As Ireland’s Women in AI ambassador, Alessandra Sala challenges the approaches used to date to improve diversity in STEM.
Alessandra Sala understands the advantages that come with good connections and diverse perspectives. When studying computer science in Italy, the professor with whom she did her thesis and PhD later became dean of the university, directing Sala towards new opportunities such as an exchange period to discover how research was being done in other universities.
“I discovered a new world. Structure, results and ideas that were beyond what I was working on,” Sala told me.
This led to five years as a student, then postdoc, then researcher at UC Santa Barbara in California. During this period, Sala received high-level training and exposure to top-level conferences. She was a key contributor on several funded proposals from the US National Science Foundation, and was awarded the Cisco Research Award in 2011. The experience, Sala said, “changed my life completely”.
“The US really has a structure in place for performing research at the top level, it is tremendous,” she said. But while she loved the energy, connections, competitiveness and working opportunities available to her in the US, she was ready to come back to Europe. She missed the culture, she missed her family. And while thinking of making a return, an opportunity from Bell Labs presented itself.
‘How are we failing to create a pipeline that is strong enough, resilient enough and connected enough to be successful?’
– ALESSANDRA SALA
While Bell Labs’ New Jersey HQ is known as “the Mecca of research”, according to Sala, she knew the company also had a strong research base in Dublin. “I was very much interested in working with large-scale data, so their programme on big data [in Dublin] was definitely interesting to me,” she said.
Sala joined the Bell Labs big data research team in 2012, her research focusing on distributed algorithms and complexity analysis, with an emphasis on graph algorithms and privacy issues in large-scale networks. Within a year and a half, she became technical manager of a newly formed team.
“We started to have a lot of success because we had data coming from telecommunications networks and we started to show all the different things you can do with those data sets. And then it became, when Nokia arrived, an even larger network.”
Now, as head of analytics research at Nokia Bell Labs, Sala leads teams in Dublin and Paris, and previously coordinated others in Budapest and Cambridge.
Women in AI
It was another helpful connection that led to Sala’s other role as chief ambassador of Women in AI Ireland. Women in AI, a non-profit working towards gender-inclusive AI for the benefit of global society, was apparently looking to grow in other countries. Word had got to the group that Ireland had many people working in AI and data, which led to an introduction to Sala.
Becoming the ambassador for a women in tech group marked a complete turnaround of perspective for Sala, who in her earlier years hadn’t understood the need for these communities and networks.
“I thought this was a waste of time because, in my limited experience, I was so supported by men, I was so well mentored by professors, I was so well accepted within my research teams,” she said. “But then I realised my journey was very different from other people’s journeys.”
As Sala’s career progressed and she familiarised herself with others’ experiences, she realised the imbalance of power between men and women was “shocking” and finds little has changed in the intervening years.
“It’s 15 years that we are trying to connect women, helping women, giving them role models, showcasing different parts and yet in the big corporations, in the large organisations, the situation is dramatic. So what’s going on? How are we failing in the past so many years to create a pipeline that is strong enough, resilient enough and connected enough to be successful?”
For Sala, a different approach is needed. “The model is not to just state that we have a problem. Stating that we have a problem is obvious to everyone. […] Sharing the same experience and stopping there, it doesn’t move the needle.”
She believes these shared experiences must evolve into a connection and possible collaboration to effect change. “If we can do something together, it gives hope.”
Determined to build a women’s sci-tech network that was effective, Sala first did some essential groundwork, seeking out other sector groups and making sure they were on side with her mission. She didn’t want to be seen as a competitor entering an already busy space of meet-ups and networks, but as an asset to the community. After all, with Women in AI, she was hoping to solve a problem they were all trying to address.
Sala could see a great opportunity in Ireland’s small, well-connected and diverse AI and data community. But she was also aware that creating an abundance of activities for people to choose from can be as much a hindrance as a help – a problem that she already had a lot of experience researching.
‘People are constantly stimulated and triggered to pay attention to things that, at the end of the day, are not building up solid knowledge’
– ALESSANDRA SALA
“Information overload is killing us today,” she explained. With technology providing us with easy access to an increasing variety of information, we have yet to solve the problem of making these vast quantities of information digestible for the human brain.
“We are constantly overwhelmed by messages in chat channels, emails, news articles, social media, Twitter, Instagram, LinkedIn, and, even in the physical world, events of all possible sorts,” said Sala. “So people get more confused and disconnected. [They are] constantly stimulated and triggered to pay attention to things that, at the end of the day, are not building up solid knowledge, but only building dysfunction.”
The solution Sala sees is to create a “connectivity layer” that allows people to digest the information available without being overwhelmed. “Giving you the ability to filter out or filter in what’s relevant in the moment is absolutely important in the digital space and in the physical space,” she added. “It is exactly the same principle.”
Reaching across the divide
For Sala, there is much more that Ireland’s local tech ecosystem can give us if we would just stop for one second and refocus on problems and solutions. Paring her own mission down to its core points, she focuses on three principles: inclusion, person-to-person connections and education.
On the education side, Sala was eager not to fall into the easy traps of helping young people who already had demonstrated an aptitude in STEM or who came from a background where opportunities in STEM would be easier to come by. Her goal is to reach across the divide to those who would miss out on these opportunities completely without this effort.
This is something she learned from her own research in network studies, whereby the more connected you are, the more you grow your network – the ‘rich get richer’ concept.
“I figured out that I was doing the same thing. I was working, helping and awarding my free time to people that were already at the top of their careers and at the same time I was seeing this gender gap, this inability to grow the female participation in the tech, STEM and AI community,” she said.
“At that point it was absolutely clear I was doing something wrong. I had to devote my attention and my energy towards those people that didn’t even dream or see the opportunity of being part of this tech world, of this science world, of these more mathematical studies.”
She believes we can engage young people using their own familiar frame of reference, showing them how science can contribute to solving problems important to them through a language that speaks to them.
“If we even move the needle very little, I think it can be dramatically helpful. Because we can change the trend,” she said. “Diversity is important. It’s necessary.”
Reflecting on the history of innovation, she notes how many examples we have, from medicine to transport, where designing with only one perspective in mind created disadvantages or even became harmful to others. “Why should we repeat the same mistakes for the technology of the future?”
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