Miller Center Fellowship
Document Type
Research Report
Publication Date
11-2015
Abstract
This interim report will serve as the basis for a senior thesis that will be published in May 2016. This report will recommend strategies for iMerit Technology Services to benefit from machine learning. It will explain the potential of machine learning by using iMerit as an example of a successful social enterprise engaging in computer vision data processing. This paper presents research activities including interviews and observation of iMerit’s employees as evidence of their capability, self-efficacy, and ability to acquire skill over time, and thus show their ideal position in the delivery chain of machine learning technologies. iMerit is uniquely suited to the challenge of creating accurate data sets for computer vision software. By hiring and training marginalized youth and women, iMerit ensures that sensitive data is protected, a positive and familial work environment is sustained, and lastly, iMerit is able to form positive technological work habits from the beginning of its operator’s work careers.
During interviews, iMerit’s Metiabruz operators reported that they felt a sense of pride and selfconfidence from working on projects that involved high technology. The operators displayed a high aptitude for critical thinking compared to other workers in their same demographic. This critical thinking manifested itself through advanced technological habits such as using hotkeys to perform tasks on a computer. When surveyed, iMerit’s operators displayed a self-efficacy that was consistently above average, with the highest scores correlating to a belief in personal achievement.
On the basis of these key findings, this report recommends that iMerit implement additional machine learning training for its operators. The report also suggests that iMerit implement its own data processing software platform. Hiring a subject-matter expert in the field of machine learning could be very beneficial for iMerit to strengthen its sales and marketing strategy. iMerit may find advantages in further testing its operators using self-efficacy as a benchmark. In this way iMerit can evaluate the degree to which new training is effective in the empowerment of its workers.
Recommended Citation
Kotero, Christiane and Rohacz, Christine, "IMerit: Machine Learning for Women's Empowerment, an Interim Report" (2015). Miller Center Fellowship. 46.
https://scholarcommons.scu.edu/gsbf/46
Comments
https://www.millersocent.org/portfolio/imerit/