Published In
Americas Conference on Information Systems (AMCIS 2021: Digital Innovation and Entrepreneurship)
Document Type
Conference Proceeding
Publication Date
8-2021
Subjects
Algorithms -- Social aspects, Data Science -- methods
Abstract
With the explosion of data, analytics and artificial intelligence, information systems research focuses on the use, management and consequences of algorithms. This far, only a handful of papers offer insights into how algorithmic solutions work. To address this gap, we studied the code making up 45 public data science Jupyter notebooks containing algorithmic solutions developed to predict customer churn in a credit card dataset on a data science platform Kaggle. com. We synthesized a process model of an algorithmic solution: preparing the environment, reading in data, cleaning data, exploratory data analysis, pre-processing the dataset, building and training the model, and testing and validating model. Unboxing the algorithm and investigating the process offers a more fine-tuned understanding and language to better conceptualize the use, management and consequences of algorithmic solutions. It also provides a scaffolding for research into the development of algorithmic solutions, highlighting their variability, experimentation and data scientist decisions.
A video of the presentation is available online:
https://aisel.aisnet.org/amcis2021/art_intel_sem_tech_intelligent_systems/art_intel_sem_tech_intelligent_systems/19/
Rights
This is the accepted manuscript version of a conference paper. Final version copyrighted © by Association for Information Systems. Authors retain copyright for material published as part of AIS conference proceedings.
Persistent Identifier
https://archives.pdx.edu/ds/psu/37040
Citation Details
Stelmaszak, M. (2021) Unboxing the Algorithm: A Process Model of an Algorithmic Solution. Americas Conference on Information Systems 2021, 9-13 August 2021.