Ethical Government

In Building Ethical Organisations, Cerys Hearsey writes, in part:

Here are some of the most important steps that leaders and employees can take to ensure that grass-roots ethics and organisation-wide actions meet in the middle:

• Create psychological safety: if employees are safe to speak out, they will feel safe to stand by their principles. This is essential for creating an environment where questions can be asked about long term impact without the fear of long term consequences for careers.
• Explore long-term impacts in a dedicated sprint: building in an ethics sprint (or at least an ethical element to user stories) can help teams new to the concept of voice these concerns focus on long-term, unforeseen impacts.
• Gather signals from customers in real time: in the event of a breakdown inside the organisation, customers also act as an early-warning sensor network to issues and potential resolutions.
• Multi-disciplinary, diverse agile teams: different mental models and ways of working help combat groupthink and echo chambers around developing products and services.
• Transparent by default: challenging the need for closed communications, collaboration and co-operation communities is an excellent step towards ambient awareness across silos.

While not specifically written about government, these steps also seem like excellent ones to apply to public service culture.

I’ve been on the list of witnesses to speak to the Public Accounts Committee about open data for almost a year; when the committee finally meets to consider this issue, the core of my testimony will involve the suggestion that open data is not primarily a technical issue, but rather one of culture.

What Hearsey calls “psychological safety” is something largely missing from the public service, where the information one manages and controls is too often treated as trade secret; I’d like to see us move toward a culture where public servants are rewarded not for keeping the data safely hidden in the vaults, but rather for telling any and all, as often as possible, what they do, how they do it, the metrics they use to measure success and failure, and the data that describes their work product.