Harnessing Artificial Intelligence for Labour Market Insights
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How the Labour Market Information Council is exploring artificial intelligence to support the labour market information ecosystem
With advancements in computing infrastructure, deep learning, and natural language processing, artificial intelligence (AI) is transforming industries worldwide, and the labour market information (LMI) sector is no exception. At the Labour Market Information Council (LMIC), we are in the early stages of exploring how AI and other emerging technologies can enhance our work in labour market data collection, analysis, and reporting.
AI already influences how data is collected and analyzed in other sectors, and it holds enormous potential for improving data insights and tools in the LMI space. Organizations like LMIC must take steps to ensure the technology is integrated responsibly. In this blog post, we’re sharing an inside look at how we’re embracing AI to support the LMI ecosystem while addressing data quality, ethics, and transparency considerations.
AI, which involves the development of intelligent systems, software, or algorithms capable of recognizing and responding to their environment, is revolutionizing how we collect, analyze, and interpret data (Castro & New, 2016).
Why AI matters for labour market information (LMI)
AI offers powerful ways to reshape how labour market data is collected, analyzed, and shared. For organizations like LMIC, where we handle large amounts of workforce data, AI can enable deeper insights while improving data accuracy and supporting the creation of tools that will make LMI more accessible to Canadians.
But adopting AI is about more than just implementing algorithms—it’s also about serving the needs of policy-makers, researchers, and the public while upholding the highest standards of trust and responsibility. This is underscored by Canadians’ skepticism about the use of AI technologies: a recent survey found that only 31% of Canadian respondents trusted these technologies—a full 19 percentage points lower than the global average. The same survey showed that 48% of Canadian respondents turn to online searches to find trusted information about new technologies and innovation, highlighting the importance of clearly communicating AI’s benefits and building public trust.
Recognizing these challenges, the Government of Canada has taken a leadership role in promoting the responsible use of AI through initiatives like the guidelines on its Responsible Use of Artificial Intelligence webpage and Canada’s Digital Charter. These efforts reflect the government’s commitment to transparency, accountability, and fairness in the use of AI technology. LMIC’s exploration of AI’s potential in the LMI sector aligns with these principles. We are working diligently to ensure our approach respects ethical standards and fosters stakeholder trust.
LMIC’s approach to integrating emerging technologies
As we explore AI’s potential in the LMI context, our approach is focused on building the right infrastructure first. Over the past few years, we have focused on developing data pipelines and frameworks that position us to explore AI effectively in the context of our work. This approach ensures that any integration of AI into our processes is done thoughtfully and with a focus on data quality and the needs of our stakeholders in mind.
In one of our upcoming projects, we applied machine learning algorithms to analyze online job postings and identify patterns in skill requirements across different occupational groups. While we aren’t yet developing AI tools ourselves, this project demonstrates how we are starting to test and validate AI’s potential to support more comprehensive labour market analyses.
Building infrastructure to reinforce data accuracy and accessibility
At LMIC, we prioritize data quality, reliability, and accessibility. Our commitment to these principles involves ongoing efforts to refine our data processes, address emerging challenges, and ensure our tools are trustworthy and effective. In recent years, we have strategically focused on building big data capabilities and implementing the frameworks necessary to support our research and analytics capacities. This groundwork will enable us to better evaluate the potential for AI integration into future projects, ensuring that any new technology adoption aligns with our commitment to providing high-quality LMI.
One of the core components of our data strategy is the development of a data warehouse designed to ingest, curate, and standardize labour market data from different sources while also addressing common challenges in the ecosystem, including relevance, access, and interpretability—factors that have historically impeded effective labour market analysis. By centralizing data from trusted sources like Statistics Canada and Vicinity Jobs, we can ensure that our analyses are based on reliable and up-to-date information.
How LMIC is working to consistently meet industry standards
We have established several processes to ensure that we meet industry standards consistently:
Standardized Procedures
We have set up standardized procedures for data collection, storage, and processing in our cloud environment. This ensures that data is treated uniformly and subjected to quality checks at every stage.
Data Partnerships
We work with trusted data from Statistics Canada and Vicinity Jobs, both of which adhere to high standards for data quality and robust security protocols.
Process Refinement
We regularly refine and improve our internal data processes to keep pace with advancements in data management technology. This commitment is reflected in our efforts to standardize data processes, implement privacy safeguards, and maintain the integrity of our analyses.
Comprehensive Documentation
We strive to maintain comprehensive documentation to monitor data adjustments and changes in inputs, allowing us to clearly explain any modifications.
By emphasizing transparent documentation and explainable outputs, we aim to strengthen stakeholder confidence and provide clear, reliable insights.
Leveraging Data Infrastructure to Deliver Real-Time Labour Market Insights
Through a project funded by the Future Skills Centre, LMIC has developed the data infrastructure to support tools like our Canadian Job Trends Dashboard. The dashboard aggregates data sources, provides timely updates, and makes high-quality labour market data easily accessible. This demonstrates how LMIC’s data infrastructure enables us to work with diverse, quality data sources to deliver accessible and actionable labour market insights.
Balancing AI exploration with ethics and data security
We are mindful that while there are potential uses for AI in the LMI sector, there are also ethical and security challenges. While LMIC is not actively developing or deploying AI tools, we are committed to ensuring that our partners and the tools we work with uphold high standards for data quality, privacy, and ethical responsibility.
One of our key data partners, Vicinity Jobs, exemplifies these values by using AI algorithms transparently to process and analyze online job postings. They uphold industry standards by being clear about their methodologies, the data they use, and their approach to data collection, processing, analysis, and reporting. Their commitment to transparency and ethical practices has made them a trusted data partner for Canadian organizations, municipalities, and government departments. To learn more about their approach, see here.
Our 2023 feedback-gathering exercise (completed in collaboration with Statistics Canada), our 2018 public opinion research, and our 2022/23 research focused on career development professionals emphasized the critical role of trust in the delivery of LMI that users seek when making decisions. When working with AI tools, following specific AI and overall technology standards is critical. These standards ensure the accuracy and fairness of models while maintaining the integrity of the data produced. To build trust in AI-driven tools, it is essential to prioritize transparency and accountability in data processes. This includes validating responses, tracking potential biases in models, and ensuring that outputs are trustworthy and equitable.
What’s next: AI’s role in labour market innovation
Looking ahead, we will continue exploring how AI and emerging technologies can transform labour market data. Our upcoming research report will provide a deep dive into how AI and new technologies could shape the future of LMI. The report will provide practical recommendations for how AI can be integrated into LMIC’s systems, highlighting best practices for ethical AI use and data management.
This report will not only detail our findings but also offer guidance for the broader LMI ecosystem on how to navigate the challenges and opportunities posed by AI. Our goal is to help the sector adopt AI in ways that are responsible, secure and beneficial for all stakeholders.
Lorena Camargo
Principal researcher
Lorena Camargo contributes to contemporary, forward-looking research projects about labour market issues in Canada. Her expertise includes innovation policy and global markets.
Sukriti Trehan
Data scientist
Sukriti Trehan contributes to building the data architecture for LMIC and provides analytics solutions for ongoing Canadian labour market projects. Her work with the organization aims to facilitate easy access to structured and unstructured labour market data.
References
Castro, D., & New, J. (2016). The promise of artificial intelligence. Center for Data Innovation. https://www2.datainnovation.org/2016-promise-of-ai.pdf