Inclusive Research Methods

Researching people and social contexts is tricky, to say the least! As a researcher, I feel obligated to stay ethical in my research practices. A large part of ethical research methods while researching people and their experiences, is to seek inclusive tools and methods to understand various data-sets and their sources holistically.

Remember:

• People trust numbers, but love to hear a story.

When working with people data, going beyond the numbers is crucial while drawing inferences. This is especially true for data-driven decision-making. Inferring with empathy and context-specific understanding help draw meaning from data that mere statistics and predictive analytics cannot.

• There is bias hidden in your analytics.

We often think of numbers and algorithms as synonymous to logic, ground truth, and unbiased. Although numbers and algorithms in themselves may be mathematically thought of as unbiased, their usage on human data allows bias to creep in. For example, think about training a machine learning algorithm to predict employee engagement, the bias here is from the training set that the algorithm was tuned using. If your training data does not have adequate representation, your algorithm is naturally biased against the minority inputs to it.