What Is Data Ethics?

A business may be allowed to collect data without every possible use of that data being appropriate. Should it infer sensitive information from a customer’s purchases? Upload internal files to an AI tool? Make a hiring decision using a model whose criteria no one can explain?

Data ethics helps organizations answer these questions. It examines how collecting, using, sharing and retaining data affects people. Alongside legal requirements, it asks a practical question: Is this use of data justified, transparent and fair? Statistics Canada similarly describes data ethics as addressing the appropriate use of data.

Why does data ethics matter?

Data can help businesses understand customer needs, improve services and make better decisions. But its use can also create risks, including privacy breaches, unauthorized access, inaccurate conclusions and decisions that unfairly disadvantage certain groups.

An ethical approach helps a business identify these risks before a project launches. It also supports trust: customers and employees are better able to understand what information is being used, why it is needed and how it is protected.

These questions are especially relevant when a business plans to introduce artificial intelligence into its operations. An AI tool’s output depends in part on the data it uses and on how people act on its responses.

What are the principles of data ethics?

Collect only what you need

Before requesting information, establish what you will use it for. The fact that data is available does not mean it is necessary or appropriate to collect.

For example, a business needs certain contact details to send an invoice. It should be able to explain why it would also request information that has no apparent connection to the transaction. In Québec, necessity is also a key consideration when collecting personal information.

Explain how the data will be used

People should be able to understand what information is collected, why it is collected and who it may be shared with. Clear explanations help them make informed choices and reduce the gap between what they expect and what a business actually does.

Consent is only part of the assessment. Depending on the circumstances and applicable law, an organization must also consider whether the information is necessary, whether the proposed use matches the stated purpose, and what conditions apply to its use or disclosure.

Protect data throughout its life cycle

Security is part of responsible data use. Appropriate safeguards depend on the sensitivity of the information and the risks involved. They may include access controls, multifactor authentication, encryption, backups, vendor oversight and retention rules.

Businesses should also know who can view or change their data and remove access when it is no longer needed. A secure data environment for AI can help organizations manage information classification, permissions and the use of internal data in AI tools.

Check data quality and the fairness of outcomes

Incomplete, outdated or unrepresentative data can lead to poor conclusions. When data is used to screen job applicants, assess requests or tailor offers, businesses should also consider whether the results could unfairly disadvantage certain groups.

For example, a model trained mainly on existing customers might overlook the needs of a new customer group. Testing results, documenting limitations and requiring human review for consequential decisions can help reduce that risk.

Make someone accountable

A policy has limited value if no one knows who approves a new use of data, corrects an error or responds to a concern. Organizations need clear responsibilities and ways to monitor how their rules are applied.

That is where data governance comes in. It establishes the roles, policies and processes needed to put ethical principles into practice.

Data ethics and compliance: What is the difference?

Compliance means meeting applicable legal requirements. In Québec, businesses must consider the rules governing personal information, including changes introduced by Law 25. The European Union’s GDPR may also apply to some activities, but it is not the default legal framework for every Québec business.

Data ethics asks an additional question: what might happen as a result of this use of data? A practice can raise concerns even when consent has been obtained. Would people reasonably expect their information to be used this way? Is the data reliable enough for the decision being made? Are the potential benefits proportionate to the risks?

How can a business put data ethics into practice?

Start with one specific use of data, such as an HR dashboard, a customer segmentation tool or an AI agent. Then ask five questions:

1. What is the purpose? Identify the decision or service the data is meant to support.

2. What data is necessary? Leave out information that does not serve that purpose.

3. Who could be affected? Consider the possible effects on customers, employees and others.

4. What safeguards are in place? Review access, security, data quality and retention.

5. Who reviews and corrects the results? Assign responsibility and establish a way to address errors or complaints.

These questions can become part of the organization’s broader data governance practices.

Use data responsibly

Data ethics helps businesses choose worthwhile uses for their information, understand the possible consequences and set rules their teams can follow. A practical starting point is to define the purpose of each data project, limit the information used and review the effects of the resulting decisions.

Mallette’s team can help you strengthen data governance and establish clear practices for using information in your digital projects.