Mackenzie Jorgensen

As data-driven AI methods develop rapidly within academia, industry, and government, the need to ensure AI does not harm individuals and groups when making predictions about them is of the utmost importance. While powerful, these methods carry with them a risk of discrimination and unfairness. Since data-driven AI methods typically operate in a non-transparent way, AI practitioners can struggle to identify and rectify unfairness. While bias mitigation methods have been developed, they do not necessarily prevent AI from making potentially harmful predictions. The main aim of this project is to reduce discrimination and other potential harm arising from data-driven AI methods, while also aiming to uplift underprivileged groups.  

My research project, AID: Attesting AI Discrimination, and working alongside my supervisor, were my primary reasons for joining the STAI CDT. My project aligns with my interest in AI and with my passion for ethical technology that helps, rather than hinders, certain groups unfairly. I was also eager to join the CDT because of the way it is structured such that I would be a member of a cohort of researchers on the cutting edge of Safe and Trusted AI. The training programme was another positive for me since it helps me not only become a better researcher, but a more informed and developed person as well.   


Undergraduate Qualification: BSc in Computer Science, Villanova University, Villanova, PA, USA 

Research, Awards and Work Experience: Since I was focused on making a positive impact through computer science research as an undergraduate student, I pursued a 2017 summer research internship in Machine Learning (ML) and Big Data. I worked as an NSF (National Science Foundation) REU (Research Experience for Undergraduates) student at Northeastern University on a health informatics problem.  My research from that summer was published by IEEE, after I presented at the 2017 MIT/IEEE Undergraduate Research Technology Conference.   Since I am committed to the necessity of international technology partnerships, I applied for a DAAD RISE internship (German Academic Exchange Research Internship in Science and Engineering) and was awarded an internship at the Universität Kassel. During summer 2018, my research focused on how two agents could communicate and coordinate their actions to solve a game; the answer was in hierarchical deep learning. In spring 2019, my mentor and I’s research paper was published by the Association for Computing Machinery’s Symposium on Applied Computing. We completed further research, and our results were published for fall 2020 in the Special Issue on Intelligent Robotics and Multi-Agent Systems in Cybernetics and Systems: An International Journal.    In summer 2019, I applied for and was awarded another DAAD RISE scholarship in Münster at the European Research Center for Information Systems Headquarters. My research focused on abusive language detection in English and German using ML. I published my findings in a research paper as lead author at the International Business Informatics Congress and I presented at the conference in March 2020.    I was recognized by the National Center for Women and Information Technology as a Collegiate Award Finalist and Honorable Mention in spring 2020 for my research project I completed in Münster. The award recognizes technical contributions to projects that demonstrate a high level of innovation and potential impact. In addition to that award, I received an NSF Graduate Research Fellowship in spring 2020 which recognizes and supports outstanding graduate students in NSF-supported STEM disciplines in graduate school.  

As a woman in tech, I am passionate about inspiring future female generations of technologists. With that said, I co-founded a Washington state nonprofit, WATT (Women Advancing Tomorrow’s Technologists) which empowers young girls to pursue computer science and teaches them the magic of coding in the greater-Seattle area. As an undergraduate student, I undertook three summer research internships as mentioned above funded by the National Science Foundation in Boston and two funded by the DAAD in Kassel and Münster. After graduating from Villanova, I interned as a Machine Learning Engineer with the NGO HURIDOCS (Human Rights Information and Documentation Systems) over the summer of 2020, where I worked on an explainability project for the Office of the UN High Commissioner for Human Rights.