Kangaroo Court

Kangaroo Court: The Story of the Luddites

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The Luddites were a secret oath-based organization of English textile workers in the 19th century, a radical faction which destroyed textile machinery as a form of protest. The Luddite movement emerged during the harsh economic climate of the Napoleonic Wars, which saw a rise in difficult working conditions. Luddites objected primarily to the rising popularity of automated textile equipment, threatening the jobs and livelihoods of skilled workers.

In retaliation, the Luddites would meet at night on the moors surrounding industrial towns, where they practiced military like drills and manoeuvres. Their main areas of operation began in Nottinghamshire in November 1811, followed by the West Riding of Yorkshire in early 1812. Finally, they moved to Lancashire in March 1813. They smashed stacking frames and cropping frames among others. However, there does not seem to have been any political motivation behind the Luddite Riots. There wasn’t even a national organization. They were merely attacking what they saw as the reason for the decline of their livelihoods.

The British Army clashed with the Luddites on several occasions. At one time there were more British soldiers fighting the Luddites then there were fighting Napoleon on the Iberian Peninsula. Finally, after some time, the British government sought to suppress the Luddite movement with a mass trial at York in January 1813. The harsh sentences of those found guilty, which included execution and penal transportation, quickly ended the movement.

The real tragedy of the Luddites was the feeling they endured. They had spent years of their lives toiling away, only to being cast aside as economically irrelevant. The ruling class had treated entire communities of workshop laborers like obsolete machinery. Having a sense of purpose and pride helps to generate the most basic feelings of meaning in life. When a community loses those basic human needs, the impact cuts deep. Family’s face depression, hopelessness, and intense desperation. In early 19th century England, the Luddites felt like their humanity had been reduced to a point where they felt powerless. Without hope, they fought back and destroyed some of the machines that replaced them, if only to give their voices light. Ultimately, they were let down by the combination of government and industry, accepting the innovation but neglecting to transition the people who helped build the foundations which brought them wealth. Today, the term ‘Luddite’ has been applied to those whom generally oppose technological innovation.

This story isn’t new, but it certainly isn’t very old. The collapse of the coal mining industry across the Appalachia’s has economically crippled large parts of the country. Spare a thought for these hard-working folk. For years they had undertaken dangerous and back breaking work, risking their lives under millions of tons of rock to mine the raw materials which would help fuel the United States energy needs. In return they could earn a decent living, purchase a house, and feel a sense of purpose that connected with a community whom was largely employed within this once powerful industry. The American dream was very real, until it wasn’t. The U.S. coal mining industry had been declining in the face of lower-cost natural gas, renewable energy and regulations designed to reduce greenhouse gas emissions and protect public health. Add decades of mechanization, and the prospects of finding meaningful work becomes slim.

Again, the issue here isn’t innovation. The reduction in fossil fuels and adoption of renewable energy creates an overwhelming positive for the health and quality of our planet, let alone the lives of future generations. The issue is the neglect workers experienced from the industry and government. Just like the Luddites, the energy industry had quietly forgotten what helped build the foundations which enabled it to prosper. The problem occurs when those who risk being automated aren’t part of the conversation. They don’t have the forum to understand when innovation is going to impact their work, and how they can adapt alongside to ensure their skill set remains aligned with changes in the industry.

Finding new ways to innovate has generally speaking been a good idea throughout much of our history. The extent and viability of adopting different products or practices can vary, but the fundamental idea is sound. It’s the reason we don’t live in huts and depend on horses for transportation. It’s the reason I can speak to my family on the other side of the world at a reasonable price. It’s the reason we can order nearly any product in the world to our door on a Saturday. It’s the reason the iPhone 12 is equipped with a LiDAR scanner for the purpose of augmenting reality. It’s the reason why SpaceX built the Falcon 9, the first orbital rocket capable of re-flight. It’s the reason I can live-stream the Australian Rugby team’s test-match against Argentina at 2:45am this Saturday morning, in ultra-high definition. Whatever enables the brilliant engineers among us to keep pushing our technological advancements toward new heights, I for one, applaud them.

Not all innovation is good. Strong arguments could be made that building more powerful military equipment has a net-negative value for human safety. Some of our greatest scientific achievements have resulted in horrific destructive applications. In 1917, a New Zealand-born physicist by the name of Earnest Rutherford successfully split the atom. However, our penchant for innovation would eventually lead to a test site located 210 miles south of Los Alamos on the barren plains of the Alamogordo Bombing Range. Even at a very mundane level, innovation can sometimes feel annoying. Almost like an inconvenience, updates in products and processes can find slow adoption when it turns into a task. There is a significant difference between being forced to learn something, and learning as part of an evolving team.

In the eDiscovery industry, machinery comes in the form of digital platforms built for managing and understanding data. Before everything went digital, legal services incorporated a significant business for printing mountains of paper that supported a now painstakingly slow review process. When paper shifted to digital, the industry adapted and business models changed. Innovation created new service offerings and the supporting machinery assisted professional development through certification and a robust set of industry best practices. It’s the responsibility of service providers to have a competitive strategy in place that accounts for market forces and competitor positioning. New industry challenges are opportunities in disguise. The most innovative firms will either develop, source, or create partnerships that seek to solve these obstacles head-on.

Artificial Intelligence has brought a new level of change which is already disrupting traditional review tools. The last five years of improvements to machine learning have delivered a new breed of contextually accurate algorithms which supersede the human ability to comprehend and understand language at scale. This momentous leap forward has an enormous impact on the number of bodies required to complete a comprehensive and sound document review. A process that use to require utilizing hundreds of contract review attorneys, can now be achieve with a small fraction of those numbers.

This presents an opportunity to bring the contract review attorneys into the conversation, and identify new opportunities for work with the introduction of new tools and service lines. What skills are required? What are the other ways that AI could be trained on legal data? Is there opportunities to shift those with historically reactive roles to more proactive functions, training on existing data and turning it into AI models. After all, the skill set is one of tagging (or coding) documents. Would it not make sense to commission the skills of existing contract review attorneys, remove them from the costly business of traditional doc review, and insert them into law firms to take the vast amounts of historical data and turn it into models?

The traditional Luddite reaction would be to pick up a blunt instrument and begin smashing GPU’s. The modern Luddite would argue against the need for such tools, claiming that human beings are more effective at reading and understanding data. They might argue that we our specialist at understanding language, which makes us the exceptions, and not the rule. But the facts don’t add up. In 2017, Google boldly announced that machines had reached parity with humans at speech recognition, with a per-word dictation error rate of 4.9%. In 2018 Google created BERT, the most advanced deep learning natural language algorithm known to man. When they attached BERT to their search engine in 2019, it had a 10% improvement on all US based searches that year. BERT could understand both context and semantics.

This is not about taking jobs away from good people. This is about engineering a process where the same skills are combined with professional development pathways. It is about recognizing the individual roles which are most prone to automation, and growing their careers alongside AI.  

Chip Delany on Email
Chip Delany
Strategy Director at Lineal Services, previously worked as a strategist for Legal AI tech firm NexLP and before that as a consultant in continuous improvement and labor modelling. Australian National and US permanent resident.

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