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Sidney Dekker Masterclass Series

14/07/2021 12:00pm to 1:30pm

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Buy tickets online

Ticket Type Ticket Price Quantity Subtotal

NZISM Member

$100.00

Public ticket plus membership to 31.03.2022

$475.00


Information

For enquiries, contact cpd@nzism.org

Please note, once you purchase a ticket you will be emailed the link to register for the Zoom webinar.

If you wish to purchase 5 or more tickets to the event please contact admin@nzism.org


Click here for full details on the 4-part series


Masterclass 1

Understanding 'Human Error'

We have long seen ‘human error’ as a major cause of trouble—as if we’re the custodians of basically safe systems that simply need to be protected from erratic, unreliable human behavior. With tighter procedures, a focus on compliance, technology, surveillance and supervision, we think we can contain an acceptable bandwidth of human performance.

In this masterclass, you will learn that the label ‘human error’ has been a counterproductive attribution, a judgment we make after the fact, ever since human factors and safety scientists started to study it seriously. Some 80 years ago already, the science showed that ‘human error’ is systematically connected to features of people’s tools, tasks and operating environment. The human performance some call ‘error’ is information about how people have been set up for success (or not) to cope with the complexities and contradictions of real work.

You will learn that a ‘human error’ problem is at least as complex as the organisation that helps bring it forth, and that with a better understanding of the messy details of people’s daily practice, you can find the adaptive capacities that actually make things go right despite ever-present goal conflicts and resource constraints.


No register, no view

The Sidney Dekker masterclasses will be recorded. However:

  1. they can only be watched by those people who have paid and registered for the Masterclass series, and
  2. they will be only be accessible for a period of one month.

Venue

Zoom Webinar