We Need More Women in AI Strategy, Ethics, Policy, and UX Roles — Visa Global Head of Risk Analytics and Insights

(US & Canada) Heather Tubbs, Global Head of Risk Analytics and Insights at Visa, speaks with Amy McNee, SVP, Solutions Architecture and Technical GTM at Informatica, in a video interview about the concerns around AI application and its implication on data, the opportunities and challenges for women in AI, and the need to understand the underlying processes to better utilize AI.

Visa is a trusted network and world leader in digital payments, working to remove barriers and connect people to the global economy.

Speaking of the concerns around the application of AI, Tubbs states that the speed at which the need for AI is increasing is much quicker than the readiness and responsible usage of AI. While many organizations find the fastest way to an AI solution, they still cannot keep up when it comes to the identification of anomalous behavior or real-time alerting capabilities.

The onus falls on the data team to ensure keeping up with the pace of the need and build capabilities thoughtfully, says Tubbs. The data professionals need to ensure that the solution or product is at least 80% right the first time and then iterate to create the right need for the tool.

Delving further, Tubbs notes that with incredible potential comes risk, such as biases. For instance, one may not think of the right inputs and whether the team ensures using ethical guidelines while moving hastily with a model.

According to Tubbs, it is critical to consider these aspects to avoid unintended consequences due to the speed of getting to the AI solution. It boils down to striking the right balance and harnessing the power of AI in the right way to drive innovation and efficiency. While she loves the idea of AI solutions, she notes that it must be done the right way.  

When asked whether AI presents opportunities or challenges for women, Tubbs states that there are tremendous opportunities for women in AI. She elaborates that AI has created a solid demand for diverse skill sets.

Taking her team as an example, Tubbs shares that along with the required technical skills, the team also has business acumen and strategic thinking abilities around data use. She asserts that organizations need more women in AI roles that revolve around strategy, ethics, policy, and user experience instead of being tied down to technical roles.

Tubbs believes that women have a huge opportunity to not just participate but lead in the field. It also brings diversity and how AI is recognized by having more women in the space. Visa is leading such efforts, she adds.

However, Tubbs feels that there are areas where women are underrepresented in the STEM field. Therefore, it is crucial to encourage women to consider STEM-focused areas and give them the right training opportunities.

Another challenging area is job displacement due to AI. For instance, the education and retail workforces that are predominantly female tend to sometimes be more repetitive in nature and can be replaced by AI.

Moving forward, Tubbs states that, from a broader perspective, it is not just the women who are concerned about losing jobs to AI. When it comes to generative AI, organizations tend to deliver insight through AI for cases that do not require much organizational thinking at the global level.

To address this, a commitment to continuous learning is required, and not everybody prioritizes that, says Tubbs. Women, for instance, would feel good about where they are because of the nature of having families and wanting work-life balance. She emphasizes the need to promote continuous learning, especially for women, and create a culture that fosters diversity.

Next, Tubbs concurs with one of the gravest concerns highlighted by McNee, which is the depletion of critical thinking due to increasing reliance on AI. She asserts that after using Copilot extensively, she realized that it was referencing her.

Summing up, Tubbs notes that it is still an evolution that will look different in 5 years. She also believes that constant upskilling and creating a market that would require skills that coexist with AI is a smart move.

In closing remarks, Tubbs recommends everyone to leverage AI but also understand what creates it. While AI is an enabler, it is imperative to understand the inputs, how it is being built, and where the information is sourced from; otherwise, it will turn into a black box.

With tools like Co-pilot or ChatGPT, one gets instant answers to problems that require critical skills to solve, especially when it comes to data, coding, and SQL. Tubbs says that one should embrace AI but avoid relying on machines for everything.

CDO Magazine appreciates Heather Tubbs for sharing her insights with our global community.