1. Transparency and accountability
Hi, let's find out more about the importance of transparency and accountability principles for data ethics.
2. Transparency
Transparency in data ethics is about providing clear and easy-to-understand information on your data processing activities. Being transparent about how and why you collect, use, and share data is crucial to building stakeholder trust. It's essential to establish trusted lines of communication and engagements with your users and partners. There are many ways to implement the transparency principle in your organization. You can publish a privacy statement on your website, commission a third-party audit on your privacy processes, and have a clear plan to communicate when mishaps happen honestly.
3. Good example
Complicated privacy statements are useless for transparency since the target audience will not understand them. These statements should be concise, clear, and written in plain language that should be easily understood by a high-schooler.
BBC for instance has a very good privacy policy. It uses plain language and breaks down the data collection and usage in short declarative statements such as:
- "We'll only send you marketing emails if you've agreed to this."
- "You can delete your account. Your account information will be deleted immediately."
4. Don't hide or mislead
Transparency means that when an unfortunate event happens, like when a cyber attack compromises user data, don't hide the incident or mislead the users on its gravity. Have a robust communication plan with the affected parties, including customers and clients. You should advise them on the best course of action, like changing their passwords, your responsibilities, and their rights, assure them of the progress of your response measures, and provide them FAQs and channels to communicate their frustrations and seek answers. Owning up the mistake demonstrates accountability and builds trust.
5. Reality check
Before we dive into accountability in companies, let's see what companies think about data ethics. McKinsey, the leading management consultancy firm, gathered responses from 1,843 participants representing the full range of regions, industries, company sizes, and functional specialties on their data and AI practices. The results are not very promising, data ethics-wise. Only 30% of the respondents recognized the data ethics risks during AI adoption, only 17% have dedicated data governance teams with legal and risk professionals, and only 27% check for unbiased datasets in their data science projects. Without awareness of data ethics risks, companies will not understand what responsibilities they have to prevent and manage these risks, especially to embrace the accountability principle of data ethics.
6. What does being accountable mean?
Accountability can been seen as a core data ethics principle that helps implement all the other data ethics principles. It's an integral part of all data processing activities. An organization is also accountable to make sure that its third party collaborations also follow the same data ethics standards. Organizations are responsible for protection of personal data, individual rights, minimizing risks to individuals and society and to enhance the benefits.
7. Who is accountable?
So the question is, who is accountable? The easy and challenging answer is- everyone! Data ethics is not limited to a single department or function. Everyone in the organization, from data science teams, and compliance and risk divisions to IT systems managers and C-suite executives, has a role in implementing data ethics. Organizations should also consider the accountability just as their do for their social responsibility targets, in the form of corporate digital responsibility or CDR. It refers to a set of shared values and norms guiding an organization with respect to its processes related to digital technologies and data. These processes are related to assessing the impact of their digital assets such as data both to avoid risks and harm as well as to create benefits to the wider society.
8. Let's practice!
Awesome! Now let's go ahead and test your knowledge.