Christa-Awa Köllen’s Insights on Diversity and Inclusion in Data Science Sectors
Please introduce yourself, what you do, and your current role.
My name is Christa-Awa Köllen, a data scientist and machine learning engineer based in London, UK. Currently, I am a senior data scientist at Marks and Spencer, one of the largest British multinational retailers. My expertise lies in ranking algorithms and personalisation for the M&S website. Prior to that, I held data science and machine learning roles at Workfinder and JustEat, respectively.
What inspired you to pursue a career in AI and data science, and what continues to motivate you in this field today?
My passion for AI and data science began during an internship where I had the opportunity to work at a research lab in the industry. It was during this time that I delved into building a chatbot and discovered the concept of word embeddings through the Tensorflow embedding projector. Witnessing how words could be represented as vectors and the potential for quantitative research in understanding cultures and human behaviour captivated me. As the field progressed from neural networks to LSTMs and now LLMs, I remained fascinated by the study of human behaviour, decision-making, and finding ways to extract the richness of human language for machine learning models.
Who have been your role models, and how have they played a role in getting you to where you are today?
My role model is my mother, whose unwavering determination and belief in finding solutions to challenges have greatly influenced me. Her practical problem-solving approach has been invaluable in my role as a data scientist, enabling me to navigate complex problems by connecting the dots even when things seem impossible.
Why do you think diversity is crucial for the AI and data science sectors?
By embracing diversity and fostering an inclusive environment, the AI and data science sectors can leverage a wider range of perspectives, experiences, and expertise to drive innovation and ensure equitable outcomes for all.
Firstly, to truly understand and interpret global behavioral patterns, we need data scientists who represent diverse end-users. This ensures that we capture and protect valuable insights while advocating for the consideration of vulnerable data that may affect specific populations.
Secondly, as AI becomes an integral part of our lives, it is vital that the global population be involved in building these complex systems. The decisions made throughout the development process should consider the interests and needs of all individuals, preventing any form of disadvantage or exclusion.
What needs to happen for the sector to become more inclusive?
To promote inclusivity, the sector needs to break free from traditional norms and biases, ensuring that certain personality types or archetypes are not favoured over others. This starts with diversifying leadership positions, as their inclusive leadership styles will permeate throughout the sector, enabling a more diverse workforce. It is important to consider a wide range of leadership qualities and embrace different perspectives, creating opportunities for individuals to progress without relying solely on targeted recruitment campaigns.