5 Women in AI you May not Have Heard of
Artificial intelligence is a booming field. Right now, more than ever, we need the participation of women to keep up with the field’s rapid advancements. Otherwise, we risk having bias seep into the algorithms we design and the products we sell. In North America, for instance, women accounted for 22 percent of all AI and computer science PhD programs in 2019, just 4 percent higher than in 2010. Progress is still slow globally, but tangible change can be seen already, especially here at McGill. Let’s get to know 5 more women (among so many others) who continue to make their mark on the field.
Bias in Machine Learning. Read more here
Rana el Kaliouby
Rana el Kaliouby is an Egyptian-American computer scientist and entrepreneur inspired by her mother who was one of the first female computer programmers in the Middle East.
El Kaliouby realized the “emotional blindness” of our virtual worlds and strove to create more human-centric technology. This propelled her to co-found Affectiva: pioneer in the field of Emotion AI which analyzes users’ facial expressions and interactions with the objects around them along with other contextual clues to make conclusions about the inner cognitive and emotional states of humans. Her products aim to harness the power of machine learning and computer vision to design more emotionally intelligent products, such as a perceptive smart phone capable of catching early warning signs of anxiety or depression, or automotive AI to catch a driver falling asleep at the wheel. Applications of Affectiva's AI include healthcare and mental health, robotics, conversational interfaces, education, gaming, and more.
Dr. Rana el Kaliouby: AI Thought leader. Machine Learning Scientist. Deputy CEO at Smart Eye. Former Co-Founder and CEO of Affectiva. Author of the book “Girl Decoded.” Disrupting industries and humanizing technology with Emotion AI
“You don't have to be a genius to be a scientist, but you do need to be persistent.”
/*Also, do check out this gem of a podcast between Rana and Lex in which they discuss everything from women in the MENA region to mangos to emotionally intelligent robotics.*/
Poppy Gustafsson
Poppy Gustafsson founded Darktrace at 30 years old in 2013. At the time, she and her colleagues were leading a research team of mathematicians from Cambridge as well as AI experts. From there, Darktrace was born. Her cyber-AI company leverages the power of mathematics to enable AI to autonomously defend organizations from cyber-attacks including ransomware, email phishing, and threats to cloud environments. The key insight that led to Darktrace’s inception was that efforts aimed at uncovering the ever-changing and evolving techniques that hackers use to breach an organization’s security was just not possible nor efficient. Instead, organizations should learn the ins and outs of their own normal, day-to-day network activity and from that, they can then spot unusual anomalies that may signal suspicious malicious activity. Today, Darktrace’s AI is capable of spotting sophisticated attacks as they happen in real-time and fight back instantaneously on behalf of humans. Darktrace’s R&D team have also made it possible for their AI to interrogate its own findings: instead of humans manually “checking its work,” AI is now taking care of this too.
“We are already used to the idea of AI recommending what to watch on Netflix based on our personal preferences — in security, it will become completely commonplace for AI to be recommending what action to take in response to its own investigations into a cyber-attack. In many cases, the action will be taken without the human in the loop. Time is rarely on your side when dealing with computer-driven attacks, and action usually needs to be instantaneous to prevent the breach or damage. For us this is just scratching the surface — we see a future where even higher-level thought processes like red teaming and cyber risk analysis could be executed by AI. The sky is the limit!”
Maha Achour
Co-founder and CEO, Maha Achour founded Metawave in 2017. Metawave develops long range and high resolution imaging (arguably the very hardest problem in automotive radar) SPEKTRA radar technology which can perform real-time object classification for the purposes of safer autonomous driving in all weather conditions. Armed with a Physics background, Achour leveraged the science of beamsteering technology: a technique that focuses a narrow, wireless signal towards a specific target receiver rather than have the signal spread in all directions as a usual, less precise broadcast antenna would. (This technique is also behind the success of 5G technology). In 2020, achieving this feat was the first of its kind. Metawave also has its own AI (AWARE) platform, making the company a fusion between AI/ML and their revolutionary sensing technology. They are able to use the latest advancements in deep learning in the hopes of making autonomous driving safer. Achour also holds over 450 pending and issued patents and has over 20 years of experience in the radio frequency, wireless, optics and networking industries.
“Don’t search for opportunities - instead observe, learn, and dare to ask the first simple question.”
Joumana Ghosn
Ghosn was a master’s student in computer science at the University of Montreal when she met Yoshua Bengio. She dabbled with computer vision and machine learning and eventually ended up pursuing a PhD program back in 2002 under Bengio’s supervision as one of only 3 women on the team. She is now a researcher in applied machine learning at Mila. She has developed an expertise in natural language understanding, specifically at Nuance Communications, where she worked with a team of deep learning researchers to create virtual assistants and computer-assisted clinical documentation improvements.
“I believe that women must have confidence in their abilities to advance within an organization. When I look back on my career, I have been fortunate enough to hold management positions that interested me and suited my abilities. I realize, however, that I never sought my promotions. They came my way and I was happy with them, but I realize that I could have been more assertive. I believe that many women have the same reflex as me and are reluctant to talk about their ambitions and wait for opportunities to be offered to them. We need to teach women to take more calculated risks, to put themselves forward professionally. Fighting for the best job opportunities and conditions is a value that is instilled in men very early on. We should do the same for women.”
Fei Fei Li
Li is a Chinese-American computer scientist and professor at Stanford University who is well-known for her work in establishing ImageNet: an object classification dataset that enabled the revolutionary advancements in computer vision of the past decade. Her research interests include cognitively inspired AI, machine learning, deep learning, computer vision and AI in healthcare especially ambient intelligent systems for healthcare delivery. In the past she has also worked on cognitive and computational neuroscience. She is also cofounder of AI4ALL, a nonprofit that aims to increase diversity and inclusion in AI education, research, development and policy.
“The real existential challenge is to live up to your fullest potential, along with living up to your intense sense of responsibility and to be honest to yourself about what you want.”
