AI roles are frequently highly collaborative.
Software engineers might be known for working independently, but don’t expect solitude in an AI role.
While some engineering positions may be more solitary, Parse pointed out, “AI projects are rarely a solo effort.” This is partly due to AI being a rapidly evolving technology that demands collaboration across multiple teams and stakeholders, she explained.
For instance, Parse mentioned that she collaborates with seven or eight different teams when working on an AI recommendation system project.
In her experience, the process begins with data collection and preparation by the data analysis team. Next, data scientists apply statistical methods and modeling. The machine learning team then develops and fine-tunes the model. Once the model is complete, UX and UI experts design the user interface, and software engineers build the front end.
Finally, the marketing team defines the product’s launch strategy.
“An end-to-end AI project involves extensive communication and collaboration,” Parse emphasized.
Ethics should always be a top priority.
Privacy teams are often deeply embedded in the process when sensitive data is handled during AI development.
Parse said the privacy protocols are extensive. When working with a person’s data, employees need to receive permission for tasks. Projects also require robust production measures, like pseudonymizing identities and ensuring models don’t “inadvertently recreate biases or create inequitable outcomes.”
This requires complying with legal and regulatory requirements, she said. It also means thinking about the long-term implications of projects, including potential unintended consequences and ethical dilemmas.
While privacy may seem like an obvious consideration for those working in AI, Parse said it can be easy to get caught up in how the models perform. Also, since so many teams contribute to the product, it can be easy to focus on your specific task rather than the overarching implications, she added.
Parse said it’s up to companies to train employees on proper privacy and ethical guidelines. But it’s also important for employees to consider a third-person perspective on the work they’re doing.
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