Terminology used by those in the data sciences field can sound like another language or something pulled from the script of a science fiction movie. Data mining, blockchain, artificial intelligence (AI), big data, machine learning, “internet of things” (IoT) and other data science terms can be daunting to outsiders.
Reality, however, is that the vernacular and usage of data sciences has permeated virtually every industry and has changed the way information is learned, decisions are made, and problems are solved.
Data science is one of the five initiatives of Baylor’s academic strategic plan, Illuminate. The University is committed to growing the investment in the field to enable Baylor students and professors to contribute more fully to the cutting edge of technology and new knowledge in areas such as biomedical informatics, cybersecurity and business analytics.
Dr. Stephen Gardner is The Herman Brown Professor of Economics in Baylor’s Hankamer School of Business and director of the McBride Center for International Business. The Center’s Global Business Forum brings experts together each year to expand students’ knowledge and understanding of global business trends. In 2018, the Forum’s “The Automated World,” took a look at AI and robotics and their impact on industries around the world. Gardner says while there is no single or generally accepted definition of data science, he defines it broadly as a field of study aimed at gathering information and making it useful.
“No one can be an expert on anything, but those in data science can be conduits of understanding to others.“
“Data science is a broadly interdisciplinary field that draws heavily on statistics and computer science and has applications in business, engineering, medicine, law, education, sociology, political science, and almost every other academic discipline,” Gardner says. “Data science is the foundational field for development of artificial intelligence, robotics and sensory technology—technologies that can mimic or transcend many aspects of human intelligence.”
In data science, information is gathered or drawn upon through massive computer systems, and algorithms are used to deduce and extract information that lends to structured and unstructured insights. Machine learning is the use of statistics and data which, when digested and processed repeatedly in a trial-and-error format by computer systems, can ultimately generate neural-type networks that act similarly to human brain neurons.
“Today, regardless of your job, decisions on the way almost anything should be done is driven by data. For example, in the healthcare industry, decisions are being made based on 20 years’ worth of charts and folders that have been digitized. Doctors can plug in an issue or symptom and make a determination based on the collaborative data.”
Data, now more easily accessible to be analyzed, can take many different forms because all varieties of sensory information—sight, sound, taste, touch and smell—can now be digitized, Gardner says. Data scientists are key to driving all fields forward.
“No one can be an expert on everything, but those in data science can be conduits of understanding to others,” he says. “There’s a parallel between these advances and globalization; it’s inevitable and unavoidable.”
Data science courses are offered in several departments in Baylor’s schools and colleges, including computer science, statistics, geosciences, management information systems, and economics. Many Baylor faculty members across disciplines incorporate and rely on data science in their research.
“The changes are happening rapidly,” he says. “People think it’s far in the future, but it’s really not. Other technical universities have a head start on us in the area of developing technology, but there is also so much more going on in the broader area of ethical and public policy issues related to the use of data. I truly see that this is an area, based on our grounding and perspective as a Christian university, that Baylor can be a leader.”
Microsoft data scientist George Montañez, MS ’11, agrees with Gardner that the responsibility of the ethical use of data falls to the academic.
“It takes principled effort to guide the field forward in ways that lead to human flourishing,” Montañez says. “Baylor has a long history of developing sustainable and appropriate technologies. Baylor’s talent pool is large, as is its mission to be a light to Texas, the Church and the world. Wielding a sharp mind from a compassionate heart is what Baylor should be known for.”
A number of Baylor alumni have established expertise in data science industries. Their perspectives add to our understanding of the impact of growth in the University’s pursuits in this field.