legal tech law machine learning tax law tax foresight employment law employment foresight

How Blue J Legal Keeps Tax and Employment Foresight Accurate and Up-To-Date

October 19, 2018 | by Monica Layarda

black-board-bright-226569At Blue J Legal, we recognize that the law is in a perpetual state of change. To keep our technology current, our team of legal analysts conduct a weekly round of classifier system testing and case law database updates. In September and October 2018, we added a total of 86 new cases to the Tax Foresight and Employment Foresight classifier and case finder database.

Worker classification, a major issue within both employment and tax law, featured prominently during this round of updates, accounting for roughly 15% of the recently added cases. Tax Foresight’s and Employment Foresight’s Worker Classification classifiers correctly predicted 12 out of the 13 newly added cases. The continuing relevance of worker classification issue within Canadian jurisprudence is perhaps unsurprising to many as it serves as yet another testament to the issue’s growing importance within the economy more generally, a trend we recently discussed.

Nevertheless, while virtually all businesses recognize the importance of accurately classifying their workers, accomplishing this objective can be elusive. As analyzed in greater depth here (tax) and here (employment), defining employment relationships involves a careful balancing act of various factors, none of which is solely determinative. The dividing line between an employee and an independent contractor becomes murkier when the key factors, including intent, control, ownership of tools, profit and loss opportunity, and the degree of integration, point in opposite directions. A recent tax case added to our system this month illustrates the challenge.

When Contractual Intent Isn’t Enough

In 2068193 Ontario Inc v. M.N.R., the worker in question was a mechanic for an automobile repair shop. When he commenced his employment, the worker signed a written agreement clearly specifying his status as an independent contractor. Consistent with the terms specified in the contract, the employer made no tax deductions on behalf of the worker, and the worker provided invoices to the employer. Further, the duration of the relationship considered was only 10 months, during which time the worker was free to work for other non-competitors. All of these facts tend to support an “independent contractor” finding.

Nonetheless, the Tax Court of Canada disagreed. It ultimately ruled that the actual relationship was best classified as employer-employee based on the employer’s exercise of control over the employee’s work schedule and repair tasks, the worker’s use of the employer’s facility and tools, and the worker’s lack of entrepreneurial opportunity for profit and loss.

This case shows that even a proactive approach to worker classification can often be insufficient to shield businesses from legal liability down the road. The good news is that Blue J Legal’s AI-powered technology offers a solution. Tax Foresight’s Worker Classification Classifier was able to predict the outcome of the above case with 89% confidence. 

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Testing Alternate Scenarios

Importantly, the classifier also allows users to adjust various factors and measure how these changes influence the outcome. For instance, if the worker in this case had been able to choose when to perform the repair task for the hirer, the confidence level for an “Employee” classification would be reduced to 57%. Additionally, if the worker also supplied his own tools and had flexible hours, the prediction would shift entirely to a finding of “Independent Contractor” with 69% confidence.

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Key Takeaways

Machine learning gives Tax Foresight the unprecedented ability to quantify the interplay between the various factors that go into classifying employment relationships. The software can help businesses and tax professionals conduct more thorough due diligence to minimize risks and, if litigation is unavoidable, help lawyers build the strongest arguments drawn from the most current cases searchable in our Case Finders. Learn more about our technology here.

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Tags: legal tech law machine learning tax law tax foresight employment law employment foresight

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