Women Leading The AI Industry: “The primary concern I have is bias in AI.” with Dr. Rebecca Parsons of ThoughtWorks and Tyler Gallagher
The primary concern I have is bias in AI. It’s one thing when Amazon gives someone a recommendation they don’t care about, but it’s another thing when an algorithm is giving a misinformed recommendation to a judge or a doctor. This has real consequences for people.
I had the pleasure of interviewing Dr. Rebecca Parsons. Parsons is ThoughtWorks’ Chief Technology Officer with decades-long applications development experience across a range of industries and systems. Her technical experience includes leading the creation of large-scale distributed object applications and the integration of disparate systems. Separate from her passion for deep technology, Dr. Parsons is a strong advocate for diversity in the technology industry.
Thank you so much for doing this with us! Can you share with us the ‘backstory” of how you decided to pursue this career path?
When I was young, I always knew I’d get a PhD in something, I just didn’t know what. I had a strong love for math and science, and eventually that translated into a passion for programming. It was all sparked by my high school algebra teacher, who gave me a textbook and encouraged me to learn. I earned my undergraduate and worked towards a master’s degree, working full-time for seven years, before eventually earning my masters and PhD from Rice University in computer science. The program gave me the headspace I needed to study the subject deeply and move my career forward.
What lessons can others learn from your story?
Don’t be afraid to try something new. I believe that too many people limit themselves. My parents instilled in me that if I worked hard enough, I can achieve what I dreamed. I hope others can find the confidence to learn new things and go after what they are passionate about.
Can you tell our readers about the most interesting projects you are working on now?
A big focus of mine right now is the notion of continuous intelligence. We’re looking at extending the concepts behind continuous delivery and applying that to machine learning applications. By developing tools and processes around continuous intelligence, we can better manage the flow of models through development and into production. A lot of AI developments just end up as toys or proofs of concept, but I’m focused on bringing them live for a more practical use that will drive better outcomes. It’s an exciting challenge!
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?
Although I had been curious about AI, I didn’t begin studying it closely until joining the AI Special Interest Group that was part of DECUS (Digital Equipment Computer Users Society). Through collaboration with many intelligent people within the group, I began my exploration of knowledge representation and machine learning systems. I credit this experience for setting me up for my work in genetic algorithms and evolutionary computation, beginning at Los Alamos National Laboratory where I worked as a Postdoctoral Fellow.
What are the 5 things that most excite you about the AI industry? Why?
First, it’s exciting to see how much AI has advanced in recent years. We now have the compute power and memory to be able to execute algorithms and data that we’ve never been able to do in the past. It gives us the potential to keep up with systems and data sets that humans don’t have the capacity to keep up with manually. This opens the door for really powerful things.
Similarly, what’s also exciting is the concept of intelligent empowerment. AI allows for us to automate simple work and offload it from humans, which ultimately empowers humans with more time to focus on larger issues and needs. AI helps us to get more out of human capability.
I’m also incredibly excited to see the sheer volume of compute power that’s emerging as we explore quantum computing and increasingly smart systems. I see great opportunities, especially for industries such as smart cities and smart factories.
Additionally, the breadth of application domains that AI helps to deliver is impressive and it will continue to have positive implications for software development, such as increased security and reliability.
Lastly, I’m intrigued by the potential for the approach that was used to train the AlphaGo program, which beat the Go master. This is an incredibly difficult game, and the technology was able to identify a strategy that a human had never used or trained the system to do. What’s even more fascinating, the program did not involve any brand new breakthrough technology, it is successful simply based on the way old technology was trained.
What are the 5 things that concern you about the AI industry? Why?
The primary concern I have is bias in AI. It’s one thing when Amazon gives someone a recommendation they don’t care about, but it’s another thing when an algorithm is giving a misinformed recommendation to a judge or a doctor. This has real consequences for people.
Secondly, we are in a transition period of societal understanding of technology. We’re straying into territory where we don’t have parameters to guide the way. For example, should a manufacturer of a driverless car build it in a way that would save the life of a pedestrian in an accident, or save the life of the driver? People want to be altruistic about broad applications of AI technology, but there are a lot of issues that need to be discussed first.
Similarly, there are many who don’t understand AI and its limitations well enough, which leads people to assume it has a level of objectivity or competence that might not be true. It’s important for people to understand the technology’s potential faults or errors before relying on it.
I’m also concerned about hype of AI. This technology is powerful enough to have a tremendous impact on society. When something is hyped, the potential damage is so much greater.
Lastly, on a technology level, we need to be aware that the data of many organizations is old and messy. If this isn’t taken into account when training systems or mining data, there could be unintended consequences. Data does not age well.
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?
Every technology has the potential to do great harm. We need to recognize, the more control we give to the systems, the faster things are going to be happening. At the same time, humans can’t speed up their reaction time, which could eventually pose a risk. For example, there have been cases where an algorithm has been used for investing funds that ultimately led to banks going bankrupt in minutes. I think we are a ways away from a large threat to humanity, but I don’t completely discount it.
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?
The more we can understand the basis on which these systems are operating, the more we can prevent. We need to put more emphasis on understanding how these systems are working.
How have you used your success to bring goodness to the world? Can you share a story?
I once heard a story about a young woman who was told by her male advisor that she should drop out of graduate school. He told her she was taking the opportunity from another man and that she should be a mother instead. It was a jaw-dropping moment for me and led me to decide I needed to be a more visible role model. From that moment on, I’ve made it a wholehearted mission to serve as a resource for other women in tech, who may be feeling discouraged or outnumbered. ThoughtWorks has incredible networking and professional development groups that I’ve enjoyed participating in. I’ve also shared my perspective on the importance of women and other diverse technologists at the annual Grace Hopper Celebration.
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?
I would simply advise women to support each other. You don’t have to get along with everyone, but being a support system is incredibly important. Secondly, pick your battles. There are some things that just aren’t worth fighting, even though it might be unfair or hurtful. Lastly, don’t artificially form your opportunities. You are a woman in a human’s world.
Can you advise what is needed to engage more women into the AI industry?
Emphasizing the potential for AI to solve real problems. It’s not there just to play Go and to do cute things. It has great potential, and women are more likely to care about the outcomes and value it delivers. Women want to solve problems.
What is your favorite “Life Lesson Quote”? Can you share a story of how that had relevance to your own life?
While it’s not necessarily a specific quote, I love the overall life lesson of ‘never give up’ — like The Little Engine That Could. Those are simple yet powerful words that I’ve tried to live by since I was young. For example, there’s a common perception that once you begin working, you’ll never be able to go back to school. I knew there was more that I wanted to learn even after I had started my career, so I challenged that perception by pursuing my master’s degree while working full-time and then going back to school full-time to earn my PhD.
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 envision incredible opportunities stemming from an IT revolution which I call RevIT. Technology is not neutral and depending on its application, the outcomes can be positive or negative. We need a mindshift to create a future state where we get the policy and ethical decisions about technology right. A movement toward a world where technology truly serves people — and where technologists can be proud of the code we create, the data we collect, and the technologies we release.
How can our readers follow you on social media?
@ThoughtWorks
@RebeccaParsons
