AI enabled Healthcare: As we all know, AI has made tremendous progress in the field of medicine: helping doctors with accurate patient diagnosis, predicting their future health and recommending treatments. AI has many other applications in health and medicine including expediting drug discovery, helping accelerate the search for a coronavirus vaccine, and in helping detect Covid-19 cases.
As part of my series about the women leading the Artificial Intelligence industry, I had the pleasure of interviewing Huma Abidi.
Huma Abidi is a Senior Director of AI Software Products at Intel, leading a globally diverse team of engineers and technologists responsible for delivering world-class Deep Learning and Machine Learning products that enable customers to create artificial intelligence (AI) solutions. Huma joined Intel as a software engineer and has since worked in a variety of engineering, validation and management roles in the area of compilers, binary translation, and AI and deep learning. She is the founder of the Women in Machine Learning group at Intel.
Huma is passionate about women’s education, supporting several organizations around the world for this cause, and was a finalist for VentureBeat’s 2019 Women in AI award in the mentorship category. She has delivered keynotes at many major events including the O’Reilly AI conference in San Francisco, the MIT Pan Arab conference in Lebanon and the Dell HCP conference in India.
Thank you so much for doing this with us Huma! Can you share with us the ‘backstory” of how you decided to pursue this career path?
I grew up in a small town in India. My dad was an engineer and my mom a teacher, and they encouraged my sister and I to pursue science, the same way they encouraged my brother. So the interest in science and technology was there from the start and I found science fiction especially intriguing, to imagine if machines could speak, see, or interact with humans.
I was studying to become a doctor, and just as I finished my Bachelor’s in chemistry/Pre-Med I got introduced to computers. I learned programming and ended up with a Master’s degree in computer science from the University of Massachusetts. My first job out of school was as a software engineer at Intel, where I’ve been working for over two decades in many different technologies. For the past few years, my focus has been in the area of AI.
Because of some major technological breakthroughs in the last decade, things we had previously imagined as science fiction are now real-world applications enabled by AI. I feel very fortunate to be working in this super exciting field. I believe this is the most exciting time of my career.
What lessons can others learn from your story?
The first thing I’d like to say is to not let culture, language or location be a barrier. If you are really passionate about something, you will find a way to achieve it.
Second, it is ok to change your mind or to change directions if you find something else compelling. I was pursuing my career in medicine and found computers to be more fascinating and changed gears.
Third, I think we should not be afraid to explore different areas, even those that may seem unrelated to our job. That is why I am passionate about encouraging girls to learn about technology. Anyone can be a user, or, even better, a contributor, to emerging technology areas like AI, because these are so interdisciplinary.
Can you tell our readers about the most interesting projects you are working on now?
One of my main jobs is to make sure that the latest AI workloads perform well on Intel hardware. It is super exciting to work on and optimize different types of AI use cases with our customers and partners.
These vary from healthcare companies using AI for faster drug discovery and creating anonymized CT scans using 3D GANS to help doctors, to speeding up the largest recommendation engines, to automating detection of silicon packaging cosmetics defects, to automating traffic monitoring, and more. There are several “AI for social good projects” that we’ve worked on with our partners which have been especially rewarding.
On the personal side, I really enjoy combining my hobbies such as painting and embroidery with AI. Using the Neural Style Transfer technique I was able to blend my painting with another painting (e.g. Van Gogh or photo of a chip) to create new art.
None of us are able to achieve success without some help along the way. Is there a particular person who you are grateful towards who helped get you to where you are? Can you share a story about that?
Certainly! I’ve had a great number of managers and mentors who have given me wonderful advice and encouragement throughout my career. From telling me I’ve got what it takes to boosting my confidence to offering specific advice on what I should do to go to the next level.
Early in my career, a senior woman executive gave me a great piece of advice: if you cannot find a woman boss (it was not so common at that time), then work for a manager who has daughters. He’d want you to succeed because he wants a world where girls and women succeed.
Another piece of advice was given to me by my manager almost 15 years ago, but it still helps me. Before a presentation to senior executives, I was very nervous because I felt I was not an expert on the subject at hand. My manager sat me down and told me that I did know enough, and in fact knew a lot more than my audience did because I was the one working in this area. That realization gave me a lot of confidence.
What are the 5 things that most excite you about the AI industry? Why?
AI is very exciting! It is moving very fast and there are endless areas where it can be applied. Some that I find fascinating are:
- AI enabled Healthcare: As we all know, AI has made tremendous progress in the field of medicine: helping doctors with accurate patient diagnosis, predicting their future health and recommending treatments. AI has many other applications in health and medicine including expediting drug discovery, helping accelerate the search for a coronavirus vaccine, and in helping detect Covid-19 cases.
- Another area in which AI has moved very fast is Conversational AI and the deployment of AI in the Natural Language Processing (NLP) domain. Smart assistants like Alexa, Siri, and Google Assistant anticipate, optimize, and automate daily life to translation between virtually any two languages. GPT-3, which is the largest AI-based pre-trained language model ever produced with 175 billion machine learning parameters, is capable of producing high-quality text. It takes a prompt and attempts to complete it, for example this GPT-3 written article couldn’t be distinguished from ones generated by humans.
- AI and Art: Another significant milestone was when AI algorithms were used to create world class art autonomously. Christie’s recently sold its first piece of auctioned AI art — a blurred face titled “Portrait of Edmond Belamy” for 432,500 dollars. AI programs can also create music in the style of classical composers (e.g. Mozart), or contemporary artists (e.g. Lady Gaga). Also, human artists are using AI to create new works — a fascinating example of human-machine collaboration.
- Another area where AI is showing great potential is Multimodal AI, that involves processing different modalities or data types such as image, text, speech and numerical data together to create a holistic view. Earlier this year, Facebook launched the Hateful Memes Challenge for AI to understand content the way people do, e.g. when viewing a meme, it is more meaningful to understand combined meaning of photo and text rather than independently.
- AI for Social Good projects: it is heartening to see many leaders in AI working to use AI to solve societal issues and make a positive impact in the world. At Intel, we work on many AI for Social Good programs, with partners. Some examples are preventing exploitation of children, preventing illegal forest logging and animal poaching, detecting water contamination, and enabling a wheelchair for paraplegics which can be controlled by facial gestures and more.
What are the 5 things that concern you about the AI industry? Why?
- Bias in AI: AI models are created by humans and reflect, or amplify, human biases. If AI used for a movie recommendation is flawed because of bias in the data or algorithm, the impact may not be that great, but in cases where AI is used for healthcare risk predictions, policing, judicial sentencing, finance/loan approval etc. then the results could be disastrous for those on the receiving end of the decision, if the prediction was flawed due to inherent bias.
- AI has the potential to create a lot of wealth, and thus potential to create even more inequality. Those with access to high tech and AI will continue to have advantages and wealth may be concentrated to a few countries or companies. This may increase the wealth gap between the richest and poorest in our society.
- Regulation of AI: policies and laws for promoting AI at a global, regional, and national level are not yet clearly established. AI should be regulated: similar to nuclear weapons and bio-chemical weapons, AI use in the military should follow agreed-upon protocols. To avoid negative impacts, lawmakers around the world need to adjust regulations and laws to include the new technological possibilities, limiting abuse wherever possible. This urgent process has only just started.
- Deepfakes are based on generative adversarial networks (GANs) that have extremely positive uses cases particularly in medicine, such as generating anonymized high fidelity MRI images to train algorithms for disease detection. However, they have very high potential to be misused, such as false celebrity videos, fake news, hoaxes, and financial fraud. There are many initiatives such as Google’s Deepfake Detection Challenge which are aiming to filter out misinformation.
- Diversity in AI: We need to make sure that our current and future algorithms are not just powerful but also ethical and fair, concerned about bias, unpredictability and opaqueness and these are not solely a technical challenge. To build a correct AI system you needdomain experts, technologists, data scientists, lawyers, consumer advocates, public health professionals, industrialists, designers, ethicists, anthropologists, and policymakers: a diverse workforce representative of the population that solution will be serving.
We need to define and build clear standards and processes with quantifiable measurements of quality and robustness leading to ethical solutions that are fair, transparent, and explainable.
As you know, there is an ongoing debate between prominent scientists, (personified as a debate between Elon Musk and Mark Zuckerberg,) about whether advanced AI has the future potential to pose a danger to humanity. What is your position about this?
In the short term, in the next couple of decades I believe that Zuckerberg is correct. In its current form AI (narrow AI that can perform specific tasks) is already enhancing our lives in so many areas that no one thought possible. We’re already seeing AI make its impact on our daily lives, both in visible and invisible ways, and the possibilities for this class of technologies are almost limitless. AI is helping solve big challenges in consumer products, healthcare, finance, education, retail, agriculture, transportation, oil and gas, government, etc.
Musk’s concern should not be ignored either. The doomsday scenario that he is referring to could come into play when AI has reached AGI (Artificial General Intelligence) which is when machines will be as smart as humans. In certain areas, machines are outperforming humans but we are very far from when they will be at the same levels as humans in learning even the most basic things. AGI may happen in decades, centuries or never. No one knows this for certain but the disruptive effects it could have on society cannot be understated.
What can be done to prevent such concerns from materializing? And what can be done to assure the public that there is nothing to be concerned about?
As Marie Curie said “Nothing in life is to be feared, it is only to be understood. Now is the time to understand more, so that we may fear less.”
I think it is very important that all of us understand this technology, so that, as a society, we can identify and respond to both the opportunities and the potential threats. Clearly, there are areas of immediate concern — such as how to deal with deepfakes and other forms of disinformation, and how to prevent bias.
None of us can predict when AI will reach AGI and whether the doomsday scenario even has merits. We should however make sure that there are checks and balances in place. We need to start addressing issues such as deepfakes, bias in AI, data privacy, regulations etc. that are of immediate concern.
How have you used your success to bring goodness to the world? Can you share a story?
I’ve spent the majority of my career advocating for women and underrepresented minorities (URM), promoting diversity, equity and inclusion in STEM careers. This is especially important in technology and AI where the gap is even larger. If the people/group who are creating the technology is homogeneous, then it will work well for that specific population or group and not for all, which is why it is extremely important to have a diverse workforce — because diverse groups will build better products for a diverse population.
I was heavily involved in Intel’s goal to reach full representation of women and underrepresented minorities in the U.S. workforce by 2020. By participating in diversity hiring events, helping new hires navigate through Intel, mentoring individuals and leading cohorts, I helped with the retention of women and URMs. As we look to 2030, our goal at Intel is to increase women in technical roles to 40% and to double the number of women and underrepresented minorities in senior leadership.
Throughout my career, I’ve mentored and advised a large number of women and girls both at Intel and externally. I frequently speak at several high schools and forums such as Girls Who Code and Girl Geek X. I also serve as an Advisor at “Led by” which provides professional development to minority women.
I am the founder of Women in Machine Learning at Intel (WiML) where we discuss technical topics as well as have sessions on mindfulness.
I love to paint and experiment mixing AI and art. For the past few years I’ve supported Givelight Foundation, a global humanitarian organization that provides support and education to orphanages. The founder saw some of my artwork that I had created in the extra time I had during the pandemic and suggested we auction it. I don’t consider myself a great artist, but fortunately we were able to generate some money that went to the good work this NGO does.
As you know, there are not that many women in your industry. Can you share 3 things that you would you advise to other women in the AI space to thrive?
Women make up nearly half the world’s population and yet there is a large gap when it comes to technical roles. This is even more critical when it comes to AI, where the lack of diversity can cause biases.
I believe that AI is the future, and it is already changing the world that we live in. Women in particular should have a growth mindset and proactively participate in and seek opportunities in the AI space. AI is an interdisciplinary field and there are many opportunities to apply AI to your current domain, whatever that may be. There are a large number of excellent online courses on AI and machine learning (ML), as well as podcasts that can help you keep up to date on the advancements of AI.
Networking is very important: connecting with others in the field, participating in events and conferences. There are numerous organizations, talks, and meetups that will help you get connected to the other women (and men) working in different roles in AI who will be willing to share their work and experiences with you. Make sure you have mentors or champions who are there to provide you help and support and the right connections as needed.
It is very important to be passionate about your work — you should enjoy what you are doing! For example, working on AI for Social good or neural style transfer energizes me because it is something that I love doing and is combining my passion with my work.
Can you advise what is needed to engage more women into the AI industry?
Tech companies are facing a lack of gender parity and unless we build a pipeline of women in technology, the gender gap will not be narrowed or closed. It’s especially important to get more women and underrepresented minorities in AI, because of potential biases lack of representation can cause when creating AI solutions.
We need to be engaged early on, before young girls start developing negative perceptions. There should be role models who can show them that it is cool to be an engineer or a scientist. It is not that women are not good at sciences, and there are a lot of women in medicine, but somehow engineering and AI are seen in society as led by men. Thus it is very important to have women representation and role models in AI. Fortunately we now have many great role models such as Fei Fei Li who is leading human centered AI at Stanford and Meredith Whittaker, who works on social implications through the AI Now institute at NYU, plus many, many more women leaders emerging in AI.
We need to work together to adopt inclusive business practices and expand access of technology skills to women and underrepresented minorities. At Intel, our 2030 goal is to increase women in technical roles to 40% and for that we will work with other companies, institutes and communities to accelerate adoption of inclusive business practices including equal pay and expand access of technology skills to women and URMs.
What is your favorite “Life Lesson Quote”? Can you share a story of how that had relevance to your own life?
“Don’t sweat the small stuff and it’s all small stuff.”
Many years ago, when my son was in kindergarten, I was about five mins late in dropping him to school. I was very stressed out about that. I called my husband and told him how we need to change things around so this doesn’t ever happen again. The entire day it seemed like I had failed at something that is so basic.
When I came home I noticed a little gift wrapped package on my bedside table, I opened it and it was the book “Don’t sweat the small stuff and it’s all small stuff.” That mantra has helped me keep calm and, in fact, has helped our family handle every situation better.
You are a person of great influence. If you could start a movement that would bring the most amount of good to the most amount of people, what would that be? You never know what your idea can trigger. 🙂
I have a lot of ideas! Here are a few.
I think women’s education in tech and particularly AI is the way to create diverse and inclusive AI. “AI for ALL” requires that we also include everyone, including women and URMs, into AI and create equity for them in their professional AI careers. Explosive and transformative AI growth demands a larger workforce to make progress. Start young at elementary to middle schools (as students are most impressionable at that age) to prevent sexist or other negative stereotypes and myths about engineering or tech career paths, particularly for girls.
Just like FDA approval is needed for drugs, there should be some kind of approval before deployment of AI solutions. This should check for biases and ensure that it is ethical, fair, transparent and explainable.
While staying at home during the pandemic, we spent some time in the garden, learning about plants and vegetables that we can grow ourselves at home. If possible, it is a great way for families to spend time outdoors, learn about plants and eat healthy. Some cities in the US have shared/community gardens which can ensure not only fresh healthy produce but also bring people together.
How can our readers follow you on social media?
This was very inspiring. Thank you so much for joining us!