Blockchain and distributed ledger technology are considered by experts to be the biggest technological change since the invention of the internet. Since ancient times money has been the domain of governments. Because digital currencies such as Bitcoin are not created by governments as a central authority, and are being increasingly used to transfer wealth, regulators struggle on how to categorize such digital assets.
It is predicted that 10% of the global GDP will be handled by blockchain by 2027. Starting this Fall on September 19th, The Chang School of Continuing Education part of Ryerson University, is offering a course on blockchain regulation and governance.
The course is being taught by Professor Timothy Storus. Timothy Storus is the former Head of Legal and Compliance Department, Chief Compliance Officer, and Chief Anti-Money Laundering Officer at the Bank of China (Canada). He has held General Counsel positions at various banks and trust companies over the years.
The course is geared towards legal professionals, regulators, and people with an interest in technology, start-ups, and cryptocurrencies. For lawyers, understanding blockchain and the current law will help them advise clients on contracts, securities, and litigation. Examples of current commercial applications of all three typologies will be explored.
Each class will focus on a different aspect of blockchain technology, including:
- the difference between crypto-currency and traditional money;
- the uses of block chain technology;
- utility tokens;
- security tokens;
- fraud, theft, and anti-money laundering efforts; and
- smart contracts.
The course is taught over 12 weeks, from 6pm-9pm, on Thursday nights (starting September 19). To learn more about the course or to enrol click here.
(Views are my own and do not reflect the views of any organization.)
Recently Alan Freeman wrote about the use of artificial intelligence in third party funding of litigation, in his article “Intelligent Funding: Could AI Drive the Future of Litigation Finance”. Litigation funding, also known as third party funding, provides financing to plaintiffs and law firms to enable them to pursue their claims in return for a piece of the recovery.
For a court to approve a third party funding agreement, the party must show that (a) the agreement is necessary to provide access to justice, (b) that access to justice is facilitated by the third party funding agreement in a meaningful way, (c) the agreement is fair and reasonable by enabling access to justice while protecting the interests of the defendants, (d) the third party funder is not over-compensated, and (e) the third party funder is not interfering with the solicitor-client relationship, including the duty of loyalty. Typically in class action law suits the third party funder takes about 10% or less of the recovery. (Houle v St. Jude Medical Inc., 2018 ONSC 6352 at paras 34, 63-64)
Through applying artificial intelligence to thousands of cases, third party funders may be able to better determine which cases to “bet” on. Freeman writes that by using artificial intelligence programs, like Blue J Legal, third party funders may be able to determine the likely outcome of a case. He further quotes Professor Alarie (also a founder of Blue J Legal) that using artificial intelligence programs may become common place for third party funders.
I also predict that predictive programs will become more prevalent in the law. However, as long as humans are the judges, artificial intelligence programs will have its limitations in predicting the outcome of cases. There are many influencing factors beyond precedent in deciding a case. The evidence that is admitted and how witnesses are perceived also play a major role in the outcome of the case.
Additionally, there are opportunities for artificial intelligence programs to make mistakes. In the New Yorker article The Hidden Costs of Automated Thinking, Jonathan Zittrain writes that machine learning systems (subset of artificial intelligence) can be tricked into making inaccurate judgments. “Seduced by the predictive power of such systems, we may stand down the human judges whom they promise to replace. But they will remain susceptible to hijacking—and we will have no easy process for validating the answers they continue to produce.”
(This article was originally posted on slaw.ca. Views are my own and do not reflect the views of any organization.)
In Tomorrow’s Lawyers, Richard Susskind predicts that the Big Four Accounting Firms would overtake law firms in the years to come. Susskind explains that the accounting firms were forced to deal with disruption earlier than law firms. In the course of adapting to the disruption, the large accounting firms became more streamlined and became more creative in packaging services. As a result, Susskind predicts that the accounting firms would first begin to dominate law firms by eating into more routine legal work.
Yet again, Susskind’s predictions were correct. It was recently announced that Ernst & Young would be buying a legal managed services business from Thomson Reuters, named Pangea3. The company focuses on document review, contract review, financial trade documentation, and regulatory change management.
As technology improves and more legal service providers enter the picture, it begs the question: “will lawyers be forced to end their monopoly on providing legal services?” I think so.
In the Vancouver Sun, Ian Mulgrew discusses this question, and quotes Profession Gillian Hadfield. Hadfield states that the solution to making justice more affordable is to change the regulations. Hadfield argues that law should be a team sport like medical care. Medical care is provided by a “wide variety of medical professionals: nurses, radiologic technologists, pharmacists. The law should be too.”
Hadfield further argues that “Any solution that makes a dent in the problem will also have to involve expanding the types of people and organizations that are authorized to provide legal help. … [I]t is a major mistake for the legal profession to focus exclusively on how to solve the access problem with more money — public or charitable money — and volunteer pro bono efforts alone.”
As the legal market faces more competition from technology and accounting firms, law societies will be forced to confront who and what types of organizations should be regulated.
(Views are my own and do not reflect the views of any organization. This article was originally posted on slaw.ca.)
In Blockchain Revolution: How the Technology Behind Bitcoin is Changing Money, Business, and the World, Don Tapscott and Alex Tapscott discuss the potential for blockchain in changing our world. Blockchain is a list of records (blocks) that are linked using cryptography. The list of records are permanent, open, and time stamped. The records are linked using algorithms that are almost impossible to break.
Don and Alex Tapscott write that blockchain could be used to transform our judiciary. For example, they cite the concept of CrowdJury. “CrowdJury looks to transform the justice system by putting several judicial processes online, using both crowdsourcing and the blockchain, including filing a charge or complaint, gathering and vetting of evidence, engaging citizens in open trials online and as online jurors, and issuing a verdict.” The analysis and decision making would be crowdsourced, which could lead to a more accurate outcome in a shorter time frame.
In the CrowdJury process, the process would begin by someone making a report online and inviting potential witnesses to provide evidence. The original complaint and the evidence would be cryptographically stored on the blockchain to ensure that it remained on record and was not tampered with. If the accused proceeded to a trial, then the trial and all the evidence would be broadcasted online in an open-court like model. The decision-making would then be made by a mass jury.
Although CrowdJury sounds problematic in many ways, I think blockchain could still be used in our current system to safely store information. Blockchain could be a safe way to create and maintain electronic court files and store evidence and exhibits.
(Originally posted on slaw.ca. Views are my own and do not represent the views of any organization.)
Content might be king, but distribution is the kingdom. – Derek Thompson
In Hit Makers: The Science of Popularity in an Age of Distraction, Derek Thompson explains what makes a hit. He argues that consumers are looking to try new things but are also afraid of anything new. So the goal for making a hit new product is to make something that people will share with their audience. The way to get there is to make something bold yet instantly comprehensible.
It needs to looks familiar yet be advance. It is a tug of war between the “love of the new versus the preference for the old”. The trick is to frame new ideas as tweaks of old ideas, “to make your audience see the familiarity behind the surprise.”
However, in creating these bold new products, inventors must calculate the odds of its success. In The Undoing Project, Michael Lewis explains that when people calculate the odds of something happening they are really making judgments about similarity. This becomes problematic when people rely too heavily on stories rooted in the past rather than on probabilities.
Amos Tversky and Daniel Kahneman explain this conundrum. “It is far easier for a Jew living in Paris in 1939 to construct a story that the German army will behave as it did in 1919 than invent a story in which it behaves as it did in 1941, no matter how persuasive the evidence might be that, this time, things are different.”
In sum, we must create familiar yet bold new products. But we must not let our memories of the past warp our imagination of the future.
(Views are my own and do not represent the views of any organization.)
A basic premise of our legal system is that you are innocent until proven guilty. But what if we could predict who would offend using Big Data?
At its core Big Data is about predictions. It’s about taking large data sets and applying math to infer probabilities. In the Future of the Professions, Susskind predicts that Big Data will draw conclusions and offer advice as well as or better than a human expert.
But how should we respond to the dark side of Big Data? What if we could predict who would be litigious, who would re-offend criminally, or who would likely sexually abuse children? What if a company, like Google or Facebook, with its vast amount of data fired people based on Big Data, rather than on any wrongdoing? What if the Government placed potential abusers on a Watch List?
In Big Data Ethics, Neil Richards and Jonathan King provide some recommendations. They recommend establishing ethical principles and practices to guide government agencies, corporations, data brokers, information professionals, and individuals. However, principles will not be enough. We will also need laws to limit what we can do with data.
Big Datas predictions are just that: predictions. So to penalize someone before an event would set a dangerous precedent. It would gut the principle of “innocent until proved guilty”. It would place undue deference to a mathematical calculation.
(Views are my own and do not represent the views of any organization.)
Predicting the outcome of a case may be getting easier. The Toronto based product Tax Foresight, part of Blue J Legal, promises to do just that. Users enter facts into the program and an answer is provided.
Professors Benjamin Alarie et al, explain in “Computational Legal Research and the Advocates of the Future” that the program’s algorithms are trained on data of thousands of cases. The software analyzes the facts provided by users, then places those in facts in relation to facts in previously decided cases, and produces a prediction about the likely outcome of the case.
It is predicted that tools like this will be available for every major legal area and jurisdiction.
Although I am a proponent of such software, questions must be asked. How do we ensure neutral algorithms? How will data created by these program be used? Will data about the types of users, types of questions asked, and types of answers be sold for profit? Who will guard the privacy interests of users? What role will lawyers’ have in creating these products? Will judges be allowed to use these products? We must also ask what role law societies will have in regulating these products? After all people’s reliance on information from programs with outdated data or biased algorithms could have serious legal and financial consequences.
I predict that Blue J Legal’s software will also expand to other areas of law like insurance. It will allow lawyers and lay people to answer questions and find results within minutes.
Perhaps in the future, litigation will be dominated by disputes about which facts should be inputted into algorithm. For example, in a personal injury case, the focus may be on whether someone really has chronic pain. Once a judge determines the person has chronic pain, the fact is inputted into the algorithm and the algorithm calculates the amount of damages owed.
(Views are my own and do not reflect the views of any organization. This is not a sponsored post.)