2026 Community of Human and Organizational Learning 32nd Annual Conference

Part 1 of 2

Most organisations are very good at investigating events. Far fewer are genuinely good at learning from them.


Too often, events trigger a familiar cycle: find the failure, identify the error, write the report, assign the actions, close it out. The language may sound modern, the process may look polished, but the outcome is often the same — shallow insight, predictable fixes, and missed opportunities to understand how work was really happening.


This 4-hour workshop is designed for people who already know the language of human performance and want to sharpen the practice. It focuses on one of the most persistent challenges in our field: how to learn from events in ways that move beyond hindsight, bias, blame, and investigation theatre.


Together, we will explore what gets in the way of meaningful learning after failure, disruption, and surprise, and what it takes to generate richer understanding in the real world of organisational pressure, competing agendas, and the need to “get to the answer.” The session will introduce practical tools and approaches for gathering better contextual data, exploring work as done, understanding local rationality, and producing outputs that are useful, credible, and capable of driving better decisions.


This is not a workshop about making investigations slightly better. It is about rethinking what we are trying to achieve after an event, and building the skills to do it in a way that people actually learn from.


If you have ever looked at an investigation and thought, “We still do not understand what really mattered here,” this workshop is for you.

Part 2

Most organisations are very good at investigating events. Far fewer are genuinely good at learning from them.


Too often, events trigger a familiar cycle: find the failure, identify the error, write the report, assign the actions, close it out. The language may sound modern, the process may look polished, but the outcome is often the same — shallow insight, predictable fixes, and missed opportunities to understand how work was really happening.


This 4-hour workshop is designed for people who already know the language of human performance and want to sharpen the practice. It focuses on one of the most persistent challenges in our field: how to learn from events in ways that move beyond hindsight, bias, blame, and investigation theatre.


Together, we will explore what gets in the way of meaningful learning after failure, disruption, and surprise, and what it takes to generate richer understanding in the real world of organisational pressure, competing agendas, and the need to “get to the answer.” The session will introduce practical tools and approaches for gathering better contextual data, exploring work as done, understanding local rationality, and producing outputs that are useful, credible, and capable of driving better decisions.


This is not a workshop about making investigations slightly better. It is about rethinking what we are trying to achieve after an event, and building the skills to do it in a way that people actually learn from.


If you have ever looked at an investigation and thought, “We still do not understand what really mattered here,” this workshop is for you.

The Art and Science of Decision-Making; The attention on our team members and their decisions seems to be greater today than in many years past. The demand to make “the right” decision is the loud voice right now and yet is tragically misguided in so many ways. Human interactions under stress will never yield a perfect right or wrong outcome. Trainers, leaders, attorneys and all involved in the process of preparing and evaluating  events need to understand what actually takes place and contributes to decisions under stress. This session will break apart the science we know today on decision making and how working the “art” of assisting that process may eventually lead to more ideal outcomes where possible.  We will frame this discussion from the lens of the police world but relate it to any of our industries where there are real stakes whether they are financial, product or people.

Traditional occupational health systems often emphasize compliance, reactive metrics, and error prevention. This session will explore the adoption and integration of Human and Organizational Performance (HOP) operational learning tools like: Proactive Reporting, Leadership Walk & Talks and Learning Teams to drive organizational culture and operational excellence. Attendees will gain new insights into practical strategies for piloting these tools across diverse organizational settings to open proactive mindsets around safety performance, regulatory compliance, and continuous improvement.

Organizations with limited resources often assume meaningful HSE improvement requires new programs, technology, or headcount. In reality, some of the most effective improvements come from better leadership behaviors, clearer priorities, and stronger system design. This session challenges the myth that progress requires capital and demonstrates how Human and Organizational Performance (HOP) can drive real results in scrappy, fast-moving environments.


Grounded in real-world experience, the session explores why traditional, compliance-heavy approaches often fail to prevent serious incidents in resource-constrained organizations and how a human-centered HOP approach provides a practical alternative. Participants are introduced to core HOP principles—learning from normal work, understanding variability, and designing systems that support people under real conditions—in ways that are immediately applicable.


A key focus is serious injury and fatality prevention through identification and strengthening of critical controls, using simple, no-cost risk assessment techniques. The session also highlights leadership behaviors that influence trust, learning, and culture without formal programs or additional resources. Participants will leave with practical tools and zero-cost actions they can implement immediately.

Artificial Intelligence is already drafting risk assessments, analysing incident data, generating safety communications, and automating assurance workflows. But does that trajectory end with AI supporting safety practice—or replacing it? This double breakout session uses a structured, high-energy debate format to test that question in real time, separating hype from operational reality and exposing what “replacement” really means in complex sociotechnical systems.
In the first 50-minute session, participants will nominate as speakers and be randomly allocated to either the Affirmative (“AI will replace the Safety Practitioner”) or the Negative (“AI will not replace the Safety Practitioner”). Teams will rapidly build their case using guided prompts and fast research, while the rest of the room engages in a facilitated, interactive discussion to surface assumptions, evidence, risks, and ethical boundaries. Together we will map the strongest arguments on both sides—covering capability, accountability, regulation, human judgement, leadership, organisational learning, and the messy realities of work-as-done.


In the second 50-minute session, the room becomes a formal debating chamber. Teams deliver timed opening statements, structured rebuttals, and closing arguments, supported by a timekeeper and clear rules of engagement. The audience acts as adjudicators, voting on the winner and sharing the reasoning behind their decision. The facilitator will officiate, synthesise themes, and provide feedback—connecting debate insights to practical implications for the safety profession: what to automate, what to augment, what to protect, and what new capability the next generation of safety practitioners will need.


Participants will leave with a sharper, evidence-informed view of AI’s realistic role in safety—and a clearer line between tasks that can be mechanised and responsibilities that must remain human-led.

Artificial Intelligence is already drafting risk assessments, analysing incident data, generating safety communications, and automating assurance workflows. But does that trajectory end with AI supporting safety practice—or replacing it? This double breakout session uses a structured, high-energy debate format to test that question in real time, separating hype from operational reality and exposing what “replacement” really means in complex sociotechnical systems.
In the first 50-minute session, participants will nominate as speakers and be randomly allocated to either the Affirmative (“AI will replace the Safety Practitioner”) or the Negative (“AI will not replace the Safety Practitioner”). Teams will rapidly build their case using guided prompts and fast research, while the rest of the room engages in a facilitated, interactive discussion to surface assumptions, evidence, risks, and ethical boundaries. Together we will map the strongest arguments on both sides—covering capability, accountability, regulation, human judgement, leadership, organisational learning, and the messy realities of work-as-done.


In the second 50-minute session, the room becomes a formal debating chamber. Teams deliver timed opening statements, structured rebuttals, and closing arguments, supported by a timekeeper and clear rules of engagement. The audience acts as adjudicators, voting on the winner and sharing the reasoning behind their decision. The facilitator will officiate, synthesise themes, and provide feedback—connecting debate insights to practical implications for the safety profession: what to automate, what to augment, what to protect, and what new capability the next generation of safety practitioners will need.


Participants will leave with a sharper, evidence-informed view of AI’s realistic role in safety—and a clearer line between tasks that can be mechanised and responsibilities that must remain human-led.