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Nobel Conference Project – Big Data

Nobel Conference Project – Big Data

For this discussion, I watched the video “Big Data drives our daily decisions and bake in bias?” by Talithia Williams. Williams (2021) focuses on various concepts about the use of machine learning to support the use of Big Data in decision-making. The concepts have helped me learn how Big Data is linked to various aspects of people’s lives, such as financial management and entertainment. For instance, I learned that brands such as Spotify and Netflix use Big Data for predictive modeling to influence customer decisions. According to Lamba & Madhusudhan (2022), predictive modeling focuses on creating a model that can predict new data values based on observations. Talithia Williams explains how Netflix uses predictive modeling to pool different elements together to get an idea of what the user may be interested in watching and uses other examples, such as how calendar apps use Big Data to notify a user about an appointment based on traffic data to justify her argument that big data affects people’s daily decisions thus creating a clear picture of the role of Big Data in human decision-making.

The second thing I learned from the video is that Big Data can create bias in decision-making. Talithia Williams explains how Big Data can lead to biased decision-making using an example of how a camera may make wrong assumptions because of the training of the algorithm used to program the camera. Williams (2021) further explains how machine learning can create bias using examples I could relate to, thus helping me understand the link between Big Data use and biased decision-making. The discussion also helped me learn that recidivism algorithms are often biased because they make wrong assumptions about the people who are likely to commit crimes and the importance of reviewing the accuracy of Big Data before using it in decision-making to avoid making decisions that could negatively impact businesses as observed in the example about Amazon. I also learned that algorithms may default when they are not trained on a diverse group of people, such as people from different backgrounds and ages.

Generally, I think the video was quite informative about the role of Big Data in decision-making in different aspects of people’s lives and how Big Data can lead to biased decisions. Using examples that I could relate to made it easier to understand the content in the video and gain more interest in learning more about Big Data. I also think that the images used in the video were essential in explaining the concepts discussed in a manner that anyone without knowledge of big data can understand. The content of the video also demonstrated the speaker’s experience with the use of Big Data. For example, the example about how Amazon was accused of using biased criteria to determine areas eligible for same-day delivery demonstrates that the speaker is well-informed about the relationship between bias in decision-making and Big Data based on something she has observed. I also think that the content in the video is reliable because the arguments made by the speaker are supported by concrete examples that can be found in articles and books written by other authors who have explored the concepts she discussed. Therefore, in conclusion, Talithia William’s video, Big Data Drives Our Daily Decisions and Bake in Bias? Is among the information sources that people interested in learning more about Big Data can use.


Lamba, M., & Madhusudhan, M. (2022). Chapter 8: Predictive Modeling. In Text mining for information professionals: An uncharted territory. Springer Nature.

Williams, T. (2021, October 5). Big data drives our daily decisions and bake in bias? | Talithia Williams | Nobel conference [Video]. YouTube.


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Nobel Conference Project

Nobel Conference Project

The goal of this project is to learn something about big data that you did not know before. For this project, you will watch at least one video presentation at Nobel Conference 57 hosted by Gustavus Adolphus College in 2021. You will report about (1) what you learned in the video and (2) your reaction to the content of the video.
Once you find a video from the conference that is of interest to you, watch the video and write two pages or more about what you learned in the video.
Personalize your paper, that is, relate what you learned to yourself: what did you learn? What do you think about it? What is your reaction to the content of the video?
You may want or need to do a little more research outside of the conference website for words/topics with which you are unfamiliar or for which you want to dig a little deeper.

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