97 Things About Ethics Everyone in Data Science Should Know

Chapter 42. The Ethical Data Storyteller

Brent Dykes

Author and Senior Director, Insights & Data Storytelling, Blast Analytics

When the topic of data science and ethics is discussed, data privacy and bias in machine learning are often at the forefront of people’s concerns. It can be unsettling to think that your personal data could be misused by companies, or that algorithms could perpetuate race-, gender-, or age-based biases. However, if we step back and evaluate the entire data life cycle, we find ethics can influence everything from how we collect data to how we use it to make decisions. A principled approach to analytics is needed at every stage in this data life cycle, including the “last mile” of analytics where key insights are shared or communicated with audiences.

As the need to convey insights to others in an effective manner has grown, many people have shown interest in data storytelling, in which key insights are visualized and presented in a compelling narrative format. However, some data professionals are still skeptical and uncomfortable with storytelling’s role in communicating findings. Stories are often associated with entertainment, fiction, and fluff—leaving some people to view storytelling as subjective and superficial. Others may recognize the persuasive power of narrative but feel it can compromise the integrity of the facts. For these reasons, some individuals ...