What does it mean when we say that important parts of something can be lost when it is datified? For a definition of datafication, watch the video I posted on Local Data or look up datafication on the web.
Please post your understanding of what might be lost in the datafication process. What elements can get lost when we take a real experience or phenomenon and turn it into a data set? And, in what ways is the data not an accurate representation of the experience of phenomenon that it is meant to represent? Use of examples would be strongly encouraged.
Post your initial response latest by end of day on Friday. Then post replies to at least two other students’ posts:
1. Datafication is a new form of value when it comes to applying technology to every aspect of our lives and turning that information into data. It is the process of collecting, tracking, analyzing, and optimizing information for storage in digital form. Datafication is truly a significant process as it helps define core business operations through a global reliance on data, especially for companies striving to remain competitive. With the huge amount of data generated after encoding and extracting chaotic information into valuable insights, datafication presents that information in a way that is useful to help human decisions after filtering information.
However, datafication has also sparked worries about personal data exploitation and privacy. When we assert that when something gets datafied, significant portions of it may be lost, it is the context, nuance, complexity, and important details of a phenomenon. Because the datafication process is often brief and objective, real-life phenomena and human experiences are often omitted, leading to incomplete and inaccurate analysis. This affects decision-making during the analysis due to limitations and biases of the data. For example, when a school datafies scores on students’ tests to assess a student’s ability and intelligence to show the number of students who will graduate with distinction, external factors that can impact students’ grades such as learning environment, academic spirit, and personal issues will be ignored. This causes the final result to be inaccurate and ineffective.
2. According to my understanding datafication refer to the process of turning real-life experiences into sets of numbers and other quantifiable data points. While this can be useful in many ways, it can also cause us to lose important contextual information and miss the complexities of the original experience. A perfect example to me would be this, if we rely solely on data points such as weight and blood pressure to assess a person’s health, we might miss other Important factors such as their mental health and quality of life. These are not easy to quantify, but they are very essential to understanding a person’s general well-being.
Another example would be, social media platforms like Facebook, TikTok and Instagram that collect data about users’ behavior and preferences through algorithms, but this data does not capture the full complexity of human social interactions, such as facial expressions and tone of voice. The most Important thing I learnt through my search was that datafication can result in inaccurate or biased representations Therefore, it is important to be mindful of the limitations of data and to use multiple sources of information to get a more complete picture.
