ML in Multicultural Teams: Bias Detection & Mitigation. A Case Study of Angola

The Angolan industrial sector is formed mainly by international companies, which leads to frequent relationships with different cultures. This research explores some biases and their impact on the decision-making process of multicultural teams and the application of machine learning in mitigating such biases. Research has shown that biases in their varying forms can be detrimental to the collaboration of the teams and in decision-making, especially in the outcomes of the decisions made in the healthcare field. The research methodology for the project is mixed, involving the use of qualitative and quantitative techniques to collect evidence of team interactions and decisions reached. The collected and analyzed evidence demonstrated that background cultural differences significantly contributed to and strained the team dynamics. Moreover, it was noted that machine learning algorithms aimed at solving this problem- tailored machine learning algorithms- successfully identified the patterns of biases and their alleviation in the team’s performance.