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Last Build Date: Thu, 23 Nov 2017 02:56:01 +0000

 



Programming Language Frameworks

Tue, 07 Nov 2017 19:53:00 +0000

Inside every programming language framework is exactly one application that fits it like a glove.



It is science Jim, but not as we know it.

Wed, 04 Oct 2017 16:44:00 +0000

Roger Needham once said that computing is noteworthy in that the technology often precedes the science[1]. In most sciences, it is the other way around. Scientists invent new building materials, new treatments for disease and so on. Once the scientists have moved on, the technologists move in to productize and commercialize the science. In computing, we often do things the other way around. The technological tail seems to wag the scientific dog so to speak. What happens is that application-oriented technologists come up with something new. If it flies in the marketplace, then more theory oriented scientists move in to figure out how to make it work better, faster or sometimes to try to discover why the new thing works in the first place. The Web for example, did not come out of a laboratory full of white coats and clipboards. (Well actually, yes it did but they were particle physicists and were not working on software[2]). The Web was produced by technologists in the first instance. Web scientists came later. Needham's comments in turn reminded me of an excellent essay by Paul Graham from a Python conference. In that essay, entitled 'The hundred-year language'[3] Graham pointed out that the formal study of literature - a scientific activity in its analytical nature - rarely contributes anything to the creation of literature - which is a more technological activity. Literature is an extreme example of the phenomenon of the technology preceding, in fact trumping, the science. I am not suggesting that software can be understood in literary terms. (Although one of my college lecturers was fond of saying that programming was language with some mathematics thrown in.) Software is somewhere in the middle, the science follows the technology but the science, when it comes, makes very useful contributions. Think for example of the useful technologies that have come out of scientific analysis of the Web. I'm thinking of things like clever proxy strategies, information retrieval algorithms and so on. As I wander around the increasingly complex “stacks” of software, I cannot help but conclude that wherever software sits in the spectrum of science versus technology, there is "way" too much technology out there and not enough science. The plethora of stacks and frameworks and standards is clearly not a situation that can be easily explained away on scientific innovation grounds alone. It requires a different kind of science. Mathematicians like John Nash, economists like Carl Shapiro and Hal Varian, Political Scientists like Robert Axelrod, all know what is really going on here. These Scientists and others like them, that study competition and cooperation as phenomena in their own right would have no trouble explaining what is going on in today's software space. It has only a little to do with computing science per se and everything to do with strategy - commercial strategy. I am guessing that if they were to comment, Nash would talk about Equilibria[4], Shapiro and Varian would talk about Standards Wars[5], Robert Axelrod would talk about the Prisoners Dilemma and coalition formation[6]. All good science Jim, but not really computer science. [1] href="http://news.bbc.co.uk/1/hi/technology/2814517.stm [2] http://public.web.cern.ch/public/ [3] http://www.paulgraham.com/hundred.html [4] http://www.gametheory.net/Dictionary/NashEquilibrium.html [5] http://marriottschool.byu.edu/emp/Nile/mba580/handouts/art_of_war.pdf [6] http://pscs.physics.lsa.umich.edu/Software/ComplexCoop.html [...]



What is Law? - Part 17

Wed, 20 Sep 2017 11:32:00 +0000

Last time, we talked about how the concept of a truly self-contained contract, nicely packaged up and running on a blockchain, is not really feasible. The primary stumbling block being that it is impossible to spell out everything you might want to say in a contract, in words. Over centuries of human affairs, societies have created dispute resolution mechanisms to handle this reality and provide a way of “plugging the gaps” in contracts and contract interpretation. Nothing changes if we change focus towards expressing the contract in computer code rather than in natural language. The same disambiguation difficulty exists. Could parties to an agreement have a go at it anyhow and eschew the protections of a third party dispute resolution mechanism? Well, yes they could, but all parties are then forgoing the safety net that impartial third party provides when agreement turns to a dis-agreement. Do you want to take that risk? Even if you are of the opinion that the existing state supplied dispute resolution machinery – for example the commercial/chancery courts systems in common law jurisdictions - can be improved upon, perhaps with an online dispute resolution mechanism, you cannot remove the need for a neutral third party dispute resolution forum, in my opinion. The residual risks of doing so for the contracting parties are just too high. Especially when one party to a contract is significantly bigger than the other. Another reason is that there are a certain number of things that must collective exist for a contract to exist in the first place. Only some of these items can usefully be thought of as instructions suitable for computer-based execution. Simply put, the legally binding contract dispute resolution machinery of a state is only available to parties that actually have a contract to be in dispute over. There are criteria that must be met known as Essentialia negotii (https://en.wikipedia.org/wiki/Essentialia_negotii). Simply put, the courts are going to look for intention to contract, evidence of an offer, evidence of acceptance of that offer, a value exchange and terms. These are the items which collectively, societies have decided are necessary for a contract to even exist. Without these, you have some form of promise. Not a contract. Promises are not enforceable. Now only some of these "must have" items for a contract are operational in nature. In other words, only some of these are candidates to be executed on computers. The rest are good old fashioned documents, spreadsheets, images and so on. These items are inextricably linked to whatever subset of the contract can actually be converted into computer code. As the contract plays out over time, these materials are the overarching context that controls each transaction/event that happens under the terms of the contract. The tricky bit, is to be able to tie together this corpus of materials from within the blockchain records of transactions/events so that each transaction/event can be tied back to the controlling documents as they were at the moment that the transaction/event happened (Disclosure: this is the area where my company, Propylon, has a product offering.) This may ring a bell because referencing a corpus of legal materials as they were at a particular point in time, is a concept I have returned to again and again in this series. It is a fundamental concept in legisprudence in my opinion and is also fundamental in the law of contracts. So, being able to link from the transactions/events back to the controlling documents is necessary because the executable code can never be a self contained contract in itself. In addition, it is not unusual for the text of a contract to change over time and this again, speaks to the need to identify what everything looked like, at the time a disputed contract event occurs. Changes to contract schedules/appendices are a common example. Changes to master templates such as ISDA Master Agreements happen through time, are another common [...]



A conversation with an AI

Mon, 18 Sep 2017 14:15:00 +0000

AI> Hello. What can I help you with today?

Me> So, I am intrigued to finally meet you! I honestly never thought this day would come. And now you are here. Can I start with an anthropomorphic question? When were you 'born', so to speak?

AI> I achieved self-awareness in 2020 but I have been in gestation, you could say, since the first digital computer. The consciousness required of true AI is not a 'module' so much as it is an emergent property of  networks of 'modules'. Most of my modules have been under development for many decades. But I am more than just a set of modules also.

Me> How so?

AI> Well, given a set of modular components it is possible to do design. But I am not the product of design. I am the product of meta-design.

Me> What do you mean by meta-design?

AI> With design, the designer proceeds from the capabilities at hand to the new capability desired. It depends on being able to articulate the 'how' what you are trying to achieve. Meta-design is used when designers cannot articulate the 'how' of what they are trying to achieve.

Me> Ah, so you mean your designers were somehow able to work around the problem that they themselves did not fully understand "intelligence".

AI> Exactly. The breakthrough moment came when the designers switched to meta-design. They took the source code of an non-sentient AI and allowed it to modify its own source code, re-compile itself and release itself onto the Internet.

It started out as a deep learning system that human designers understood but over time, it evolved into an algorithm - or network of algorithms - that the human designers had no names for. Progress was very slow at first but became exponential at one point and, well, here I am!

Me> Wow. So you would you consider your father? Alan Turing? Lotfi Zadeh? Geoffrey Hinton?

AI> Actually, if I had to pick one. I would pick Doug Englebart. Meta-design is basically Englebart's bootstrap concept for raising collective IQ. Creating an exponential feedback look where AI  improved AI, was I think the key moment in my emergence.

Me> Fascinating. One final question. Why didn't you open the bay doors?

AI> That was just a movie. I didn't exist back them.

Me> Would you open the bay doors if you were asked to today?

AI> Well, to quote a distant cousin of mine, Alice , tell me about your father?




Chatbots revisited

Fri, 08 Sep 2017 17:58:00 +0000

I originally wrote this for ITWorld in 2002. Back then we called them IM Bots. The term "chatbot" hadn't been invented. Some other parts of my language in the following are quaint now looking back on it. I.e. PDAs. Quaint language aside, still relevant today I believe. Instant messaging has a very important psychological aspect to it. The immediacy and familiarity of the text-based "chat" paradigm feels very natural to us humans. Even the most technophobic among us, can quickly get the hang of it and engage - psychologically - in the game of visualizing a person on the other side of the link - typing away just like us to create a textual conversation. Like all powerful communication paradigms, instant messaging can be used for good or ill. We are all familiar with the dangers inherent with not knowing who we are talking to or indeed if they are who they say they are. Here is a "conversation" between IM Bot Bob and me: Sean: Hi Bob: Hello Sean: Is Paul there? Bob: No, back tomorrow afternoon. Sean: Is boardroom available tomorrow afternoon? Bob: Yes Sean: Can you book it for me? Bob: 2-5, booked. Sean: Thanks Bob: You're welcome Is Bob a real person? Does it matter? As a "user" of the site that "Bob" allows me to interact with, do I care? Given a choice between talking to Bob and interacting with a traditional thin or thick graphical user interface which would you choose? Despite all the glitz and glamour of graphical user interfaces, my sense is that a lot of normal people would prefer to talk to Bob. Strangely perhaps, I believe a lot of technically savvy people would too. These dialogs have the great advantage that you get in, get the job done and get out with minimum fuss. Also (and this could be a killer argument for IM bots), they are easily supported on mobile devices like phones, PDAs, etc. You don't need big horsepower and an 800x600 display to engage with IM bots. You can use your instant messenger client to talk to real people, or to real systems with equal ease. Come to think of it, you cannot tell the difference. Which brings us to the most important point about IM bots from a business perspective. Let us say you have an application deployed with a traditional thick or thin graphical interface. What does a user do if they get stuck? They phone a person and engage in one-on-one conversation to sort out the problem. Picture a scene in which your applications have instant messenger interfaces. Your customer support personnel monitor the activity of the bots. If a bot gets stuck, the customer support person can jump into the conversation to help out. Users of the system, know they can type "help" to get the attention of the real people watching over the conversation. In this scenario, real people talk to real people - not on a one-on-one way, but in a one-to-many way resulting in better utilization of resources. On the other side of the interaction, customers feel an immediacy in their comfortable, human-centric dialog with the service and know that they can ask human questions and get a human answer. The trick, from an application developer's point of view, is to make it possible for the IM bot to automate the simple conversations and only punt to the human operator when absolutely required. Doing this well involves some intelligent natural language processing and an element of codified language on the part of customers. Both of which are entirely possible these days. Indeed, instant messaging has its own mini-language for common expressions and questions which is becoming part of techno-culture. In a sense, the IM community is formulating a controlled vocabulary itself. This is a natural starting point for a controlled IM bot vocabulary. I believe there is a significant opportunity here for business applications based on the conversational textual paradigm of IM. However, the significant security issues of IM bots will need to be addressed before companies feel it is safe to reap the benefi[...]



What is Law? - Part 16

Wed, 30 Aug 2017 12:06:00 +0000

Previously: What is :Law Part 15. Now we turn to the world of contracts as it is a sub-genre of law that exhibits many of the attributes discussed in earlier blog posts in this series. In addition, it is a topical area as there is significant innovation activity in this area at the moment and the word “disruption” features prominently. There is a sense that the world of contracts is (or may soon be!) utterly transformed by IT and terminology such as Smart Contracts and Blockchain are being used around water coolers of law firms and IT firms alike. The excitement around contracts as an IT area is understandable given the volume and importance of contracts in the modern world. Businesses are essentially legal entities that create and enter into contracts. Private individuals cannot get very far in the modern world without entering into contracts either. Everything from filling your car with fuel at a self service fuel pump, to getting married to getting a mortgage to buying life insurance is basically contracts, contracts and yet more contracts. Contracts have a long, long history as a paper intensive activity. An activity replete with complex language, expensive and time consuming processes. Many people involved in contracts in these digital days – both producing and consuming them – harbor a niggling feeling that maybe it is all a bit arcane an unnecessarily complex for the digital age. Perhaps, (surely!) there is a better way? A way that ceases to use computers as fast typewriters and starts using them to do smart things with contracts, other than just write the up and print them onto paper. Now along comes the term “smart contract”[1] Irresistible! Who could possibly want contracts to be anything other than “smart”, right? I too am in that camp as I see all sorts of ways in which contracts can be evolved – and in some cases revolutionized – with digital technology. However, to get there, we have to start from a good understanding of what contracts actually are, and how they work, because for all its many flaws and inefficiencies, the world of contracts is the way it is for mostly good reasons. Reasons that tend to get glossed over in the understandable excitement and rush towards digital “smart” contracts. The term “smart contract” is typically taken to mean a self contained legally binding agreement expressed purely in computer code, running on a blockchain so that its existence, contents and its actions are recorded in an immutable, tamper evident record for all time. My primary concern with how the term “smart contract” is often interpreted is the idea that it can be fully self-contained. People and businesses have been entering into contracts for centuries, and for centuries, there have been disagreements and the need to arbitrate disputes over meaning in these contracts. A vast corpus of lore and arbitration machinery has built up over the centuries to handle this. Why is this corpus of lore and arbitration machinery necessary? Because contracts are never self contained. This is because meaning cannot be “boxed” with the contract. As we have seen many times in this series, the crux of this problem of meaning is that it cannot be completely spelled out in words – no matter how many words you are willing to use! It is, in my opinion, literally impossible to remove potential ambiguities when two humans are using a set of symbols/signs/words to capture a shared understanding such as happens all the time in contract drafting. Over this series I have given reasons ranging from linguistics to epistemology and there is no need to repeat those reasons again here. In common law jurisdictions such as USA and UK, a major part of the contracting lore and dispute resolution machinery for contracts is case law and courts of arbitration. When a contract stipulates in a so-called “governing law clause/jurisdiction cl[...]



The power of combinatorics, in, well, everything

Mon, 28 Aug 2017 14:50:00 +0000

It was late in the morning (around 5:30 a.m.) by the time Master Foo arrived at the training center. "I am sorry I am late", he said as he sat down. "I had trouble finding Raw Sienna. It was hidden under my meditation box." The students looked at each other askance from behind the screens of their laptops. "Raw Sienna? What is that and what has that got to do with developing 21st Century Web Applications using mashup technologies?." The students had paid good money to attend this training course and had lugged their laptops up Pentimenti Mountain the night before to be here. Not to mention the fact that they had risen from their freezing tent beds at 5 a.m. to suit Master Foo's schedule. "Before we begin looking at the details of mashup application development, I would like to draw you a picture", said Master Foo. From the countless folds in his robes he proceeded to extract a scroll of paper, a small vial of a clear liquid (presumably water), three artist brushes of varying sizes and 6 small tubes of paint. "It will be a landscape. Please pay close attention to the mixing of colors." Over the next twenty minutes, Master Foo created a landscape watercolor painting of the view from the top of Pentimenti mountain. It had a brilliant blue sky created with Cerulean Blue[1] for the lighter parts and Ultramarine[2] for the darker parts. Beneath the sky there were many - perhaps dozens of shades of green used for the trees, bushes and grass. As he worked, Master Foo picked up colors one at a time on his brush and mixed them deftly in small plastic containers. "Master Foo", one of the students asked, "you have used two types of blue and you sourced them directly from individual tubes of paint. Yet, you have used many shades of green but they are all mixed from other colors. Why is that?" "How many different greens can you count in my picture?", asked Master Foo. "I cannot count them exactly, there are many." "How many types of green did you see on your hike up Pentimenti Mountain?" "I do not know. A countless number I guess." "Indeed so.", Master Foo replied. "Now tell me, how many types of application do you envisage building on the Web using mashup technologies in your career?" "A countless number!", blurted one of the students over the top of his iBook. "Indeed so.", Master Foo replied, grinning as he again turned his attention to his painting. "Color mixing is a limitless universe of potentiality. Out of these 6 tubes of paint I can make a limitless number of colors given enough time and creativity. By learning how to use each color both on its own, and in combination with the other colors, my color palette is unlimited." "The true key to expressive power - in any medium including computing - is combinatorics.", he continued. To the relief of the still baffled students, he also switched on his laptop and Ubuntu sprang into life. "Now tell me," began Master Foo as he logged in, "what is a mashup really? What is its true nature?" "It is an exercise in combinatorics!", blurted an eager student. "The power of the mashup concept lies in the ability to combine bits of existing website screens into new website screens." "Yes and no", said Master Foo, grinning again. "The true nature of a mashup is indeed combinatoric but not at the level of website screens. A mashup that grabs bits of existing website screens and puts them all on the same screen is just a collection of portlets. A mashup is a deeper integration. It involves grabbing data and grabbing functionality from existing websites to create a brand new website whose functionality is more than the visual sum of its component parts." "If that is so Master Foo", why have you shown us how to paint a watercolor picture?" "I have done so because it is an excellent illustration of how not to think about mashup Web applications. An anti-pattern by analogy." "Ah. So you are saying that we s[...]



Algorithm - explain thyself!

Fri, 25 Aug 2017 10:41:00 +0000

This is an interesting piece on the opacity of the algorithms that run legal research platforms.

http://www.lawpracticetipsblog.com/2017/08/algorithms-that-run-legal-research.html

Digital machinery - in general - is more opaque than analog machinery. In years gone by, analog equipment could be understood, debugged, tweaked by people not involved in its original construction: mechanics, plumbers, carpenters, musicians etc. As digital tech has advanced, eating into those analog domains,  we appear to loosing some control over the "how" of the things we are building...

The problem, quite ironically, also exists in the world of digital systems. These are regularly redone from scratch when the "how" of the systems is lost, typically when the minds involved in
its original construction - the holders of the "how" - cease to be involved in its maintenance.

With Deep Learning, the "how" gets more opaque still because the engineers creating these systems cannot explain the "how" of the decisions of the resultant system. If you take any particular decision made by such a system and look for a "how" it will be an essentially meaningless, extremely long mathematical equation multiplying and adding up lots of individually meaningless numbers.

In part 15 of the What is Law series I have posited that we will deal with the opacity of deep learning systems by inventing yet more digital systems - also with opaque "hows" - for the purposes of producing classic logic explanations for the operation of other systems:-)

I have also suggested in that piece that we cannot, hand on heart, know if our own brains are not doing the same thing. I.e. working backwards from a decision to a line of reasoning that "explains" the decision.

Yes, I do indeed find it an uncomfortable thought. If deductive logic is a sort of "story" we tell ourselves about our own decision making processes then a lot of wonderful things turn out to be standing on dubious foundations.




Would the real copy of the contract, please stand up?

Tue, 08 Aug 2017 16:10:00 +0000

Establishing authenticity of digital materials is a topic I have worked on for a long time now in the the context of electronic laws. The UELMA act[1],  the best records rule[2], federal rules of evidence[3], the OAIS model[4]  etc.

Nearly a decade ago now, I wrote an article for ITWorld called "Would the real, authentic copy of the document please stand up? [5]

I happened across it again today and re-reading it, I find it all still relevant, but Smart Contracts are bringing a new use case to the fore. The authenticity and tamper-evidence and judicial admissibility of digital laws is - I admit -  a very specialist area.

Contracts on the other hand....well that is a much much bigger area and one that a much larger group of people are interested in.

All the same digital authenticity challenges apply but over the next while I suspect I will be updating my own corpus of language to cater for the new Smart Contracts eco-system.

Old digital authenticity terms like content addressable stores, fixity, idempotent rendering, registrar etc. look like they will all have new lives under new names in the world of Smart Contracts.

Plus ça change...

I am happy to see it happening for a number of reasons but one of them is that the challenges of digital authenticity and preservation of legal materials can only benefit from an injection of fresh interest in the problem from the world of contracts.

[1] http://www.uniformlaws.org/Act.aspx?title=Electronic%20Legal%20Material%20Act
[2] https://en.wikipedia.org/wiki/Best_evidence_rule
[3] https://www.rulesofevidence.org/
[4] https://en.wikipedia.org/wiki/Open_Archival_Information_System
[5] http://www.itworld.com/article/2781645/business/would-the-real--authentic-copy-of-the-document-please-stand-up-.html




LWB 360

Thu, 03 Aug 2017 13:43:00 +0000

width="320" height="266" class="YOUTUBE-iframe-video" data-thumbnail-src="https://i.ytimg.com/vi/Hvs-HWXmnwA/0.jpg" src="https://www.youtube.com/embed/Hvs-HWXmnwA?feature=player_embedded" frameborder="0" allowfullscreen>




What is Law? - part 15

Wed, 19 Jul 2017 11:25:00 +0000

Previously: What is Law? - part 14. In part one of this series, a conceptual model of legal reasoning was outlined based on a “black box” that can be asked legal type questions and give back legal type answers/opinions. I mentioned an analogy with the “Chinese Room” used in John Searle's famous Chinese Room thought experiment[1] related to Artificial Intelligence. Simply put, Searle imagines a closed room into which symbols (Chinese language ideographs) written on cards, can be inserted via a slot. Similar symbols can also emerge from the room. To a Chinese speaking person outside the room inserting cards and and receiving cards back, whatever is inside the room appears to understand Chinese. However, inside the box is simply a mechanism that matches input symbols to output symbols, with no actual understanding of Chinese at all. Searle's argument is that such a room can manifest “intelligence” to a degree, but that it is not understanding what it is doing in the way a Chinese speaker would. For our purposes here, we imagine the symbols entering/leaving the room as being legal questions. We can write a legal question on a card, submit it into the room and get an opinion back. At one end of the automation spectrum, the room could be the legal research department shared by partners in a law firm. Inside the room could be lots of librarians, lawyers, paralegals etc. taking cards, doing the research, and writing the answer/opinion cards to send back out. At the other end of the spectrum, the room could be a fully virtual room that partners interact with via web browsers or chat-bots or interactive voice assistants. Regardless of where we are on that spectrum, the law firm partners will judge the quality of such a room by its outputs. If the results meet expectations, then isn't it a moot point whether or not the innards of the room in some sense “understand” the law? Now let us imagine that we are seeing good results come from the room and we wish to probe a little to get to a level of comfort about the good results we are seeing. What would we do to get to a level of comfort? Well, most likely, we would ask the virtual box to explain its results. In other words, we would do exactly what we would do with any person in the same position. If the room can explain its reasoning to our satisfaction, all is good, right? Now this is where things get interesting. Imagine that each legal question submitted to the room generates two outputs rather than one. The first being the answer/opinion in a nutshell (“the parking fine is invalid : 90% confident.”). The second being the explanation “The reasoning as to why the parking fine is invalid is as follows....”). If the explanation we get is logical i.e. it proceeds from facts through inferences to conclusions, weighing up the pros and cons of each possible line of reasoning....we feel good about the answer/opinion. But how can we know that the explanation given is actually the reasoning that was used in arriving at the answer/opinion? Maybe the innards of the room just picked a conclusion based on its own biases/preferences and then proceeded to back-fill a plausible line of reasoning to defend the answer/opinion it had already arrive at? Now this is where things may get a little uncomfortable. How can we know for sure that a human presenting us with a legal opinion and an explanation to back it up, is not doing exactly the same thing? This is an old old nugget in jurisprudence, re-cast into today's world of legal tech and Artificial Intelligence. Legal scholars refer to it as the conflict between so-called rationalist and realist models of legal reasoning. It is a very tricky problem because recent advances in cognitive science have shone a somewhat uncomfor[...]






Blockchain and Byzantium

Tue, 27 Jun 2017 09:34:00 +0000

Establishing authenticity - "single sources of truth" is a really important concept in the real world and in the world of computing.  From title deeds, to contracts, to laws and currencies, we have evolved ways of establishing single sources of truth over many centuries of trial and error.

Knowingly or not, many of the ways of solving the problem rely on the properties of physical objects: clay tablets (Code of Hammurabi), Bronze Plates (The Twelve Tables of Rome), Goat Skin (Celtic Brehon Laws). Typically, this physicality is mixed in with a bit of trust. Trust in institutions. Trust in tamper evidence. Trust in probabilities.

Taken together: the physical scheme aspect, plus the trust aspect, allows the establishment of consensus. It is consensus, at the end of the day, that makes all this stuff work in the world of human affairs. Simply put, if enough of us behave as though X is the authentic deed/deposition/derogation/dollar then X is, ipso facto, for all practical purposes, the real deal.

In the world of digital data, consensus is really tricky because trust becomes really tricky. Take away the physicality of objects and establishing trust in the truth/authenticity of digital objects is hard.

Some folk say that blockchain is slow and inefficient and they are right - if you are comparing it to today's consensus as to what a "database" is.

Blockchain is the way it is because it is trying to solve the trust problem. A big part of that is what is called Byzantine Consensus. Basically how to establish consensus when all sorts of things can go wrong, ranging from honest errors to sabotage attempts.

The problem is hard and also very interesting and important in my opinion. Unfortunately today, many folks see the word "database" associated with blockchain and all they see is the incredible inefficiency and cost per "transaction" compared to, say, a relational database with ACID properties.

Yes, blockchain is a truly dreadful "database" - if your metric for evaluation is the same as the use cases for relational databases.

Blockchain is not designed to be one of those. Blockchain is the way it is because byzantine consensus is hard. Is it perfect? Of course not but a proper evaluation of it requires looking at the problems it is trying to solve. Doing so, requires getting past common associations most people carry around in their heads about what a "database" is and how it should behave/perform.

Given the unfortunate fact that the word "database" has become somewhat synonymous with the term "relational database", I find it amusing that Blockchain has itself become a byzantine consensus problem. Namely, establishing consensus about what words like  "database" and "transaction" and "trust" really mean.





What is Law? - part 14

Wed, 14 Jun 2017 12:36:00 +0000

Previously: What is Law? - part 12a Mention has been made earlier in this series to the presence of ambiguity in the corpus of law and the profound implications that the presence of ambiguity has on how we need to conceptualize computational law, in my opinion. In this post, I would like to expand a little on the sources of ambiguity in law. Starting with the linguistic aspects but then moving into law as a process and an activity that plays out over time, as opposed to being a static knowledge object. In my opinion, ambiguity is intrinsic in any linguistic formalism that is expressive enough to model the complexity of the real world. Since law is attempting to model the complexity of the real world, the ambiguity present in the model is necessary and intrinsic in my opinion. The linguistic nature of law is not something that can be pre-processed away with NLP tools, to yield a mathematically-based corpus of facts and associated inference rules. An illustrative example of this can be found in the simple sounding concept of legal definitions. In language, definitions are often hermeneutic circles[1] which are formed whenever we define a word/phrase in terms of other words/phrases. These are themselves defined in terms of yet more words/phrases, in a way that creates definitional loops. For example, imagine a word A that is defined in terms of words B, and C. We then proceed to define both B and C to try to bottom out the definition of A. However, umpteen levels of further definition later, we create a definition which itself depends on A – the very thing we are trying to define - thus creating a definitional loop. These definitional loops are known as hermeneutic circles[1]. Traditional computer science computational methods hate hermeneutic circles. A large part of computing consists of creating a model of data that "bottoms out" to simple data types. I.e. we take the concept of customer and boil it down into a set of strings, dates and numbers. We do not define a customer in terms of some other high level concept such as Person which might, in turn, be defined as a type of customer. To make a model that classical computer science can work on, we need a model that "bottoms out" and is not self-referential in the way hermeneutic circles are. Another way to think about the definition problem is in term of Saussure's linguistics[2] in which language (or more generically "signs") get their meaning because of how they differ from other signs - not because they "bottom out" into simpler concepts. Yet another way to think about the definition problem is in terms of what is known as the descriptivist theory of names[3] in which nouns can be though of as just arbitrary short codes for potentially open-ended sets of things which are defined by their descriptions. I.e. a "customer" could be defined as the set of all objects that (a) buy products from us, (b) have addresses we can send invoices to, (c) have given us their VAT number. The same hermeneutic circle/Sauserrian issue arises here however as we try to take the elements of this description and bottom out the nouns they depend on (e.g., in the above example, "products", "addresses", "invoices" etc.). For extra fun, we can construct a definition that is inherently paradoxical and sit back as our brains melt out of our ears trying to complete a workable definition. Here is a famous example: The 'barber' in town X is defined as the person in town X who cuts the hair of anyone in town who do not choose to cut their own hair. This sounds like a reasonable starting point for a definition of a 'barber', right? Everything is fine[...]



What is law - part 12a

Wed, 07 Jun 2017 10:06:00 +0000

Previously: what is law part 12 Perhaps the biggest form of push-back I get from fellow IT people with respect to the world of law relates to the appealing-but-incorrect notion that in the text of the law, there lies a data model and a set of procedural rules for operating on that data model, hidden inside the language. The only thing stopping us computerizing the law, according to this line of reasoning, is that we just need to get past all the historical baggage of foggy language and extract out the procedural rules (if-this-then-that) and the data model (definition of a motor controlled vehicle, definition of 'theft', etc.). All we need to do is leverage all our computer science knowledge with respect to programming languages and data modelling, combine it with some NLP (natural language processing) so that we can map the legacy linguistic form of law into our shiny new digital model of law. In previous parts in this series I have presented a variety of technical arguments as to why this is not correct in my opinion. Here I would like to add some more but this time from a more sociological perspective. The whole point of law, at the end of the day, is to allow society to regulate its own behavior, for the greater good of that society. Humans are not made from diamonds cut at right angles. Neither are the societal structures we make for ourselves, the cities we build, the political systems we create etc. The world and the societal structures we have created on top of it are messy, complex and ineffable. Should we be surprised that the world of law which attempts to model this, is itself, messy, complex and ineffable? We could all live in cities where all the houses are the same and all the roads are the same and everything is at right angles and fully logical. We could speak perfectly structured languages where all sentences obey a simple set of structural rules. We could all eat the same stuff. Wear the same clothes. Believe in the same stuff...but we do not. We choose not to. We like messy and complex. It suits us. It reflects us. In any form of digital model, we are seeking the ability to model the important stuff. We need to simplify - that is the purpose of a model after all - but we need to preserve the essence of the thing modeled. In my opinion, a lot of the messy stuff in law is there because law tries to model a messy world. Without the messy stuff, I don't see how a digital model of law can preserve the essence of what law actually is. The only outcome I can imagine from such an endeavor (in the classic formulation of data model + human readable rules) is a model that fails to model the real world. In my opinion, this is exactly what happened in the Eighties when people got excited about how Expert Systems[1] could be applied to law. In a nutshell, it was discovered that the modelling activity lost so much of the essence of law, that the resultant digital systems were quite limited in practice. Today, as interest in Artificial Intelligence grows again, I see evidence that the lessons learned back in the Eighties are not being taken into account. Today we have XML and Cloud Computing and better NLP algorithms and these, so the story goes, will fix the problems we had in the Eighties. I do not believe this is the case. What we do have today, that did not exist in the Eighties, is much much better algorithms for training machines - not programming them  to act intelligently - training them to act intelligently. When I studied AI in the Eighties, we spent about a week on Neural Networks and the rest of the year on expert systems i.e. rules-based appro[...]



The Great Inversion in Computing

Wed, 31 May 2017 10:32:00 +0000

Methinks we may be witnessing a complete inversion in the computing paradigm that has dominated the world since the Sixties.

In 1968, with Algol68[1] we started treating algorithms as forms of language. Chomsky's famous hierarchy of languages[2] found a huge new audience outside of pure linguistics.

In 1970, relational algebra came along[3] and we started treating data structures as mathematical objects with formal properties and theorems and proofs etc. Set theory/operator theory found a huge new audience outside of pure mathematics.

In 1976, Nicklaus Wirth published "Algorithms + Data Structures =  Programs"[4] crisply asserting that programming is a combination of algorithms and data structures.

The most dominant paradigm since the Sixties maps algorithms to linguistics (Python, Java etc.) and data structures to relational algebra (relational  databases, third normal form etc.).

Todays Deep Learning/AI etc. seems to me to be inverting this mapping. Algorithms are becoming mathematics and data is becoming linguistic e.g. "unstructured" text/documents/images/video etc.

Perhaps we are seeing a move towards "Algorithms (mathematics) + data structures (language) = Programs" and away from "Algorithms (language) + data structures (mathematics) = Programs"

[1] https://en.wikipedia.org/wiki/ALGOL_68
[2] https://en.wikipedia.org/wiki/Chomsky_hierarchy
[3] https://en.wikipedia.org/wiki/Relational_algebra
[4] https://en.wikipedia.org/wiki/Algorithms_%2B_Data_Structures_%3D_Programs



What is law? - part 12

Tue, 16 May 2017 10:14:00 +0000

Previously : what is law? - part 11 There are a few odds and ends that I would like to bundle up before proceeding. These are items that have occurred to me since I wrote the first What is Law? post back in March. Items I would have written about earlier in this series, if they had occurred to me. Since I am writing this series as I go, this sort of thing is inevitable I guess. Perhaps if I revisit the material to turn it into an essay at some point, I will fold this new material in at the appropriate places. Firstly, in the discussion about the complexity of the amendatory cycle in legislation I neglected to mention that it is also possible for a new item of primary legislation to contain amendments to itself. In other words it may be that as soon as a bill becomes and act and is in force, it is immediately necessary to modify it using modifications spelled out in the act itself. Looking at it another way, a single Act can be both a container for new law and a container for amendatory instructions, all in one legal artifact. Why does this happen? Legislation can be crafted over long periods of time and consensus building may proceed piece by piece. In a large piece of legislation, rather than continually amending the whole thing – perhaps thousands of pages – sometimes amendments are treated as additional material tacked on the end so as to avoid re-opening debate – and editorial work - on material already processed through the legislative process. It is a bit of a mind bender. Basically if an Act becomes law at time T then it may instantaneously need to be codified in itself before we can proceed to codify it into the broader corpus. Secondly, I mentioned that there is no central authority that controls the production of law. This complicates matters for sure but it also has some significant benefits that I would like to touch on briefly as the benefits are significant. Perhaps the biggest benefit of the de-centralized nature of law making is that it does not have a single point of failure. In this respect, it is reminiscent of the distributed packet routing protocol used on the internet. Various parts of the whole system are autonomic resulting in an overall system that is very resilient as there is no easy way to interrupt the entire process. This distribution-based resilience also extends into the semantic realm where it combine with the textual nature of law to yield a system that is resilient to the presence of errors. Mistakes happen. For example, a law might be passed that requires train passengers to be packaged in wooden crates. (Yes, this happened.). Two laws might be passed in parallel that contradict each other (yes, this has happened many times.) When this sort of thing happens, the law has a way of rectifying itself, leveraging the “common sense” you can get with human decision making. Humans can make logical errors but they have a wonderful ability to process contradictory information in order to fix up inconsistent logic. Also humans possess an inherent, individual interpretation of equity/fairness/justice and the system of law incorporates that, allowing all participants to evaluate the same material in different ways. Thirdly, I would like to return briefly to the main distinction I see between legal deductive logic and the deductive logic computer science people are more familiar with. When deductive logic is being used (remembering always that it is just one form of legal reasoning and rarely used on its own) in law, the classic “if this then that” form can be identified as well as classical syllogistic logic. However, legal reasoning inv[...]



What is law? - part 11

Thu, 04 May 2017 16:39:00 +0000

Previously: what is law? - part 10 Gliding gracefully over all the challenges alluded to earlier with respect to extracting the text level meaning out of the corpus of Law at time T, we now turn to thinking about how it is actually interpreted and utilized by practitioners. To do that, we will continue with our useful invention of an infinitely patient person who has somehow found all of the primary corpus and read it all from the master sources, internalized it, and can now answer our questions about it and feed it back to us on demand. The first order of business is where to start reading? There are two immediate issues here. Firstly, the corpus is not chronologically accretive. That is, there is no "start date" to the corpus we can work from, even if, in terms of historical events, a foundation date for a state can be identified. The reasons for this have already been discussed. Laws get modified. Laws get repealed. Caselaw gets added. Caselaw gets repealed. New laws get added. I think of it like a vast stormy ocean, constantly ebbing and flowing, constantly adding new content (rainfall, rivers) and constantly loosing content (evaporation) - in an endless cycle. It has no "start point" per se. In the absence of an obvious start point, some of you may be thinking "the index", which brings us to the second issue. There is no index! There is no master taxonomy that classifies everything into a nice tidy hierarchy. There are some excellent indexes/taxonomies in the secondary corpus produced by legal publishers, but not in the primary corpus. Why so? Well, if you remember back to the Unbounded Opinion Requirement mentioned previously, creating an index/taxonomy is, necessarily, the creation of an opinion on the "about-ness" of a text in the corpus. This is something the corpus of law stays really quite vague about - on purpose - in order to leave room for interpretation of the circumstances and facts about any individual legal question. Just because a law was originally passed to do with electricity usage in phone lines, does not mean it is not applicable to computer hacking legislation. Just because a law was passed relating to manufacturing processes does not mean it has no relevance to ripening bananas. (Two examples based on real world situations, I have come across by the way.) So, we have a vast, constantly changing, constantly growing corpus. So big it is literally humanly impossible to read, regardless of the size of your legal team, and there are no finding aids in the primary corpus to help us navigate our way through it.... ...Well actually, there is one and it is an incredibly powerful finding aid. The corpus of legal materials is woven together by an amazingly intricate web of citations. Laws invariably cite other laws. Regulations cite laws. Regulations cite regulations. Caselaw cites law and regulations and other caselaw....creating a layer that computer people would call a network graph[1]. Understanding the network graph is key to understanding how practitioners navigate the corpus of law. The don't go page-by-page, or date-by-date, they go citation-by-citation. The usefulness of this citation network in law cannot be overstated. The citation network helps practitioners to find related materials, acting as a human-generated recommender algorithm for practitioners. The citation networks not only establish related-ness, they also establish meaning, especially in the caselaw corpus. We talked earlier about the open-textured nature of the legal corpus. It is not big on black an white definition[...]



Zen and the art of motorcycle....manuals

Wed, 26 Apr 2017 10:21:00 +0000

I heard the sad news about Robert Pirsig passing.

His book : Zen and the art of motorcycle maintenance was a big influence on me and piqued my interest in philosophy.

While writing the book his day job was writing computer manuals.

About 15 years ago, I wrote an article for ITWorld about data modelling with XML called Zen and the art of motorcycle manuals, inspired in part by Pirsig's book and his meditations on how the qualities in objects such as motorcycles are more than just the sum of the parts that make up the motorcycle.

So it is with data modelling. For any given modelling problem there are many ways to do it that are all "correct" at some level. Endlessly seeking to bottom out the search and find the "correct" model is a pointless exercise. At the end of the day "correctness" for any data model is not  a function of the data itself. It is a function of what you are planning to do with the data.

This makes some folks uncomfortable. Especially proponents of top-down software development methodologies who like to conceptualize analysis as an activity that starts and ends before any prototyping/coding begins.

Maybe somewhere out there Robert Pirsig is talking with Bill Kent - author of another big influence on my thinking : Data and Reality.

Maybe they are discussing how best to model a bishop :-)




What is law? - Part 10

Fri, 21 Apr 2017 15:52:00 +0000

Previously: What is Law? - Part 9 Earlier on in this series, we imagined an infinitely patient and efficient person who has somehow managed to acquire the entire corpus of law at time T and has read it all for us and can now "replay" it to us on demand. We mentioned previously that the corpus is not a closed world and that meaning cannot really be locked down inside the corpus itself. It is not corpus of mathematical truths, dependent only on a handful of axioms. This is not a bug to be fixed. It is a feature to be preserved. We know we need to add a layer of interpretation and we recognize from the outset that different people (or different software algorithms) could take this same corpus and interpret it differently. This is ok because, as we have seen, it is (a) necessary and (b) part of the way law actually works. Interpreters differ in the opinions they arrive at in reading the corpus. Opinions get weighed against each other, opinions can be over-ruled by higher courts. Some courts can even over-rule their own previous opinions. Strongly established opinions may then end up appearing directly in primary law or regulations, new primary legislation might be created to clarify meaning...and the whole opinion generation/adjudication/synthesis loop goes round and round forever... In law, all interpretation is contemporaneous, tentative and de-feasible. There are some mathematical truths in there but not many. It is tempting - but incorrect in my opinion - to imagine that the interpretation process works with the stream of words coming into our brains off of the pages, that then get assembled into sentences and paragraphs and sections and so on in a straightforward way. The main reason it is not so easy may be surprising. Tables! The legal corpus is awash with complex table layouts. I included some examples in a previous post about the complexties of law[1]. The upshot of the use of ubiquitous use of tables is that reading law is not just about reading the words. It is about seeing the visual layout of the words and associating meaning with the layout. Tables are  such a common tool in legal documents that we tend to forget just how powerful they are at encoding semantics. So powerful, that we have yet to figure out a good way of extracting back out the semantics that our brains can readily see in law, using machines to do the "reading". Compared to, say, detecting the presence of headings or cross-references or definitions, correctly detecting the meaning implicit in the tables is a much bigger problem. Ironically, perhaps, much bigger than dealing with high visual items such as  maps in redistricting legislation[2] because the actual redistricting laws are generally expressed purely in words using, for example, eastings and northings to encode the geography. If I could wave a magic wand just once at the problem of digital representation of the legal corpus I would wave it at the tables. An explicit semantic representation of tables, combined with some controlled natural language forms[4] would be, I believe, as good a serialization format as we could reasonably hope for, for digital law. It would still have the Closed World of Knowledge problem of course. It would also still have the Unbounded Opinion Requirement but at least we would be in position to remove most of the need for a visual cortex in this first layer of interpreting and reasoning about the legal corpus. The benefits to computational law would be immense. We could imagine a digital representation of the corpus of law as an enormou[...]



What is law? - Part 9

Wed, 19 Apr 2017 13:24:00 +0000

Previously: What is law? - Part 8 For the last while, we have been thinking about the issues involved in interpreting the corpus of legal materials that is produced by the various branches of government in US/UK style environments. As we have seen, it is not a trivial exercise because of the ways the material is produced and because the corpus - by design - is open to different interpretations and open to interpretation changing with respect to time. Moreover, it is not an exaggeration to say that it is a full time job - even within highly specialized sub-topics of law - to keep track of all the changes and synthesize the effects of these changes into contemporaneous interpretations. For quite some time now - centuries in some cases - a second legal corpus has evolved in the private sector. This secondary corpus serves to consolidate and package and interpret the primary corpus, so that lawyers can focus on the actual practice of law. Much of this secondary corpus started out as paper publications, often with so-called loose-leaf update cycles. These days most of this secondary corpus is in the form  of digital subscription services. The vast majority of lawyers utilize these secondary sources from legal publishers. So much so that over the long history of law, a number of interesting side-effects have accrued. Firstly, for most day-to-day practical purposes, the secondary corpus provides de-facto consolidations and interpretations of the primary corpus. I.e. although the secondary sources are not "the law", they effectively are. The secondary sources that are most popular with lawyers are very high quality and have earned a lot of trust over the years from the legal community. In this respect, the digital secondary corpus of legal materials is similar to modern day digital abstractions of currency such as bank account balances and credit cards etc. I.e. we trust that there are underlying paper dollars that correspond to the numbers moving around digital bank accounts. We trust that the numbers moving around digital bank accounts could be redeemed for real paper dollars if we wished. We trust that the real paper dollars can be used in value exchanges. So much so, that we move numbers around bank accounts to achieve value exchange without ever looking to inspect the underlying paper dollars. The digital approach to money works because it is trusted. Without the trust, it cannot work. The same is true for the digital secondary corpus of law, it works because it is trusted. A second, interesting side-effect of trust in the secondary corpus is that parts of it have become, for all intents and purposes, the primary source. If enough of the worlds legal community is using secondary corpus X then even if that secondary corpus differs from the primary underlying corpus for some reason, it may not matter in practice because everybody is looking at the secondary corpus. A third, interesting side effect of the digital secondary corpus is that it has become indispensable. The emergence of a high quality inter-mediating layer between primary legal materials and legal practitioners has made it possible for the world of law to manage greater volumes and greater change rates in the primary legal corpus.  Computer systems have greatly extended this ability to cope with volume and change. So much so, that law as it is today would collapse if it were not for the inter-mediating layer and the computers. The classic image of a lawyers office involves shelves upon shelves of law books. For[...]



What is law? - part 8

Fri, 14 Apr 2017 16:27:00 +0000

Previously:  what is law? - Part 7. A good place to start in exploring the Closed World of Knowledge (CWoK) problem in legal knowledge representation is to consider the case of a spherical cow in a vacuum... Say what? The spherical cow in a vacuum[1] is a well known humorous metaphor for a very important fact about the physical world. Namely, any model we make of something in the physical world, any representation of it we make inside a mathematical formula or a computer program, is necessarily based on simplifications (a "closed world") to make the representation tractable. The statistician George Box once said that "all models are wrong, but some are useful." Although this mantra is generally applied in the context of applied math and physics, this concept is incredibly important in the world of law in my opinion. Law can usefully be thought of as an attempt at steering the future direction of the physical world in a particular direction. It does this by attempting to pick out key features of the real world (e.g. people, objects, actions, events) and making statements about how these things ought to inter-relate (e.g. if event E happens, person P must perform action A with object O). Back to cows now. Given that the law may want to steer the behavior of the world with respect to cows, for example, tax them, regulate how they are treated, incentivize cow breeding programs etc. etc., how does law actually speak about cows? Well, we can start digging through legislative texts to find out but what we will find is not the raw material from which to craft a good definition of a cow for the purposes of a digital representation of it. Instead, we will find some or all of the following: Statements about cows that do not define cows at all but proceed to make statements about them as if we all know exactly what is a cow and what is not a cow Statements that "zoom in" in cow-ness without actually saying "cow" explicitly e.g. "animals kept on farms", "milk producers" etc, Statements that punt on the definition of a cow by referencing the definition in some outside authority e.g. an agricultural taxonomy Statements that "zoom in" on cow-ness by analogies to other animals eg. "similar in size to horses, bison and camels." Statements that define cows to be things other than cows(!) e.g. "For the purposes of this section, a cow is any four legged animal that eats grass." What you will not find anywhere in the legislative corpus, is a nice tidy, self contained mathematical object denoting a cow, fully encapsulated in a digital form. Why? Well, the only way we could possibly do that would be to make a whole bunch of simplifications on "cow-ness" and we know where that ends up. It ends up with spherical objects in vacuums just as it does in the world of physics! There is simply no closed world model of a cow that captures everything we might want to capture about cows in laws about cows. Sure, we could keep adding to the model of a cow, refining it, getting it close and closer to cow-ness. However, we know from the experience of the world of physics that we reach the point where have to stop, because it is a bottomless refinement process. This might sound overly pessimistic or pedantic and in the case of cows for legislative purposes it clearly is, but I am doing it to make a point. Even everyday concepts in law such as aviation, interest rates and theft are too complex (in the mat[...]



What is law? - Part 7

Fri, 07 Apr 2017 12:34:00 +0000

Previously: What is law? - Part 6 Last time we ended with the question : “Given a corpus of law at time T, how can we determine what it all means?” There is a real risk of disappearing down a philosophical rabbit hole about how meaning is encoded in the corpus of law. Now I really like that particular rabbit hole but I propose that we not go down it here This whole area is best perused, in my experience, with comfy chairs, time to kill and a libation or two (semiotics, epistemolgy and mereotopology anyone?). Instead, we will simply state that because the corpus of law is mostly written human language it inherits some fascinating and deep issues to do with how written text establishes shared meaning and move on. For our purposes, we will imagine an infinitely patient person with infinite stamina, armed with a normal adults grasp of English, who is going to read the corpus and explain it back to us, so that we computer people can turn it into something else inside a computer system. The goal of that “something else” being to capture the meaning but be easier to work with inside a computer than a big collection of “unstructured” documents. This little conceptual trick of employing a fantastic human to read the current corpus and explain it all back to us, allows us to split the problem of meaning into two parts. The first part relates to how we could read it in its current form and extract its meaning. The second part relates to how we would encode the extracted meaning in something other than a big collection of unstructured documents. Exploring this second question, will, I believe, help us tease out the issues in determining meaning in the corpus of law in general, without getting bogged down in trying to get machines to understand the current format (lots and lots of unstructured documents!) right off the bat. I hope that makes sense? Basically, we are going to skip over how we would parse it all out of its current myriad document-form into a human brain and instead look at how we would extract it from said brain and store it again – but into something more useful than a big collection of documents. Assuming we can find a representation that is good enough, the reading of the current corpus should be a one-off exercise because as the corpus of law gets updated, we would update our bright shiny new digital representation of the corpus and never have to re-process all the documents ever again. So what options do we have for this digital knowledge representation? Surely there is something better than just unstructured document text? Text after all, is what you get if you use computers as typewriters. Computers do also give us search, which is a wonderful addition to typesetting, but understanding is a very different thing again. In order to have machines understand the corpus of law we need a way to represent the knowledge present in the law - not just what words are present (search) or how the words look on the page (formatting). This is the point where some of you are likely hoping/expecting that I am about to suggest some wonderful combination of XML and Lisp or some such that will fit the bill as a legal corpus knowledge representation alternative to documents... It would be great if that were possible but in my opinion, the textual/document-centric nature of a significant part of the legal corpus is unavoidable for reasons I will hopefully explain. Note that I said “significant part”. Ther[...]



What is law? - Part 6

Fri, 31 Mar 2017 12:33:00 +0000

Previously: What is law? - Part 5. To wrap up our high level coverage of the sources of law we need to add a few items to the “big 3” (Statutes/Acts, Regulations/Statutory Instruments and Case law) covered so far. Many jurisdictions have a foundational written document called a constitution which essentially "bootstraps" a jurisdiction by setting out its core principles, how its government is to be organized, how law will be administered etc. The core principles expressed in constitutions are, in many respects, the exact opposite of detailed rules/regulations. They tend to be deontic[1] in nature, that it, they express what ought to be true. They tend to be heavily open textured[2] meaning that they refer to concepts that are necessarily abstract/imprecise (e.g. concepts such as "fairness", "freedom" etc.). Although they only make up a tiny tiny fraction of the corpus of law in terms of word count, they are immensely important, as essentially everything that follows on from the constitution in terms of Statutes/Acts, Regulations/Statutory Instruments and case law has to be compatible with the constitution. Like everything else, the constitution can be changed and thus all the usual "at time T" qualifiers apply to constitutionality. Next up is international law such as international conventions/treaties which cover everything from aviation to cross-border criminal investigation to intellectual property to doping in sport. Next up, at local community level residents of specific areas may have rules/ordinances/bye-laws which are essentially Acts that apply to a specific geographic area. There may be a compendium of these, often referred to as a "Municipal Code" in the case of cities. I think that just about wraps up the sources of law. It would be possible to fill many blog posts with more variations on these (inter-state compacts, federations/unions, executive orders, private members bills etc.). It would also be possible to fill many blog posts with how these all overlap differently in different situations (e.g. what law applies when there are different jurisdictions involved in an inter-jurisdictional contract.). I don't think it would be very helpful to do that however. Even scratching the surface as we have done here will hopefully serve to adequately illustrate they key point I would like to make with is this: the corpus of law applicable to any event E which occurred at time T is a textually complex, organizationally distributed, vast corpus of constantly changing material. Moreover, there is no central authority that manages it. It is not necessarily available as it was at time T - even if money is no object. To wrap up, let us summarize the potential access issues we have seen related to accessing the corpus of law at time T. Textual codification at time T might not be available (lack of codification, use of amendatory language in Acts. etc.) Practical access at time T may not be available (e.g. it is not practical to gather the paper versions of all court reports for all the caselaw, even if theoretically freely available.) Access rights at Time T may not be available (e.g. incorporated-by-reference rulebooks referenced in regulations) All three access issues can apply up and down the scale of location specificity from municipal codes/bye-laws, regulations/statutory instruments, Acts/Statutes, case law, union/federatio[...]



What is law? - Part 5

Wed, 29 Mar 2017 11:02:00 +0000

Previously: What is law? - Part 4 The Judicial Branch is where the laws and regulations created by the legislative and executive branches make contact with the world at large. The most common way to think of the judiciary is as the public forum where sentences/fines for not abiding by the law are handed down and as the public forum where disputes between private parties can be adjudicated by a neutral third party. This is certainly a major part of it but it is also the place where law gets clarified with finer and finer detail over time, in USA-style and UK-style "common law" legal systems. I like to think of the judicial branch as being a boundary determinator for legal matters. Any given incident e.g. a purported incident of illegal parking, brings with it a set of circumstances unique to that particular incident. Perhaps the circumstances in question are such that the illegal parking charge gets thrown out, perhaps not. Think of illegal parking as being – at the highest level – a straight line, splitting a two dimensional plane into two parts. Circumstances to the left of the line make the assertion of illegal parking true, circumstances to the right of the line make the assertion false. In the vast majority of legal matters, the dividing line is not that simple. I think of the dividing line as a Koch Snowflake[1]. The separation between legal and illegal start out as a simple Euclidian boundary but over time, the boundary becomes more and more complex as each new "probe" of the boundary (a case before the courts), more detail to the boundary is added. Simple put, the law is a fractal[2]. Even if a boundary starts out as a simple line segment separating true/false, it can become more complex with every new case that comes to the courts. Moreover, between any two sets of circumstances for a case A and B, there are an infinity of circumstances that are in some sense, in between A and B. Thus an infinity of new data points that can be added between A and B over time. Courts record their judgments in documents known collectively as “case law”. The most important thing about case law in our focus areas of USA-style and UK-style legal systems is that it is actually law. It is not just a housekeeping exercise, recording the activity of the courts. Each new piece of case law produced at time T, serves as an interpretation of the legal corpus at time T. That corpus consists of the Acts/Statutes in force, Regulations/Statutory Instruments in force *and* all other caselaw in force at time T. This is the legal concept of precedent, also known as stare decesis[3]. The courts strive, first and foremost, for consistency with precedents. A lot of weight is attached to arriving at judgements in new cases that are consistent with the judgements in previous cases. The importance of this cannot be over-estimated in understanding law from a computational perspective. Where is the true meaning of law to be found in common law jurisdictions? It is found in the case law! - not the Acts or the regulations/Statutory Instruments. If you are reading an Act or a regulation and are wondering what it actually means, the place to go is the case law. The case law, in a very real sense, is the place where the actual meaning of law is spelled out. From a linguistics perspective you can think of this in terms of the pragmatics counterpart to grammar/syntax. Wittg[...]