On Friday, Sept. 22, the Department of Business and Information Analytics hosted a roundtable breakfast, “Using Emerging Analytic Techniques for Practical Problems,” to kick off Fall Quarter. The guest speakers, Ethan Rojhani, Alon Avdi, and Wes Luckock, work at the Denver branch of Grant Thornton, an audit, tax and advisory firm with headquarters in Chicago. The presenters shared their perspectives on how artificial intelligence and robotic process automation are helping to take rudimentary tasks off the plates of human employees.
The breakfast opened with a discussion about the Fourth Industrial Revolution, which encompasses:
- robotic process automation or the “use of software to automate high-volume repeatable tasks that previously required a human to perform.”
- automation continuum, which refers to systems that have three levels: do, think, learn.
- machine learning, which is a “subset of artificial intelligence that allows software apps to extract certain kinds of knowledge and patterns from a series of observations to become more accurate in predicting outcomes without being explicitly programmed.”
“Human beings’ thought processes are now going to be replaced by machines,” Rojhani said. While some may find this frightening, Rojhani considers it a necessary development since process automation allows human beings to focus on challenges that machines cannot mitigate. Moreover, machine learning eliminates human error, a common occurrence that can compromise the quality of data.
Process automation does not come without risks, however. According to the panelists, there is a potential for “false positives/negatives in a results set, difficulty in algorithm selection, and a need to frequently adjust [the] model for dynamic environments with changing data.”
Ultimately, the speakers believe machine learning is here to stay. Rojhani shared an example of an analytics display, explaining its features and benefits. “People may say, ‘What’s so great about this? It’s just a dashboard,’” he said. “But what they don’t realize is it replaced human time.”
While it seems that machine learning would streamline information and eliminate uncertainty, Rojhani was hesitant to make an overwhelming proclamation. “Is it easier to have one source of truth? For me, I’d say no.”
After the formal presentation, the speakers opened the floor to questions. In a room full of students studying business analytics, there was one inquiry that was particularly top of mind. If these processes are being automated, what happens to the employees who previously managed them?
“What we’ve found is they can reallocate their time,” Rojhani said. “But that’s a great question and I don’t think we have an answer for it yet. If anyone has the answer, let me know.”