and not the external investors. The goal is *not* the exit for either the participating members or the investing/appreciating members, but rather to build up the value, diversity, resilience and purchasing power of the mutual organization network and to attract and retain outside capital. The goal is to be marginally and competitively superior to other market investments, and provide greater resilience and appreciation over time, as well as the benefits of becoming a member participant. In this respect, the capital structure is similar to a venture capital-start up relationship, but “turned on its head” to be designed from the interest of the mutual organization rather than outside investors. Naturally, this power equation will depend upon the actual and perceived success of the RMS-LLC to other outside investors.
For each asset class that a RMS-LLC purchases and uses, a security token can be issued and backed by an NFT and the value assessment of the real cost of the asset plus a percentage markup. A participating member purchases “access rights” to that asset which are vested over time with a payment schedule, similar to a car loan or mortgage. In the case of a default, the asset is recovered by the RMS-LLC reserve fund.
For each asset class, appreciation rights tokens may be sold to external investors with a market competitive financial instrument (e.g., debt, equity, or convertible note). The purchase price to the external investor is at cost plus a percentage markup, depending upon market response. The appreciation investor has a fixed period to receive dividends, with a payback of principle with a coupon. Shadow pricing market mechanisms and exchanges are subsequently able to price the token asset value and provide for phased liquidity. The RMS-LLC would have the right to pay off a note or repurchase equity if certain “trigger liquidity” events occurred, such as a rapid appreciation to the point of payout of principal and coupon. In this way, the RMS-LLC would be able to capture the further appreciation value in its reserve tokens.
### Earned Securities and Tokens
Members should be able to earn tokens in exchange for work that they created as determined by the community to be of value. These tokens could be used to pay down loans for assets or purchase in network services such as mobility, food, housing, and energy.
### The Complexity and Biological Argument and Architecture for Compounding Returns
To anyone steeped in traditional financial and economic doctrine, the notion of a firm or mutual organization being able to generate compounding value and effectively, and autonomously, grow itself might seem fanciful. Similarly, the notion that any entity or network of entities could do so without incurring debt or inflating the value of a currency might also seem borderline preposterous.
Yet that is what living, animate things do—in contrast to dead or mechanical things. Mechanical things require and consume outside energy, be it fuel or capital and do not themselves internally generate food nor energy. When they run out of capital, mechanical entities require an “injection” of capital by a third party at a price that warrants the risk associated with the return of the investment of the capital to the third party. The value of the investment totally rests upon it being liquid to the investor - not to the value generated and retained within the entity. There is nothing autonomous nor animate about it. The mechanical entity’s very existence depends upon what can be achieved by the third party which is exogenous to the entity. The mechanical entity’s survival rests upon how well it succeeds or fails in wholly fungible equity exchanges that aggregate and equate different kinds of investment value. The life cycle of the mechanical entity really is a creature of the exchange and is not in control its own fate. As such, it is not free to take full and autonomous advantage of the different ways it can internally generate self-sustaining value like all living things and ecosystems.
### Autocatalytic Sets and Animate Organizations - Economies and Tokens
Our guiding principle in developing animate or self-organizing organizations and economies is understanding that one can abstract out from the biology of the living organisms the core philosophy of self-organization. In other words, there are principles of adaptation, organization, and replication which are independent of chemistry and can be given a formal representation. This is a well traveled field over the last 50 years, beginning with Ross Ashby’s first representation of a “self-organizing system” in 1945, to John Von Neumann (1951) , Norbert Weiner (1956), Gregory Bateson, (1972) to more recently, John Holland (1970, 1975, 1999, 2015), Thomas Schelling (1978), and Stephan Wolfram (2001). More recently, scholarly work has built upon the rapid breakthroughs in genetics, bioinformatics, epigenetics, and systemic biology, including Robert E. Ulanowicz (2009), Brian Arthur (2009), Robert Rosen (2000), Andreas Wagner (2014), and Neil Gershenfeld, et. al. (2018). (It should be noted that there are many other noteworthy contributors and apologies for any egregious omissions.)
Of particular relevance to the approach being taken here, however, is the work of Stuart Kauffman (1990, 2000, 2018) a biologist, MD, and complexity scientist who, over the course of his long career, has been actively trying to model the processes involved in the spontaneous transition from inanimate matter to living organisms. In his most recent book, “A World Beyond Physics” (2018), Kaufman provides a convincing model that, to this author, is especially amenable to modeling the manner in which different incentives (tokens) and asset classes can be combined to generate a form of social and economic autocatalysis and autonomy.
The primary thesis of the animate organization is *not* of analogue or metaphor. It is not that firms can be designed “like” Nature or autocatalysis—but rather that they can be designed by and performed with *identical* principles. This is too strong an assertion to be supported in this paper, but it is important to set a marker of this strength for future considerations. That said, even though the mapping between Kauffman’s model of autocatalysis into an animate human organization enables some algorithmic and self-organizing behaviors, it is imperfect and has room to grow and improve. Nonetheless, the argument will be made that in comparison with the current organizational, economic, and financial models, the RMS-LLC can be designed to generate novel forms of value and succeed in out competing traditional firms and business models. We are arguing for the preliminary transition from inanimate to animate, the formation of the self-replicating and bounded “proto-cell,” not yet the full cell nor the multicellular organism.
### Encapsulation and Autocatalysis by Design: Extern Capital and Tokens as Raw Energy and Tokens as Refined Energy
The oft-repeated requirement for the ignition, evolution, replication and perpetuation of life is the formation of a boundary. This membrane allows self-organizing systems to establish their “self.” It is by regulating what is inside versus outside the membrane of the cell that defines its identity and what value or values are to be replicated. In the case of the RMS-LLC, it is the collection of certain assets—energy, food, mobility—that are within the defined values that the entity determines—zero carbon, resiliency, affordability. It is also the interactions or “reactions” among the assets or “molecules” that generate new forms of energy and in combination lead to less energy consumption, more efficient energy generation and value generation, as measured by the outcomes that define the mutual organization. These reactions can be defined by contracts that establish the behaviors and character of different asset types. For example, the production of solar energy can be defined through a formula based on: cost per kilowatt hour, storage costs, activation costs, maintenance costs, distribution costs, utilization costs, carbon footprint, lifecycle costs, and production verification. Note that these costs are not due to solar energy technology alone, but depend upon related technologies or “molecules” such as batteries, inverters, IOT devices, machine learning optimization, and overall patterns of miniaturization that affect the cost performance of computing, storage and transmission. Such variables affect the overall per kilowatt cost of energy. Similarly, the ability to achieve scale economies and performance in seemingly unrelated technologies (e.g. machine vision) may dramatically affect the performance and cost and demand for solar and autonomous vehicle technologies. Developments in adjacent technologies can therefore affect the affordability and suitability of housing technologies in terms of proximity to certain kinds of resources such as schools, healthcare, and food, as well in the cost of housing construction and utilization of space and resources.
### Generative Design: Catalytic Reactions and Phase Shifts
In contrast to established democratic principles based on means (such as voting, trial by jury, and elected representatives), generative design principles are based on outcomes. The goal is to achieve and avoid certain outcomes, not presuppose that certain means, such as “equal participation,” or certain materials, will lead to desired outcomes. A prevalent theme in the complexity sciences is the notion of “emergent order” arising from complexity. Given certain initial conditions and sufficient iterations, complex forms of ordering can emerge, resulting in complex life forms such as ourselves. Importantly, the goal is not that *a* form of complexity should emerge, but that *many* different kinds of complexity emerge, each with its own boundaries, conditions, reactions, and products. In other words, each animate form evolves its own method of energy production, which in the case of RMS-LLCs, we represent as different types of tokens and their related “smart contracts”.
Neil Gershenfeld, a physicist and computer scientist, and the founder of the global Fab Lab network, describes complexity as “a sequence of detecting and correcting errors in the assembly of a small set of discrete designs being represented as developmental programs rather than construction plans (Hox genes).” He also defines “Declaration design” as “the name for a design process that lets you describe what you want something to do, but not how it should do it.” (115, 2017).
Stuart Kaufman makes a similar point about what constitutes “life” from the perspective of a computational molecular biologist. Kaufman concludes: “Life is a fundamentally new linking of non-equilibrium processes and boundary conditions constraints on the release of energy into a few degrees of freedom that thus is thermodynamic work. But stunningly, the work done can construct constraints on the release of energy in further non-equilibrium processes. In reproducing systems such as cells a closure is achieved linking these processes and constraint construction in an organization that closes in on itself. The system in doing its work constructs its own constraints, and also reproduces, achieving catalytic task closure. (2019, 53)
Through the combination of different asset types (energy, housing, IOT), an RMS-LLC generates new forms of value, attains its defined outcome or constraint conditions in a self-replicating manner, and discovers more efficient (hence competitive and fit) means for achieving the outcomes that give definition to the RMS-LLC.
Another purely formal property that Kaufman cites gives credibility to the notion that new forms of fitness and organization can be discovered simply through crossing a complexity threshold by increasing the number of connections in a graph. Citing the work of Paul Erdos and Alfred Renyi (1959) on random graphs, Kaufman shows that when the number of edges (lines) in a graph of vertices (V) exceed the ratio of E/V=0.5 “suddenly a large collected cluster or “giant component” forms with a diversity of cycles. As E/V increases further, remaining isolated nodes become tied into the giant component.” (2019, 41)
This phase shift in organization creates new types of categories of “polybrids” or “complex molecule” forms of assets. One can imagine a kind of robotic building that uses new materials, AI, IOT, and sensors to provide adaptive spaces that change according to time, circumstance, energy, use, and occupant. (The new startup, Ori Systems, expresses seeds of this idea). Similarly, the cluster of machine vision, sensors, solar energy, battery tech, geodata, and electric vehicles can result in a “giant component” which completely transforms the spatial layout of cities, their carbon footprint and affordability. These combinations are generated and selected for by virtue of the “declarative design” of the RMS-LLC.
At this early phase of exploration and development, testing of an RMS-LLC will require “hand testing,” managed intervention, and evolution. However, during a more mature phase, the entire process would be governed by the type of genetic algorithms first developed by John Holland in 1960, but subsequently modified and available in a number of code libraries and versions
### Shadow Pricing Arbitrage, Repayment Triggers, and Reflexive Investment
The RMS-LLC lives in a highly competitive and hostile world in which it must compete for capital against more traditional firms and business models. If it cannot achieve more competitive value for investment capital and if it cannot achieve outcomes that matter to outside investors, it will perish. The essential premise is that a living, animate organization, by virtue of declarative design and appropriate incentive structures, can more rapidly discover and realize innovative value generation than the mechanical business models of traditional firms.
This argument is supported by the deflationary effect of rapid technological innovations such as Moore’s Law and Dennard’s Scaling Law upon the cost versus performance versus size of digitally dependent components and processes. For example, a resource such as electricity that might cost $10 at time t will cost $2.5 after two years and after four years, will cost roughly $0.70. Through generational innovation, costs decline so rapidly that a price arbitrage opportunity emerges to repay contracts over a five year period. Currently equity and bond markets do not properly price the appreciation value of certain “exponential assets” over time. Hence, a trigger point exists at which it makes more sense for a party to buy out their contract, pay back their loan to own the asset, and use the savings to nullify the debt. This strategy is applicable to the deflationary effects of single assets, such as electricity, which the traditional market prices individually. However, if our argument for the generative value of new combinations and forms of combined asset classes is correct, then the relative savings and value will be all the greater.
Therefore, it makes sense to have exogenous market shadow prices for internal assets and tokens. When the spread between the RMS-LLC cost and the external market price is sufficiently great, the RMS-LLC can buy out its contract with the projected savings and exercise its right to buy out or pay off a contract. An RMS-LLC is in effect an “innovation engine” by declarative generative design which rapidly iterates and reflexively reinvests in itself, reduces costs and impediments, and achieves its self-identified mission.
We see similar mechanisms attempted through traditional corporate, forms where companies like Amazon, Google, and Tesla assume debt or forgo profits and dividends to reinvest in themselves for successive generations of innovation. The old measure of price to earnings ratios and quarterly dividend calls work against the interests of the firm and inhibit its ability to innovate. This would not occur in the RMS-LLC.
### Equity Appreciation, Phased Evolution, and Recycled Waste
If the RMS-LLC is successful in competing for fiat dollars and demonstrating its capacity to provide external financial returns at competitive rates, then it should become a magnet for additional capital. Institutional capital will be drawn to the RMS-LLC as a lower risk and higher return asset class which has measurable impacts on socially and economically valued outcomes. Under this scenario, the reserve asset tokens of the RMS-LLC would become highly valued over time and seen as a safe asset class that minimizes counter party risk and preserves purchasing power. The assets would be liquid, allowing combinations of assets that generate value for those members of the network. It becomes, in effect, its own shadow economy.
As noted previously, and in contrast to more traditional organizational forms, the RMS-LLC is designed to rapidly evolve through stages of innovation and asset acquisition. Most large enterprises are faced with Clay Christensen’s “Innovator’s Dilemma”: how to innovate without destroying the current business? As mechanical systems are often optimized and standardized around a particular sector, technology or asset class, they are extremely vulnerable to technological disruption and often become prey to the larger platform companies. These mechanical entities can attempt acquisitions and mergers, but often the expected synergies do not materialize.
As a hyper-innovative entity, the RMS-LLC goes through many product service generational changes and, therefore, has the potential to generate an enormous amount of waste. One needs only to think of the rapid depreciation of computer storage components, screens, and mobile phones to appreciate that a crucial outcome condition for a RMS-LLC is to generate waste that is an energy source for other future animated entities. In other words, depleted components of product life cycles must have value for other forms of organization. Hence, both organismic and ecological constraints are necessary. Components should be designed to be readily broken down into base components that can be recombined in new forms of catalysis. Here, we can take an example from Nature, a system creative in repurposing its base components.
### Diagram 1
This diagram illustrates the essential conditions and processes that constitute a RMS-LLC. The border, called the “Value Boundary,” is like the membrane of a cell, which in this case is defined by the outcomes of Z-carbon, Affordability and Equity. The RMS-LLC is in this example a Node in a network of RMS-LLCs that takes outside raw energy (fiat currency) and converts it into different kinds of token related asset classes whose character and liquidity is controlled by the “smart contracts” of the banking component. The overall issuance, convertibility and liquidity of the different asset classes is controlled by the Micro-Monetary Component which acts to attain the overall outcomes of the Value Boundary. Over time, through repayment of fiat investments and loans, a reserve token pool is built up which is backed by the collateral of tangible and marketable assets. The role of the Floating Exchange is to have an index value for liquidation to investors. The Compound Asset Group represents the additional value generated through the combination of different asset classes.
### Governance Council
The RMS-LLC will be governed by a Governance Council (GC) of members representing the different asset classes and participating members in a manner similar to the way a mutual organization for insurance, investment, purchasing, credit, ownership, land and real estate. This council will set the goals and outcomes for the overall RMS-LLC on a quarterly basis and determine “micro-monetary policy” for the issuing, fungibility, and supply of different asset/token types. It is the duty of the GC to ensure privacy, security and opportunity for value preservation and generation, as well as access to the assets and services provided by the RMS-LLC exchange network, and to minimize operational costs. It also has the duty to provide oversight for the Management Unit (see below), hire and fire its officers, and contract with third party services through routine Service Level Agreements (SLAs) for the management and execution of its policies.
### Voting and Selection of Governance Council Members
The Governance Council will be formed through a process whereby members establish their “standing” as determined by their ownership of different asset tokens and their reputation or expertise in relevant areas. It is intended that a pool of candidates with the requisite standing and reputation would compete in a democratic election. It is also expected that a certain portion of the council would be *randomly* selected from a pool of candidates. Council members would be compensated for their work in tokens and be subject to term limits. There would be an Executive Chairman, Financial & Monetary Chairman and an Operations Office. These could be rotating positions to ensure accountability and shared understanding.
### Management Unit
The objective is to staff a highly trained management team that is effective in executing the policies of the council. A CEO would have principal contact with the Governance Council and a Community Officer would maintain ties to the overall community. A CTO, CFO and Chief Monetary Officer would analyze and model token flows, asset values, liquidation, and exchanges. Vanguard Mutual Funds, a $6.5 trillion mutual organization owned by its funds and shareholders, works on a similar set of principles. It is given a considerable latitude as long as it realizes its investment objectives.
### Operating Agreement
The operating intent of the RMS-LLC is to attain resilient value generation outcomes to the mutual benefit of its members. In order for this to be achieved, the following rules and operations need to be put into practice. The first order of operations is to form a provisional Governance Council (GC) which in turn, forms and contracts with a Management Unit.
As a duty of the GC is to minimize costs and preserve value, it will create a basket of reserve assets collateralized by tangible assets to reduce reserve and equity requirements for the RMS-LLC.
The GC will also set and oversee policies that achieve the definitional outcomes for the RMS-LLC, and thereby form, oversee, and contract with the Management Unit to achieve results as cost effectively as practically possible. Whenever possible, contracted processes, rules would be algorithmic, secure and auditable by an independent third party. The intent is to reduce costs and increase revenues through the use of service templates and API services.
The organizational structures of the GC and Management Unit are proposed as follows:
1. Formation of a Provisional Governance Council: Minimum of 3 members with the election of a full council one year upon full financing of initial project.
2. Formation of Provisional Management Unit. Contract for services for an initial Management Unit with sufficient staff to execute performance contract as agreed to by the Governance Council. With completion of project financing, full SLA with Management Unit either with third party or retained management and staff.
The recurring duties on a project by project basis of the Governance Council in concert with the Management Unit are:
1. Identify target populations: location, member criteria, people and entities.
2. Identity outcome priorities: carbon reduction, affordability levels, equity and others.
3. Identify asset classes, attributes, and behaviors.
4. Identify relationships: flows and *spatial* contracts between asset classes.
5. Identity cost methods for different asset classes.
6. Set Access Rights: proportions, terms and conditions for different assets for participating members.
7. Set Appreciation Rights: instruments, terms, and conditions for investors of specific asset classes.
8. Model cash flows and payments streams for asset class and token circulation, fungibility and liquidation.
9. Develop Pro Forma Model for Project Financing of Assets for access and appreciation.
10. Construct Token Governance Policy (Model) for Project.
11. Identify and contract with potential service providers, partners and developers.
12. List Project and financing instruments on platform.
13. Execute the initial project and timely pay off debt and repurchase equity and assets for appreciation rights investors.
14. Issue asset reserve tokens for project asset classes.
15. Identify new asset classes and combinations for purchase to extend the diversity and liquidity of services for members.
16. Identify activities and behaviors for which participating members can earn tokens, convertible into additional services and reserve tokens.
17. Identify other RMS-LLCs to achieve interoperable services and token exchanges.
## Conclusion
The firm is the atom of capitalism. It is the principle unit, the corpus, that is imbued with all the legal and financial means to mitigate risk, assign rights and duties, structure incentives, and aggregate and distribute proceeds to its owners and operators. In its current form, the firm is an artefact of the Mercantile and Industrial eras. It is a conceptual “body” whose personhood is conceived in mechanical terms, and which is operated solely for the benefit of its owners, regardless of its impact on its workers, community, or environment. When it fails to extract value, or its owners want to realize it value through more fungible means, its parts – shares – are traded on an exchange. When its shares fail to have sufficient value to its owners – regardless of the impact on others or its environment, it is dissolved and sold for its break up value. Such an arrangement is “free” only for its owners, not those stakeholders, human and ecological, from which the value has been extracted. The environmental and human cost of this wanton strip mining of social and ecological resources is no longer tenable. Our conclusion has been acknowledged by some of capitalism’s most successful players: Ray Dalio of Bridgewater, Marc Benioff of SalesForce, as well as some of its Central Bankers, such as Mark Carney, Governor of the Bank of England. As financial markets start to fully price the social and environmental costs of fires, floods, species extinction, climate change, and desertification, the impetus for change will be realized. Carbon based energy, manufacturing, and transportation-based assets will be deemphasized in favor of those assets and forms of economic and social organization that are inherently Generative: zero-carbon, affordability, equity and resilience.
The notion of a Reflexive Mutual Series Limited Liability Company is proposed here as a means of organizing capital, people and assets to intrinsically address the defining existential challenges of our time. It is based upon time tested principles of cooperation and mutualism, as well as the New Sciences of complexity: synthetic and evolutionary biology, ecology, as well as the technologies of cryptography, decentralized computation, machine learning, tokenization, AR, smart contracts, blockchain, IOT and 5G. In this respect, the harmonization of legal requirements, new technologies, and generative design principles represents the future computational law offers. We now have a real prospect to engineer social, economic and financial institutions based upon scientific principles, evidence, and realized successive generations of technologies focused on humane and ecological principles. We have no other choice.
## Bibliography
1. Arthur, Brian, Complexity and The Economy, Oxford, 2014
2. Arthur, Brian The Nature of Technology: What It is and How it Evolves: Free Press, 2009
3. Ashby, W. Ross, *Design for a Brain*, Chapman & Hall. 1952
4. Ashby, W. Ross, *An Introduction to Cybernetics*, Chapman & Hall. 1956
5. Bateson, Gregory, Steps to An Ecology of Mind, University of Chicago Press, 1972
6. Beinhocker, Eric, The Origin of Wealth, Random House, 2006
7. Clippinger, John, H, A Crowd of One, The Future of Digital Identity, Public Affairs, 1998
8. Clippinger, J, Bollier, David, (eds) From Bitcoin to Burning Man and Beyond; The Quest for Identity and Autonomy in A Digital Society, 2014
9. Clippinger, John H., Tokens of Truth and Title: Saving the Internet From Itself, Medium, April, 2019
10. Erdos, P, and Renyi, Alain,. "On Random Graphs. I" (PDF). *Publicationes Mathematicae*. 6: 290–297, 1959
11. Gersenfeld, N, et. al., Designing Reality, Basic Books, 2017
12. Holland, John, Adaptation in Natural and Artificial Systems (1975, MIT Press)
13. Holland, John, Hidden Order: How Adaptation Builds Complexity (1995, Basic Books)
14. Holland, John Emergence: From Chaos to Order (1998, Basic Books)
15. Holland, John, Signals and Boundaries: Building Blocks for Complex Adaptive Systems (2012, MIT Press)
16. Kauffman, Stuart (1993). The Origins of Order: Self Organization and Selection in Evolution. Oxford University Press.
17. Kauffman, Stuart (1995). At Home in the Universe: The Search for Laws of Self-Organization and Complexity. Oxford University Press
18. Kauffman, Stuart (2000). Investigations. Oxford University Press.
19. Kauffman, Stuart (2008). Reinventing the Sacred: A New View of Science, Reason, and Religion. Basic Books.
20. Kauffman, Stuart (2016). Humanity in a Creative Universe. Oxford University Press.
21. Kauffman, Stuart (2019). A World Beyond Physics. Oxford University Press.
22. Rene, Gabrel, Mapes, Dan, The Spatial Web, 2019
23. Rosen, Robert, Life Itself, Columbia University, 1991
24. Schelling, Thomas, MicroMotives and MacroBehaviors, Norton & Co. 2006
25. Von Neumann, John in 1966. *Theory of Self-Reproducing Automata*, Burks, A. W., ed., University of Illinois Press.
26. Ulanowicz, Robert, *A Third Window: Natural Life Beyond Newton and Darwin*, Templeton Foundation Press (2009)
27. Wagner, Andreas, *The Arrival of the Fittest: How Nature Innovates*. Penguin Random House. 2014
28. Wiener, Norbert, Cybernetics: Or Control and Communication in the Animal and the Machine. Paris, (Hermann & Cie) & Camb. Mass. (MIT Press)
29. Wolfram, Stephan, A New Kind of Science, Wolfram Media, 2002
30. Zuboff, Shoshana, The Age of Surveillance Capitalism, Public Affairs, 2019
----
# An Automated <!--// BLIP in MIT CLR’s //--> Formation
> *A Reflection on Legal Tech Incorporation Processes, Legal Education, and the Implications on the Legal Profession*
### INTRO//
### ORIGIN STORY//
[The MIT Computational Law Report (the “MIT CLR”)](law.MIT.edu) is a legal entity that was created more by metaphorical [Iron Man](https://en.wikipedia.org/wiki/Iron_Man) than by [C-3PO](https://en.wikipedia.org/wiki/C-3PO). It was created by a machine but also by a human, by computer-driven legal automation tools in the hands of law students.[1] Indeed, the best elements of both human and machine united to deliver a potent legal product. The process epitomized the concept of extending intelligence of both cognition and capability to produce more effective legal professionals.
The law students in [the Brooklyn Law Incubator & Policy (“BLIP”) Clinic](https://www.brooklaw.edu/academics/clinics%20and%20externships/in-house%20clinics/blip) were tasked with the MIT Computational Law Report’s business entity formation. Under the supervision of experienced, entrepreneurial attorneys, BLIP students have been setting up legal entities for twelve years. During this time, BLIP’s professorial leadership has largely held the belief that resorting to automation tools to draft legal documents would fail both students and clients alike; the presumption was that such tools would dull the developing legal professionals’ talents and intellects and that they would produce a substandard legal product. Accordingly, BLIP students were generally forbidden from using any tools that automated the drafting process, particularly if hidden behind paywalls. The exception was that students were encouraged to try to build their own automation tools, but students capable of building even the most rudimentary tools and apps were few and far between.[2] The prototypes that these students constructed were generally more proofs of concept that such tools and apps could be built, rather than constructed by those properly trained in computer programming and design.[3]
In 2011, BLIP faculty and students experienced their first wake up call on the road to inevitable human-computer collaboration. BLIP Clinic was approached by a couple of MIT engineers, calling themselves [Docracy](https://www.docracy.com/),[4] asking the Clinic to help them build and populate an online, open-source, crowdsourced, curated repository of contracts and other legal documents. The goal was to make legal documents freely available and customizable. At first, BLIP faculty and students fought against the creation of this sort of free and open repository but quickly realized that such platforms would be inevitable in the digital world, and it would be best for BLIP students, graduates, and faculty to embrace this inevitability and to learn to mutate the role of the lawyer in such a potentially societally-virtuous, human-empowering, automation-enabled digital world. As a result, BLIP students and graduates populated the Docracy site with its most robust and mutable set of documents.[5]
In any event, since 2011, the writing on the wall—or, rather, the screen—has become more and more apparent, and 2019 marked an ever-stronger pronouncement by BLIP leadership of the benefits of automated legal tools. Emphasis was placed on the utility of both their use and their development by law students. In addition, BLIP professors began experimenting with these tools as pedagogical devices and, to a greater extent, placed an emphasis on the inputs—the legal rationale that guides drafting—rather than the outputs—the largely formulaic prose of the legal provisions themselves. In doing so, the fundamental questions shifted away from “how do we create bylaws, operating agreements, etc.?” toward “why would we want to?” and “what should we be considering when we do?”
However, even a newfound appreciation for automated tools among BLIP’s forward-minded leadership could not forestall certain feelings of foreboding for the students actually tasked with carrying out incorporation through automation. Not a foreboding of the Terminator variety—clearly the technology involved in legal automation is not threatening global domination, at least not yet—but of a sort common to the plight of countless workers since the dawn of the industrial era. Were the students, by helping to nudge legal automation into the mainstream, actually articulating the demise of their own professional value? Were they laying the foundations for the replacement of lawyers with machines—taking that first small step toward beaming [Lieutenant Commander Data](https://en.wikipedia.org/wiki/Data_(Star_Trek)) from the fictional [U.S.S. Enterprise](https://en.wikipedia.org/wiki/USS_Enterprise_(NCC-1701-D)) straight into a law office?
### AUTOMATION & THE FUTURE OF LAWYERING//
### BLIP'S IMPLEMENTATION OF LEGAL AUTOMATION TOOLS//
If accountants have not been replaced by calculators yet, then lawyers should not fear being replaced by [HAL 9000](https://en.wikipedia.org/wiki/HAL_9000) any time soon. That said, efficiency, effectiveness, and affordability drive innovation, and innovation is certainly shaking up what has conventionally been considered legal work. Legal automation tools—by replicating the work of attorneys—are pushing the boundaries of the role of the attorney, especially with regard to transactional practice. Within the transactional practice, BLIP students have found that business entity formation has been the most pertinent application of legal automation for the new ventures with which they work; however, other legal applications include everything from contract drafting and document review, to intellectual property prosecution and protection, to web documentation such as automated privacy policies and terms of service, to time entry and billing. These tasks have become progressively more streamlined with the addition of applications like [Change-Pro® Premier](https://www.litera.com/product/change-pro-premier-including-change-pro-word-excel-powerpoint-ocr/), [CooleyGo’s online suite of formation tools](https://www.cooleygo.com/documents/index-document-generators/), and automation-tool generators like [Neota Logic](https://www.cooleygo.com/documents/index-document-generators/), [Community.lawyer](https://community.lawyer/users/sign_up), and [DocAssemble](https://docassemble.org/download.html).
Capable of compressing research and revision time, as well as executing the mundane, affordable automation tools are overhauling many of the traditional, perhaps tedious, tasks that once filled a lawyer’s day. As a result, lawyers cannot reasonably bill as much nor as many hours for routine, automatable tasks. Instead, lawyers, and those who educate lawyers, will need to figure out what tasks should be properly ceded to machines. It seems fitting that machines will perform tasks that are more readily reduced to black and white, zeros and ones, and humans will continue to perform those tasks that require subtle, nuanced legal analysis of the “gray areas”—the ambiguities of law, ethics, and philosophy that are not amenable to the speed, logic, and parsing of binary computational algorithms. Unsurprisingly then, BLIP students have been exploring the question of how to morph the role of next-generation lawyers to serve as sophisticated advisors in a world of digital documentation and automation.
Part of the answer seems to be getting freshly-minted lawyers to start to feel more comfortable both creating and donning the metaphorical Iron Man suit. Embracing the inevitable technological change, as well as recognizing the positive value of legal tech tools, BLIP students have, in recent years, been working with many potentially-disruptive legal automation platforms and have been using automation tools to further advance access to justice and to otherwise improve and democratize legal process.[6] After many fits and starts prototyping apps, websites, and tools with user-unfriendly platforms and kluge code, the toolsets are now almost ready for prime time and capable of use by even those attorneys not trained in computer programming. While only the most tech-savvy of law students were initially comfortable building crude legal tech apps, today, even the most tech-averse law students are finding the digital tool sets sufficiently friendly to allow those trained in the procedural and substantive law to interact with the technology to collaborate and build better digital legal tools.[7]
Time will tell, but while legal automation tools appear to be filling some legal roles, they are also creating a greater demand for legal minds. In short, automation tools are made more effective by lawyers, and likewise, lawyers are made more effective by automation tools. So, while lawyers may now swing the hammer of automation, truly effective legal counsel involves being familiar with the rapidly changing legal landscape, especially where it intersects with technology, being able to detect and effectively address the client’s legal issues, and being capable of keeping the client’s aspirations in mind every step of the way. While machines can—and should—do some of the heavy lifting here, they certainly cannot do it all, at least not the machines of today.
### AUTOMATING THE CHOICE OF DELAWARE//
### THE MIT COMPUTATIONAL LAW REPORT STORY//
Although lawyers may be using legal automation tools to implement their lawyerly judgment, these tools may start shaping their judgment as well. If designed properly, automation tools will prompt lawyers to consider relevant issues that may not have otherwise occurred to them. If designed comprehensively, these tools will provide an important backstop protection against potential malpractice. If designed to save time and expense, these tools might best meet the needs of a client trying to bootstrap a new venture. In these instances and others, attorneys may be served well by automation tools, but in regard to entity formation, for example, how do these tools change the playing field?
In general, for any attorney working on a new venture, the first major decision is *whether* to form a business entity at all—if so, the next decisions are *what* to form and *where* to form it. Various legal and business considerations—including cost and tax consequences, as well as the venture’s liabilities, future plans for operations, and ability and desire to attract certain types of funding—inform these decisions, but for the time being, the decision of *where* to form an entity may end up being made (for many) by the availability of robust automation tools that are able to draft critical legal documents, such as bylaws and operating agreements. This is not necessarily bad, certainly not for Delaware, but it does promote giving short shrift to meaningful considerations.
Funding concerns, such as securing venture or angel capital, have driven many founders into forming entities in Delaware anyway, but as things stand, the vast majority of free automation tools are doubling down on this pressure without giving much, if any, consideration as to whether Delaware really makes sense for the venture. Free automation tools point to lower legal fees, and if a google search can take the role of counsel in deciding *whether* and *what* to form, then a Delaware C-Corp can be formed by just about anyone for a fraction of the cost. This might be bad news for lawyers. At the same time, it is not necessarily good news for every founder either, especially any for whom that google search fails to advise about such issues as 83(b) elections,[8] foreign qualification, intellectual property protections, or the like.
With all of this in mind, the MIT CLR’s formation story is one worth examining. After deliberation, BLIP students formed the MIT CLR as a Massachusetts limited liability company. An entity was needed for the MIT CLR’s because the co-founders desired concrete operating procedures for business decisions, fundraising capability, and personal liability protection. So, the next consideration was *what* to form. BLIP students considered the pros and cons of forming as a C- or S-Corp, LLC, and even what it would look like to form as a Vermont BBLLC, a non-profit, an L3C, a California Social Purpose Corporation, any of the various flavors of statutorily authorized Benefit Corporations or certified B Corps, or even a Wyoming Series LLC, which might have some advantages if the entity wanted to “tokenize” itself and try to find a potential Blockchain/crypto jurisdictional corporate haven. In the end, the basic LLC won out. It provided the co-founders with the flexibility that sits in the middle ground between partnership and corporation. The flexibility and benefits of an LLC ruled the day: (1) limited personal liability, (2) no limit to the amount of ownership managers or members, (3) “pass-through” taxable income for owners, (4) no requirement of formal meetings or the accompanying documentation, (5) flexible distribution of profits, and (6) customized management and decision-making structure. The questions surrounding the adaptability and flexibility of an LLC are predominantly answered in an often highly tailored operating agreement.
As to *where* to form, BLIP students concluded that it made the most sense to form in Massachusetts. Foremost, it would be cheaper; there would be no need to foreign qualify to do business in Massachusetts nor to pay a registered agent service in Delaware. Additionally, after speaking with the founders, the traditional advantages of forming in Delaware—that is, things like a greater level of investor familiarity, more developed case law, generally lower franchise taxes, business-friendly statutes, and better filing and online services—did not seem weighty enough for the MIT CLR to benefit from forming outside of the state where it would have its principal place of business.
> *Figure 1*
In the end, the decision was made to bifurcate the automate formation process. An automation tool specific to Massachusetts LLCs was used for the certificate of incorporation. However, because Massachusetts automation tools are still limited, a Delaware-specific automation tool was used to create the operating agreement, which was then manually edited to gel with Massachusetts law. Using [the automation tool on the Secretary of the Commonwealth’s website](https://corp.sec.state.ma.us/corp/loginsystem/login_form.asp?NewFiling=True), the MIT CLR’s certificate of organization was quickly and effortlessly drafted and filed. [9] [Using the Law Help Interactive (“LHI”) website](https://lawhelpinteractive.org/Interview/GenerateInterview/5977/engine), the operating agreement was drafted with substantially more thought and somewhat more initial effort.[10] While LHI’s tool outperformed others that BLIP Clinic has used, it was also not designed for Massachusetts, and the slew of automation tools that the Clinic has tried have struggled across the board with the complexity of a multi-member, manager-managed LLC. In the end, automation tools produced a flawless certificate of organization, which is not surprising due to its [simplicity](http://www.sec.state.ma.us/cor/corpdf/c156c512dllccert.pdf), and an operating agreement that still needed some work.
> *Figure 2*
Critically, like the automation tools that were used to form the MIT CLR, BLIP Clinic’s services are free; however, if they were not, it is not so clear that a Massachusetts LLC would have been the client’s best option. Because automation tools that can form a rather complex multi-member, manager-managed LLC in Massachusetts are not in place—at least not without either hitting a paywall or undergoing a search effort too massive to be worth the time—many man-hours went into cleaning up the MIT CLR’s operating agreement. So, although establishing an LLC in Massachusetts is simple, fast, and cheap, the time required to draft or rework a complex operating agreement may generate substantial legal fees for anyone that has to pay counsel to do it.[11] In short, now that there are more robust legal automation tools geared toward forming in Delaware at lawyers’ fingertips, it might be cheaper for many clients just to form in Delaware.
### CONCLUSION//
Recounting the story of the MIT CLR’s formation has revealed at least one important truth about the automation process. Effective use of automated legal tools involves the injection of knowledge and expertise by those formally trained in the legal profession at every stage of the process. In turn, this truth leads to three important realizations. Firstly, it is unlikely that lawyers’ fear of being replaced by machines will prove to be anything more than the vague and lingering paranoia attributable to any professional setting. Computer-driven legal automation tools are better depicted by [WALL•E](https://en.wikipedia.org/wiki/WALL-E) and [R2-D2](https://en.wikipedia.org/wiki/R2-D2) than [Megatron](https://en.wikipedia.org/wiki/Megatron) and [T-1000](https://en.wikipedia.org/wiki/T-1000), and by embracing automated legal tools, today’s students will not undermine their job prospects. Secondly, legal professionals and automated legal tools will coalesce with synergistic results. Legal professionals will perform better when automated tools are incorporated into their work process, and automated legals tools will produce better results when wielded by talented legal professionals. Thirdly, the utility of automated legal tools will increase exponentially with their prevalence. The more ubiquitous and comprehensive legal automation tools become, the more effective it will be for lawyers to resort to such tools. Thus, the story of the MIT CLR’s automated incorporation serves as a testament to the philosophical underpinnings of BLIP’s emphasis on both the use and development of automated legals tools.
### Footnotes
[1] Dazza Greenwood, *Announcing the MIT Computational Law Report*, YOUTUBE (May 16, 2019), https://www.youtube.com/watch?v=M2-YaD_O6iM.
[2] For example, BLIP Clinic, in the context of a Legal Hackers Hackathon on Data Privacy back in 2013, built what might have been the first, very basic, Revenge Porn takedown site— http://takemyphotodown.herokuapp.com/. Since then, various law firms and public interest groups have built more user-friendly, more functional, more robust tools built on similar concepts. Today, such a tool would be very simple to build on any of the newfangled legal automation tools like NeotaLogic, Community.Lawyer, or DocAssemble.
[3] BLIP watched as a few other law schools embraced such tools as NeotaLogic to help law students build legal automation tools, but BLIP community shunned such tools for several years, thinking it best for students to learn without such technological training wheels. Now, BLIP Clinic openly embraces NeotaLogic and other products as a user-friendly toolsets to help lawyers build legal automation applications.
[4] *See* Docracy, https://www.docracy.com (last visited Nov. 18, 2019).
[5] *See* Alex Eriksen, *eversign Has Acquired Docracy!* eversign: Blog (Mar. 6, 2019), https://blog.eversign.com/eversign-has-acquired-docracy/ (noting in 2019, Docracy was acquired by eversign).
[6] BLIP Clinic served as corporate counsel to Community.lawyer—a Brooklyn-based venture relying primarily on open-source technology and committed to helping lawyers and law firms build legal automation tools and apps. *See* Community.lawyer, https://community.lawyer (last visited Nov. 18, 2019). BLIP Clinic, in fact, helped to establish Community.lawyer as one of Delaware’s first Public Benefit Corporations and the first whose company charter explicitly commits the venture to promote access to quality legal help.
[7] Brooklyn Law School, like several other tech-forward law schools, has established a program in which law students and technologists collaborate to build access to justice tools. The “Justice Lab” at Brooklyn Law School hosts legal tech workshops to train students in computational law and legal automation, with an eye toward building access to justice apps, particularly to advance economic, environmental, and social justice, as well as to fill access to justice voids experienced by more vulnerable, marginalized individuals and communities. The objective is to leverage the skills and passions of students and professionals worldwide to create and sustain solutions that serve millions of people in need and to prepare students to excel in the modern, digitally-enabled workplace. The Justice Lab primarily uses no-code tools, AI, machine learning, and other automation software development platforms, to be used by people without programming skills to create apps that replicate the thinking and actions of lawyers. The law students work is to figure out how best to collaborate with the technology and how to apply their legal training to storyboard the law and to parse through statutes, regulations, standards, and other legal documents and then use the tech tools to automate applications around these statutes, regulations, standards, and other legal documents. Among the apps, sites, and tools in development by the Justice Lab are tools to help vulnerable families, immigrants, post-disaster victims, stateless individuals, day laborers, sex workers, gig economy workers, potential suicide victims, and felons reentering society.
[8] The 83(b) election, a provision under the Internal Revenue Code, essentially allows the founder to pre-pay his or her tax liability on a low valuation of the venture. If the venture is successful, this can spare the founder from a massive (potentially crippling) tax liability resulting from the vesting of his or her valuable but illiquid stock. *See* Julia Kagan, *83(b) Election*, Investopedia, https://www.investopedia.com/terms/1/83b-election.asp (last visited Nov. 16, 2019).
[9] *See Limited Liability Company Information*, Sec’y of the Commonwealth of Mass., http://www.sec.state.ma.us/cor/corpweb/corllc/llcinf.htm (last visited Nov. 16, 2019).
[10] *See* LawHelp Interactive, https://lawhelpinteractive.org/Interview/GenerateInterview/5977/engine (last visited Nov. 16, 2019).
[11] It should be noted that while Massachusetts does not require an LLC to have an operating agreement, it is best practice for any LLC to have one.
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