Abstract
Generating new leads and clients in business has always been a uniquely human process.
Being a good salesperson has always come down to people skills and building an established
level of trust with your potential clients. I have spent the last year working on a project that
bridges the gap between lead generation and emerging AI-driven technologies. It has become
very clear how the technical work done in this project can have far-reaching consequences that
we may not fully understand yet.
Our technical project involved working with Zbooni, a Dubai-based company, to help
automate their lead generation process. We developed LeadFlow, a full-stack prospecting system
that handles the entire lead generation process up until an eventual handoff to a real sales team
when certain criteria have been met. The unique challenge we faced was the constraints of
working in a data-scarce environment. This means that we had to develop our system without
any historical outcome data to build off of. On top of this, we had to balance the needs of various
stakeholder groups including the sales team, management, and merchants to make our product
work long-term. While the technical work focused mainly on Zbooni’s needs, it is up to us as
engineers to examine the broader implications of our work.
My STS research project aimed to take a step back to examine these broader
implications. I examined this work through the lens of the Social Construction of Technology
framework, which emphasizes the impact different social groups have on shaping technology.
SCOT provides categories for each stakeholder including producers, advocates, users, and
bystanders and examines the different power balances and needs that lead to how a technology
develops. Transparency was a major concept to explore, as the AI-driven system is being used to
profile leads and reach out to people under the guise of being a human. AI colonialism, when
western-built AI systems are being deployed into other regions like MENA, is also of great
concern. Together, exploring these concepts is important for understanding broader societal
implications that the technical project alone didn’t fully address.
Working on the technical project gave insight into how to build and deploy an AI-driven
lead generation tool, while my STS work gave me more insight into what ethical consequences
this work might have. My technical work involved analyzing the wants, needs, and power
balances within Zbooni itself, while my STS research allowed me to analyze the users,
advocates, and bystanders involved as well. Overall, working on these two projects has led me to
learn that our work as engineers can have far-reaching consequences beyond what is in front of
us. Regardless of your good intentions, you can’t fully understand the weight of your decisions
without fully analyzing everyone affected by the technology.
