Active Research Projects

 Learn more about the researchers Jo-Ellen Pozner and Colleen Chien

 Learn more about the researchers Keyvan Kashkooli and Peter Younkin

This study takes a closer look at the impact of Artificial Intelligence and Machine Learning Tools on entrepreneurial pitches in a crowdfunding context. This research will address questions like - Does explicitly noting that text or images were generated by AI tools – regardless of whether they were actually generated by these tools – influence the perceptions of potential crowdfunders? For example, if a pitch is marked as being generated by an AI tool despite being written by a human author (or vice versa), does this impact crowdfunder perceptions? The goal of this project is to explore the ways in which potential crowdfunding investors react to AI generated pitches/imagery.

Learn more about researcher Andy El-Zayaty

Studies have shown a dearth of women in STEM entrepreneurship and innovation and have explored reasons why so few women start firms or take innovation related careers; however, few studies look at those who are thriving in these roles. This research examines examine the relationship between gender, educational background, work experience, and genetics firm outcomes to determine what influences success for women entrepreneurs in STEM fields. This project primarily entails interviewing women entrepreneurs of genetics firms to discuss their experiences starting and growing their companies.

Learn more about researcher Jennifer Woolley.

The aim of this study is to understand the experiences of religious influencers as entrepreneurs through interviewing religious influencers on major social media platforms. This process will lead to understanding how religious influencers use innovative and entrepreneurial strategies to reach their audiences, spread their values, and influence their online communities. Interviews will be conducted online with religious influencers based in the US from a variety of religious backgrounds. 

 Learn more about the researcher Di Di.

The purpose of this study is to gain a deeper understanding of how Asian American women entrepreneurs of 1.0, 1.5, and 2.0 generation of immigrants engage in racial dynamics in the United States. The second part of this project furthers the research into an applied project. With experiences learned from Asian American women participants, the significant lessons will be translated into narratives. These “critical incidents” of interactions in the forms of narratives will be recreated into virtual reality content and be used for educational purposes. The final product will be the creation of three to five of VR scenarios.

Learn more about the researcher Hsin-I Cheng.

In recent years, artificial intelligence (AI) and machine learning (ML) based talent management systems have been widely developed to improve recruiting efficiency with large-scale applicants. As a rough estimation, such AI/ML-aided systems have landed in 33% of organizations to assist the processes such as talent search, hiring decision, performance assessment, etc. While these “intelligent” systems greatly facilitate the whole recruitment process, one critical question raises–Are these methods smart enough to make a fair decision? 

In this project, the researchers will design and develop a fairness-aware talent management system, which aims to encourage diverse prediction results and alleviate the negative effect from data bias.

Learn more about researchers Zhiqiang Tao and Yi Fang.

It is well known that the allocation of venture capital funds is highly biased. Yet, despite this wide-spread awareness, bias not only persists, but continues to grow. According to Pitchbook, in 2019, female founders raised just 2.7% of the total venture capital funding invested and mixed gender founding teams received 12.9%. In 2020, funding given to female-only teams dropped to 2.2% with mixed-gender teams receiving just 12.2%. As one of the least represented racial groups in venture, black founders receive only 1% of venture capital funds.

Biases persist despite evidence that diversity offers a performance advantage over homogeneous teams: Racially and ethnically diverse companies are 35% more likely to yield financial returns above their industry medians, and in the United States, there is a positive linear relationship between diversity and financial performance. The same holds for gender diversity. 

While it is well-known that entrepreneurs’ race and gender play a role in investor decision making, commonly held beliefs on how bias manifests and what should be done to address it are fraught with error. It is as such unsurprising that efforts to help women and minority founder entrepreneurs are proving ineffective. Lacking an accurate understanding of the situation, well meaning efforts continue to fail and at times even exacerbate the problem.

Learn more about researcher Maya Ackerman.