Reflection
This project has proven to be a highly eye-opening experience for me as a person and a professional. I
learned more about my weaknesses and strengths. I realized my capability of conducting wellstructured research and relating theoretical concepts to practical applications and that I struggled
initially to explain adequately enough the value addition of the AI tool. Constructive criticism that
entailed establishing learning objectives challenged me to think more critically about how our tool
could improve upon what is already out there and engaged me more actively in continuing objective
clarification, user benefit, and assessment metrics. This even further honed my skill at taking broad
ethical principles and making them specific educational achievements, a key competency in my future
career.
Group dynamics between my group members and me were better with time during the project. We
were a four-member group. We did not experience much coordination issues. By establishing the
scope of personal responsibility and exercising openness to the exchange of information through
weekly meetings and shared documents, mutual understanding were enhanced. Conflicts were
addressed constructively, being more interested in rational argument than personal preference. I
experienced the importance of active listening and timely feedback for the first time, and this
generated good effective team spirit. Preserving milestones such as completing our first draft of our
case generator design fostered our drive and cohesion.
The project process itself required iterative adaptation. First, our focus was on demonstrating the
technical feasibility of developing cases with LLMs, but feedback suggested that justification of
learning value and greater use of HR literature was required. This made add use recent HRM
research, such as resume screening bias, which gave our design a field-backed evidence base. I also
learned the value of combining automated processes with human inspection for quality control. I
understood that flexibility and responsiveness to criticism are the essential characteristics of effective
project outcomes.
On a discipline-based front, the assignment reinforced my familiarity with the intersection of AI ethics
and HR practice. It highlighted the organizational and societal impacts of algorithmic bias and ensured
the importance of ethical frameworks like the UDHR, the Four Principles Approach, and Design for
Values in shaping responsible AI design. Applying these systems as an operative learning tool also
allowed me to critically analyze AI systems, predict value conflict, and elucidate ethical justification
effectively. The experience also reinforced the need to couple technical expertise in AI with social and
ethical literacy, a cardinal skillset for my future professional self working in AI/Robotics engineering.
Lastly, this project improved me with better research abilities, ethical considerations, and
collaboration capabilities. It made me realize that the design processes are iterative, that going to the
trouble of inviting critique is worth it, and that there is a need to interpret AI technologies in real
social and organizational contexts. These lessons will directly be applied in my next career life in
academia and industry, where I will construct AI with technical competence and ethical awareness.