Blue J Legal is excited to announce the launch of its second product: Employment Foresight. Using machine learning algorithms, Employment Foresight helps lawyers, in-house counsel, and HR professionals gain rapid clarity on how judges decide contentious employment and labour law questions. The product addresses six legal issues: the length of the reasonable notice period, worker classification, constructive dismissal, cause for dismissal, managerial exemptions to overtime, and drug testing. We encourage you to share the news with colleagues and members of your network who may be interested.
Why we expanded into employment law
Employment and labour law issues are among the most costly and frequently litigated for Canadian companies. Between 2003 and 2013, 5.8% of employees between the ages of 18 and 64 were laid off annually (Statistics Canada). As a result, there are hundreds of cases each year addressing the amount of reasonable notice that a worker is entitled to receive upon termination. Workplace drug and alcohol testing is also an increasingly live issue for employers, especially in light of the proposed legalization of recreational cannabis. For example, in Suncor Energy Inc v. Unifor Local 707A, 2017 ABCA 313, a case that has resulted in a years-long legal battle, the Alberta Court of Appeal recently upheld Suncor's random drug and alcohol testing policy. Unifor has already indicated that it may seek leave to appeal to the Supreme Court of Canada. Employment Foresight will provide much-needed guidance and allow companies to reduce the risks and costs of litigating common employment law issues.
Game-changing technology Employment Foresight is the first tool to apply machine learning to the employment law context. Other available research tools serve only as “checklists” of factors considered by courts. However, these checklists offer no basis for how to weigh and make determinations in instances with competing factors. Employment Foresight collects and analyzes all the important factors from thousands of past cases and generates accurate predictions about how those factors may interact in new scenarios. The machine learning algorithms themselves reflect how judges weigh various considerations based on the underlying data.
Faster, more accurate decisions
Employment Foresight helps lawyers and HR departments resolve difficult employment law issues more confidently. For example, the Reasonable Notice Classifier predicts the length of notice a worker is entitled to receive with far greater precision and accuracy than traditional rules of thumb, as demonstrated by the following recent cases:
Want to see Employment Foresight at your firm?
See what our early adopters are saying
“Employment Foresight will make labour and employment law more accessible to legal departments, providing detailed explanations and expertise around highly specific employment scenarios. It will help to ensure that we are more confident in the legal advice we dispense to our business teams, and in our ability to do so more quickly, efficiently, and cost-effectively with minimal reliance on external counsel. But, perhaps its biggest value will be in positioning legal departments to make quick and confident risk assessments. Particularly in this era of constantly evolving business models. It won’t replace your outside labour and employment counsel. But, it will enable you to reduce your reliance on them where appropriate.”
—Mark Le Blanc, General Counsel at TVO
“I’m very impressed with the ease of use and practicality of Employment Foresight. The service condenses hours of research into useful commentary that only takes minutes to review and ensures that the latest and most relevant decisions are properly considered. The utility and benefits of the service are substantial.”
Employment Foresight in the news
- TechVibes: Blue J Legal Combines Law and AI with Employment Foresight
- Canadian Lawyer: Blue J Legal launches AI tool for employment law issues
- Legal Week: Top 20 Legal IT Innovations 2017: what is driving systemic change in the legal industry?