Introduction
Autonomy
Transparency
Non Maleficence
Justice
Beneficence
Takeaways
Non Maleficence

Justice

We stand up for justice in our digital offerings.

We acknowledge that justice is a fundamental component of human-centered digital offerings. That is why we want to distribute our digital resources fairly and prevent discrimination. Specifically, we think and act according to the following three principles:

We actively combat prejudice in our digital offerings.

Anytime data is collected or used, bias may be present, distorting results. Such bias arises from cultural and personal beliefs and life experiences. We should always be aware of prejudices in our digital offerings and incorporate diverse perspectives and data sources to minimize their influence on our processes.

Impartiality

We ensure equality in and through our digital offerings.

We want to use data and algorithms to achieve not only economic but also social benefits. That's why we contribute to equal opportunities. How do we do that? By making sure users can benefit from our digital offerings without being hindered by prejudices, preferences, or other unfair barriers. In addition, we demand the same from the digital services of third parties we use in our own business.

Equality

We are committed to proportionality in both data collection and use.

The collection and use of data should be proportionate. This means that data should be purposefully collected and used as part of data project. In other words, we should only collect essential information. Where data influences our decision making, we also recognize the limitations of the data and check that we do not make hasty, disproportionate decisions.

Proportionality

Meet Linda

Linda is a sales and marketing intern working to optimize customer satisfaction.

Recently, she read some articles about best practices for strengthening customer relationships.

A few times, these articles mentioned the idea of providing customers with valuable and meaningful data insights (for free).

This idea inspired Linda, and she started working on a pitch for her boss. In this pitch, she proposes to share insights in the form of short infographics with the managers and decision-makers who work for our clients.

To create these insights and the accompanying infographics, Linda will need to analyze customer data and research current market trends.

(multiple answers possible)

However, not all data are made equal. For Linda's statements to be universally valid and avoid bias,

the customer data must be diverse enough.
the customer data must only come from a few main customers.
it doesn't matter how old the data is.
the research on external market trends must be high quality.
Submit

Please complete the quiz above to move on. Select the correct answers and then click on submit.

Linda is careful not to inadvertently introduce bias into her insights and selects her data sets diligently.

She also pays attention to the principle of proportionality. After all, the data represent real customers. That's why she only uses data that is essential for her project.

What do you think?

Since managers and key decision-makers are the target audience for her infographics,

Linda doesn't mention any limitations to her methodology. This additional information would make the infographic too cluttered and distract from the key findings.
A
Linda is extra careful about mentioning the limitations of her data analysis. The insights could be used to support decision-makers and, therefore, have a significant impact.
B

Please answer the question above to move on.

Linda has taken the time to think about the many implications of her seemingly straightforward project. In addition, she has considered the principles of digital ethics. This approach has enabled her to create stunning infographics with valuable data insights. These insights are based on sound data and reasoning. As a result, they are reliable and applicable in almost any scenario. In other words, they are truly helpful to our customers.

Hats off to Linda!

Next lesson
Beneficence