Faculty Research: Monideepa Tarafdar Leads the Study of Artificial Intelligence in Business

Monideepa Tarafdar, Charles J. Dockendorff Endowed Professor in Information Systems (IS), is a world authority on how artificial intelligence influences business operations, processes, and decision making. She was one of the first scholars to study “techno-stress” (stress from the use of technology) and has produced influential research on the dark and bright sides of technology use, such as social media addiction, email overload, and good and bad stress from technology. She has published more than 150 papers on the use and impact of technology in society and in workplaces. She is co-ranked internationally as the top author of academic papers (as first author) in leading IS journals during 2021-2023, as recognized by the Association for Information Systems. She teaches Information Systems Management in the MBA program at Isenberg.

An Urgent Research Field: Artificial Intelligence (AI) in Business

This area of study is important, Tarafdar says, because of human primacy: how people retain control over and confidence in using AI in business decision making. “It’s important that we don’t overstretch human capability in terms of integrating AI into work processes or diminish human involvement in decision making,” she says, adding that organizations need to ensure that people have the skills needed in a work environment where AI influences decision making. Organizations also need to ensure that there is transparency in decisions and processes among executives and workers. “Lots of people are studying this but research and findings are still emerging,” she adds.

Tarafdar first encountered artificial intelligence—technology that assists human thinking and decision making (initially known as cognitive computing)—in 2016. While on a visiting scholar appointment at the Sloan School of Management at MIT, she conducted a study into how artificial intelligence might change management practices. She described the study’s findings in the paper The Three New Skills Managers Need, published in MIT Sloan Management Review in 2016. The study concluded that business leaders and employees, in response to the challenges posed by advanced digital technologies, will need to develop new skills: how to partner with IT and other colleagues to explore and innovate opportunities and problems, how to become digitally mindful to adapt to such changes as remote work and technostress, and the need to develop empathy for others’ technology preferences.

In a short amount of time, Tarafdar’s research interests broadened to include the rapidly evolving field of AI—where machines use algorithms to reach decisions independent of humans—and the issues of bias in data and transparency, in the decisions AI generates.

“Once I had the view of the influences of artificial intelligence on business, I had to dig deeper,” she says. She was a principal investigator on a UK-Canada grant-funded study into the role of AI related bias in business hiring, including how gender and ethnic bias might be introduced at both the-organizational (during hiring processes) and labor market levels (via job advertising decisions). “Because of its scale, any good or bad that AI hiring tools do will be magnified. We want to understand bias and learn to manage it.”

AI algorithms depend on the quality of data used to train the AI model, explains Tarafdar. Algorithms are subject to human bias, which may skew the algorithm and its results. Transparency refers to securing the trust of the user or those influenced by the results generated by the algorithm, which ultimately affects the efficacy of business decision making.

Crucial AI-related Capabilities and Key Practices

In a two-year international study (2016-17), Tarafdar and her co-authors went much deeper, exploring how companies develop their ability to use AI to transform and add value to business operations. They shared findings in a paper published in 2019 in MIT Sloan Management Review. Broadly, the study looked at companies that used AI to improve business processes that reduce costs or increase revenues and found that they possessed five crucial capabilities and four key practices. The crucial capabilities are data science competence, business domain proficiency, enterprise architecture expertise, operational IT backbone, and digital inquisitiveness. The key practices identified in the study include developing clear, realistic use cases, managing ECC application learning, cocreating through the application lifecycle, and thinking “cognitive”. Read more about these capabilities and practices here.

What’s next?

We’re still at the beginning of real adoption of AI, says Tarafdar. “We need to use it over and over for transparency, and gain confidence in the decisions AI is making. For our MBA and master’s graduates, who will encounter AI as it scales up and becomes more integrated in workplaces, this means developing skills that help them effectively use AI. A recent article she co-authored in MIT Sloan Management Review, Why Executives Cannot get Comfortable with AI, highlights the importance of AI literacy for executives. 

She draws from her research in her teaching. “Students dive into the case studies, looking more closely at the capabilities and key practices identified as being key for businesses to use AI to transform their operations.” But more importantly, she says, is that students see the full picture of the good and dark sides of technology use.

“It’s important for students to get the whole picture of IT—not just AI. Human primacy is very important—training needs, vigilance, and oversight of technology. There must be humans in the loop. We must build the technology around that.”

Read about Professor Tarafdar's research:

• https://www.isenberg.umass.edu/news/faculty-research-can-technology-enhance-workplace-inclusion
• https://www.umass.edu/gateway/article/monideepa-tarafdar