College of Arts & Sciences Responds to the Opportunities (and Challenges) of Big Data and AI
The growth of the undergraduate and graduate programs in computer science reflects the trends in AI and machine learning. Enrollment in these programs has increased by 66 and 500%, respectively, over the past two years.
Yet the impact of these technological advances is felt beyond the computer science field, affecting multiple disciplines in the USD College of Arts & Sciences, said John Dudley, Ph.D., dean of the college. “AI has been all over the news recently, so we are all aware of its importance,” Dudley said. “In order to prepare our graduates for their careers and for the challenges and opportunities of a world dominated by the power of data, we need to train students to develop, use and understand AI tools across all the disciplines.”
The Next Generation of Data Scientists
USD is preparing the next generation of professionals with the knowledge to gather, analyze and interpret an ever-increasing amount of data that is too large and varied for traditional data-management systems (see “Definitions”).
Over the past several years, the Department of Computer Science has positioned itself as a leader in the rapidly growing field of data science. The bachelor’s degree in computer science is accredited by ABET, an organization that ensures a program has met standards essential to prepare graduates to enter critical science, technology, engineering and math (STEM) fields in the global workforce.
Under the direction of KC Santosh, Ph.D., who became chair of computer science in 2018, the department has rapidly expanded its programs and activities in areas related to AI and data analytics.
“USD recognizes the growing demand for data scientists and is actively preparing students to meet this need through various initiatives and programs,” said Santosh. “We do this through curriculum expansion and collaboration, an interdisciplinary approach and research opportunities.”
In 2019, the department announced that undergraduate and graduate students could earn a specialized computer science degree in AI, the first ever offered in South Dakota. The department also administers an undergraduate and graduate certificate in AI for students in any major. In addition, computer science coursework is featured prominently in disciplines throughout USD.
“We serve other divisions and departments by integrating courses related to AI and data science with their curricula,” said Santosh.
In the USD College of Arts & Sciences’ disciplines of biology, chemistry, sustainability, biomedical engineering and physics, computer science instruction plays a large role in select programs.
Undergraduate students earning their certificate in geospatial analysis receive instruction on how to collect, analyze and visualize spatial data. While studying for their certificate in bioinformatics, graduate students learn about the computational tools that will allow them to gain insights from vast amounts of biological data.
Paul Adam has made good use of varied offerings in data science during his time at USD.
“I am a computer science major pursuing a business analytics minor,” said Adam, who is originally from Pierre, South Dakota. “This year I also picked up a certificate in geospatial analysis. So, I’m clearly on a data analytics career path.”
When choosing to attend USD, the fourth-generation Coyote may have been predisposed to attend college in Vermillion, but the chance to learn with USD computer science faculty was what really sold Adam on the program.
“Computer science has very distinguished faculty; people who are very good at what they do,” he said. “It’s been an honor to learn from them.”
Adam said his computer science major pairs well with the business analytics minor. “I think business analytics really complements my computer science degree in that it forces me to make real life interpretations of data and statistics,” he said.
When Adam graduates this May, he said he hopes to find a career in business analytics and is excited to apply machine learning and AI tools to real-world problems.
“AI can take a corpus of data that would be unfathomable for a person or even a team of people to try and comb through and write different types of analyses, so you can create a program that could do all of these things a lot more efficiently than a human,” he said. “Computers are really good at memorizing things, and they don’t forget.”
Physics graduate students can specialize in analytics for large data sets by taking courses in machine learning and AI that provide them useful skills in material science as well as the opportunity to shed light on one of the most intriguing mysteries of the universe – dark matter.
USD’s Department of Physics began offering the master’s specialization in analytics of large data sets in 2017, said Dongming Mei, Ph.D., professor of physics. “We have accumulated a lot of data,” he said, referring to the information collected from the department’s dark matter and neutrino research and its on-campus laboratory dedicated to growing extremely pure germanium crystals – one of the few such facilities in the world. Germanium is a rare metalloid used in sensors that detect dark matter. It also has industrial and commercial uses, such as in medical imaging and specialized electronics.
Students in the program not only gain experience analyzing data from experiments at the Sanford Underground Research Facility in Lead, South Dakota, but they also take part in using AI tools to analyze data from 12 years of germanium crystal production. Mei said students working with this data can help speed up and streamline crystal production, giving graduates of the program experience sought after in industry as well as in academia.
Mei refers to the process of growing high-quality germanium crystals as “challenging work,” especially when it comes to controlling crystal purity. “We need to have an increase in yield of this pure germanium crystal,” he said. “Our students are using data and machine learning and AI to help increase the yield.”
At the Forefront of Data Science Research
The newest addition to the Department of Computer Science’s academic offerings is a Ph.D. in data science and engineering, offered jointly with South Dakota Mines. This degree furthers the already-robust research program in data analytics, machine learning and AI by supporting top graduate students while they produce new knowledge through their own research and work on projects with department faculty.
USD computer science faculty have wide-ranging collaborations in the U.S. and throughout the world – a significant advantage to the students who study here, Santosh said. Students are often co-authors on published studies that include analyzing foreign objects on chest X-rays with AI tools, using AI to predict male fertility, utilizing active learning to minimize the possible risk of future epidemics and examining AI ethical issues.
In addition, computer science faculty collaborate on projects at some of the U.S. Department of Energy’s National Laboratories – including Brookhaven, Argonne and Lawrence Berkeley – where researchers address issues related to energy and climate, the environment, national security and health.
“These relationships with national laboratories are definitely a plus for our graduates for their summer internships,” Santosh said.
At USD, computer science students and faculty alike perform projects with researchers in the Sanford School of Medicine, School of Health Sciences, and departments of biology, biomedical engineering, chemistry, physics, and sustainability and environment.
The research capabilities of the Department of Computer Science have recently earned it federal research grant funding from the U.S. Department of Energy and Department of Defense, Santosh added. “USD’s AI programs are able to unite AI and data engineering experts in academia, industry and government to solve current challenges in various applications such as health care, cyberthreats, quantum computing, sustainable agriculture and risk management.”
Another aspect of preparing students to live and work in a data-driven world is encouraging them to explore the nature of AI and what it means to be human. Humanities courses, such as those offered in the USD Department of Communication Studies, tackle these issues head on.
“Humanities classrooms are the perfect place for students to unpack the idea that AI is not simply good or bad, but ultimately both,” said Leah Seurer, Ph.D., associate professor and chair of communication studies.
The mark of a successful student in a humanities course is one who stops seeing the world as an “either/or” place and starts seeing the world as a “both/and” place, she added.
Seurer explains that the critical thinking and complex problem-solving skills taught in the humanities provide groundwork for students to help themselves and others effectively navigate and lead in a world of AI.
Take ChatGPT, for example. In the classroom, the AI text generator that creates human-like text responses is a fascinating tool with uses both helpful, such as describing a complex topic succinctly, and detrimental, such as enabling students to submit an assignment they didn’t write.
Seurer isn’t extremely concerned about cheating. “By and large, students are in our classrooms to learn and are willing to put in the work to do that learning,” she said.
While they address the topic of handing in computer-generated assignment responses, department faculty focus on teaching how ChatGPT works and how to assess its accuracy and quality.
Tools such as ChapGPT offer opportunities to help students develop skills they will need in their professional lives. “There are always ways to use ChatGPT to help generate ideas and save administrative time,” Seurer said. “What we hope to cultivate in our communication studies students is the ability to choose when, how and why to use AI and when to leave it on the proverbial shelf.”
AI tools and chatbots raise questions about the nature and means of human communication – making it an ideal topic of research for Seurer’s field.
“We are already arriving at a point in time when individuals can rarely distinguish between speaking with another human and speaking with AI,” she said. “As such, our field will need to expand the scope of our research and begin to unpack what human/AI relationships might look like and their benefits and risks.”
An Education in Ethics
Incorporated in the curriculum for computer science majors is the popular course Social, Ethical and Legal Aspects of Computing taught by Zachary Tschetter, an instructor in the department who also earned his master’s in computer science at USD.
The 400-level course content is high-level, with students required to research and lead discussions on a topic of debatable ethicality.
“Some past topics we have discussed are parasocial relationships, deepfakes, AI and loot boxes, which are virtual treasure chests in video games,” Tschetter said. “Common points of discussion often revolve around ethical considerations, legality, the necessity of regulation and the feasibility of regulation.”
In terms of big data and AI, Tschetter said he sees several ethical challenges that he incorporates into class discussions. Among these are data accuracy, the need to protect private information and lack of transparency.
There is also a concern about AI developing a systemic bias based on the data sources used. “There is a concern that this will worsen as people use the data, which could reinforce the bias,” Tschetter said.
Of special interest to future data scientists is the role of regulation of the industry and to what extent the industry must police itself, Tschetter said.
“Ultimately, even with regulations, it’s up to the practitioners of data science to behave ethically,” he said. “Organizations that employ data scientists need to continuously develop and monitor an ethical code of conduct as a fundamental part of their culture.”
USD computer science students graduate with a firm grasp on the ethics of these new technological advances. “This course, our program of study, our department, and USD’s culture help students gain an understanding of ethical concerns and promote ethical behavior,” said Tschetter.
The purpose of AI is ultimately to serve humanity, and this principle governs USD’s College of Arts & Sciences research and instruction in the field, said Dudley.
“What sets USD apart is our ability to pair cutting-edge technology with our grounding in the liberal arts. Ultimately, it is these liberal arts skills of effective communication, ethical decision-making, and creative problem-solving that will help our graduates succeed in a future that is increasingly populated with big data and AI.”
Read more stories about USD graduates who are putting their arts and sciences degrees to work in data science careers.
- A Liberal Arts Background Pays Off: Alumna Pursues Career in Data Science for Major Corporation
- Computer Science Grad Puts USD Honed Leadership, Problem-Solving Skills to Work in Career at Omnitech
- Using Data and AI for Good: Sustainability Alumnus Utilizes Machine Learning to Prevent Health Care Burnout
Big Data: Data of a very large size, typically to the extent that its manipulation and management present significant logistical challenges
Artificial Intelligence: The capacity of computers or other machines to exhibit or simulate intelligent behavior
Machine Learning: The capacity of computers to learn and adapt without following explicit instructions, by using algorithms and statistical models to analyze and infer from patterns in data
Source: Oxford English Dictionary
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