Organisations should make clear that employees working on and managing data projects are responsible for the ethics of their work. LOTI recommends including this as a responsibility or task in the job description for all new data jobs as a first step. These may take different forms depending on the job. For example:
Data practitioners, analysts and scientists: Manage the ethical risks and considerations of data projects, including elements of fairness, accountability, the law, moral dilemmas and other risks.
Data leaders: Develop a culture of data ethics and ethics skills within teams by creating time and space for staff to discuss ethics and embed it within their projects.
It is vital that there are data ethics competencies at different levels within an organisation, and that relevant staff know that they have to perform to a certain level with regards to data ethics. If the line manager of a data scientist (or the line manager’s manager) does not have sufficient understanding of data ethics, they will not be able to evaluate the performance of their employees.
As such, LOTI also suggests adding data ethics to performance indicators, but this will likely be a secondary step when sufficient organisational maturity is achieved to truly understand what ‘good performance’ looks like with regards to data ethics.