To give AI-focused female academics and others their well-deserved – and overdue – time within the highlight, TechCrunch has published a series of interviews specializing in notable women who’ve contributed to the AI revolution. As the AI boom continues, we'll publish these articles all year long, highlighting essential work that always goes unrecognized. You can find more profiles here.
Catherine Breslin is the founder and director of Kingfisher Labs, where she supports corporations in developing AI strategies. She has been an AI scientist for greater than twenty years, working for the University of Cambridge, Toshiba Research, and even Amazon Alexa. Previously, she was an advisor to the VC fund Deeptech Labs and a Solutions Architect Director at Cobalt Speech & Language.
She studied at Oxford University before receiving her master's and doctorate degrees at Cambridge University.
In short, how did you start with AI? What attracted you to this field?
I loved mathematics and physics at college and decided to review engineering at university. That's where I first learned about AI, regardless that it wasn't called AI on the time. I used to be fascinated by the thought of using computers for speech and language processing, which comes easily to us humans. From then on, I ended up studying language technology and dealing as a researcher. We are at a degree where AI has made great strides recently and I consider there may be an amazing opportunity to develop technologies that improve people's lives.
What work in AI are you most pleased with?
In 2020, within the early days of the pandemic, I founded my very own consulting firm with a mission to offer organizations with real-world AI expertise and leadership skills. I’m pleased with the work I actually have done with my clients on diverse and interesting projects, and in addition of with the ability to do that in a really flexible way with my family.
How do you overcome the challenges of the male-dominated technology industry and due to this fact also the male-dominated AI industry?
It's hard to measure accurately, but about 20% of the AI field is women. I even have the impression that the share decreases as I grow old. For me, constructing a support network is among the finest ways to manage. Of course, support can come from people of all genders. However, sometimes it's reassuring to seek advice from women who’re in an analogous situation or have seen the identical problems, and it's great to not feel alone.
The other thing for me is to think twice about where to place my energy. I consider we’ll only see lasting change when more women get into leadership positions, and that won't occur if women spend all their energy attempting to fix the system as a substitute of advancing their careers. There is a practical balance between driving change and specializing in my very own day by day work.
What advice would you give to women wanting to enter the AI field?
AI is a large and exciting field with loads occurring. There can also be loads of excitement from the seemingly constant stream of papers, products and models being released. It's not possible to maintain up with every little thing. Furthermore, regardless of how eye-catching the press release, not every paper or research result might be significant in the long term. My advice is to search out a distinct segment that you just really intend to make progress in, learn every little thing you possibly can about that area of interest, and tackle the issues you should solve. This gives you the solid foundation you wish.
What are among the most pressing issues facing AI because it continues to evolve?
There have been rapid advances within the last 15 years and we’ve seen AI move from the lab into products without really taking a step back to properly assess the situation and foresee the implications. An example that involves mind is how a lot of our speech and language technologies work higher in English than in other languages. This doesn’t mean that researchers have ignored other languages. Significant effort has been put into non-English language technology. But the unintended consequence of higher English language technology is that we develop and deploy technologies that don’t serve everyone equally.
What issues should AI users pay attention to?
I feel people should realize that AI is just not a panacea that may solve all problems in the following few years. It may be quick to create a formidable demo, but it surely takes loads of effort to construct an AI system that works well consistently. We mustn’t lose sight of the incontrovertible fact that AI is designed and built by people, for people.
What is one of the best approach to construct AI responsibly?
Building AI responsibly means including diverse perspectives from the beginning, including out of your customers and everybody affected by your product. It's essential to check your systems thoroughly to make sure you realize how well they perform in numerous scenarios. Testing has a repute for being boring work in comparison with the joy of considering up recent algorithms. However, it will be important to know whether your product really works. Then it is advisable be honest with yourself and your customers about each the capabilities and limitations of what you’re constructing in order that your system is just not abused.
How can investors higher advance responsible AI?
Startups are developing many recent AI applications, and investors have a responsibility to think twice about what they need to fund. I would love to see more investors express their vision for the longer term we’re constructing and the way responsible AI matches into it.
