The Human Side of Data Science Yasmeen Shorish

The Human Side of Data Science Yasmeen Shorish Associate Professor and Data Services Coordinator JMU Libraries November, 5, 2018

What is Data Science? “Data science is a "concept to unify statistics, data analysis, machine learning and their related methods" in order to "understand analyze actual phenomena" with data. ” – Wikipedia “While many university programs now offer a data science degree, there exists no consensus on a definition or suitable curriculum contents. ” – Wikipedia

“Data science is a "concept to unify statistics, data analysis, machine learning and their related methods" in order to "understand analyze actual phenomena" with data. ” What do we say it is? “Data scientists examine which questions need answering and where to find the related data. They have business acumen and analytical skills as well as the ability to mine, clean, and present data. ” “[D]ata science spans a broader array of activities that involve applying principles for data collection, storage, integration, analysis, inference, communication, and ethics. ” https: //en. wikipedia. org/wiki/Data_science https: //datascience. berkeley. edu/about/what-is-data-science/ https: //www. nap. edu/catalog/25104/data-science-for-undergraduates-opportunities-and-options

The raw material in data science is you! (sort of) The business of data science Your data is continuously harvested, packaged and sold to companies for market development As a data scientist, ask yourself how the data collection methods: 1) matter to you, personally and professionally 2) matter to your research design

Are data collected in bias-minimizing ways? Without harm? With transparency? Are biases noted in associated documentation? Data collection, statistics, algorithms ASA’s “Ethical Guidelines for Statistical Practice. ” Approved April, 2018 ACM’s “Code of Ethics and Professional Conduct. ” Approved June, 2018.

What issues?

What does this mean? § Systemic power dynamics are codified in algorithms (i. e. status of women on the Internet) § Individual interactions with technology affect product development when considered at scale. § Marginalized populations continue to be marginalized in the marketplace, yet may be overrepresented in surveillance http: //www. pewinternet. org/2017/02/08/code-dependent-pros-and-cons-of-the-algorithm-age/pi_2017 -02 -08_algorithms_0 -01/#

https: //www. scientificamerican. com/article/the-harm-that-data-do/

https: //www. weforum. org/agenda/2018/10/how-should-autonomous-vehicles-be-programmed

http: //fortune. com/2017/09/15/election-data-democracy/

Using Data to Motivate https: //www. forbes. com/sites/audreymurrell/2018/07/31/pushing-the-ethical-boundaries-of-big-data-a-look-at-chinassocial-credit-scoring-system/#4 efc 13 b 325 e 5 https: //www. businessinsider. com/video-china-train-warns-citizens-to-behave-for-social-credit-system-2018 -10

An evolving field https: //www. siliconrepublic. com/advice/data-analytics-accenture-open-house https: //sdsi. stanford. edu/about/data-science-humanity

§ Ethical data science needn’t come at a market cost § There are more tools available to help navigate the space § The winds of industry are changing and in conflict, e. g. Apple and Microsoft vs Google and Facebook

How to prepare? Consider philosophy, technology and society, gender studies, and African-American studies courses to supplement data science courses Algorithms and methods are changeable! Consider how you would improve existing processes to be more human-centered Data scientists are often a part of a larger project team. Share your human-centered, ethical philosophy with team members through conversation for shared understanding

Questions? shorisyl@jmu. edu https: //www. lib. jmu. edu/