Artificial Intelligence for strategic EHS management

Trevor Bronson, Director, Portfolio Strategy at Intelex explores the challenges and opportunities of using AI in EHS.

Credit: Alamy Stock

EHS, at its core, is an information-based discipline. The information takes many forms – it could be the calculation of complex KPIs, ensuring emissions fall below a permitted threshold, logging training completion rates or assessing the number of observations recorded across multiple sites. Whatever the info, the reality is that EHS professionals are over-burdened by administration and struggle to find time to operate strategically.

Fortunately, new technologies like artificial intelligence (AI) are helping to alleviate these issues. AI can help EHS professionals identify issues without ever seeing them, understand trends without running manual analysis and implement solutions they might not otherwise consider.

Nevertheless, despite the evident advantages of using AI-driven solutions, many organisations remain sceptical about AI’s capacity to comprehend, interpret and organise critical information that drives performance and ensures compliance.

Challenges

• Data privacy and security: AI requires large amounts of data to function effectively. In EHS this could involve sensitive information about individuals’ health, safety, incidents and environmental data. Ensuring the privacy and security of this data while utilising it for AI applications is top of mind.
• Bias and fairness: Fairness and equality is critical for all businesses, yet AI systems can inherit biases present in their training data or algorithms, which could result in unfair decisions. Efforts must be made to identify and mitigate biases in AI models to ensure equitable outcomes.
• Regulatory compliance: EHS is governed by several regulatory bodies around the world. If AI will be sued to ensure compliance, the AI needs to be aware of the dynamic nature of rules and regulations.
• Human-AI collaboration: Balancing the capabilities of AI with human expertise and ethical decision-making can be a challenge, particularly when these recommendations conflict with human intuition. Who has the final say? If it’s the AI, does that render the employee irrelevant?
• Data quality and integration: Data is the lynchpin of AI effectiveness. However, siloed, unstructured and messy data makes realising the full value of AI for EHS difficult. AI operates on the principle of “garbage in/garbage out,” which makes data quality a critical component of an effective AI program. With EHS data often being complex, dispersed and of varying quality, integrating and cleansing data for AI use can be time consuming and resource intensive.

Opportunities

• Risk assessment and prediction: AI can analyse vast amounts of historical data to proactively identify patterns and predict risk based on conditions that have contributed to incidents in the past. This can help to prevent accidents and mitigate environmental damage by correcting problematic situations before they result in negative outcomes.
• Efficient monitoring and reporting: With AI capable of processing huge amounts of data – much more than any one person – there is massive efficiency potential. AI-powered sensors and monitoring systems can also continuously track environmental parameters and workplace conditions. This data can be used to generate real-time reports, enabling faster responses to incidents and faster time to analysis
• Automated compliance monitoring: AI can assist in monitoring regulatory compliance by analysing internal compliance-related data while simultaneously scanning the regulatory horizon for relevant changes. This can help avoid fines and legal issues.
• Enhanced decision support: AI provides data-driven insights to help EHS professionals make informed decisions and supports managing complex scenarios with multiple variables and potential outcomes. By helping safety professionals make better decisions based on data, AI contributes to creating a safer workplace for frontline workers.
• Educating the future workforce: When new EHS leaders take over, they lack the organizational context of decades of EHS information – context that can be especially useful when facing difficult situations for the first time. AI can deliver these leaders the right information at the right time so they can make decisions with maximize context regarding what worked, what didn’t, what it cost, what it did to risk and so on.

Intelex has recently announced its partnership with Computer Vision company Protex AI, a platform that uses AI to enable proactive organizations to gain greater visibility of unsafe behaviours in their facilities.

Find out more…

Click here to watch an on demand SHP webinar with Intelex’s Scott Gaddis entitled, Increase Safety Engagement for Frontline Workers: How to Unlock a Culture of Safety with Mobile Digital Devices.<