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“It is a myth that doing technical work requires a traditional STEM education” with Penny Bauder & Michelle Gaseor

Doing technical work as a woman or any other person doesn’t require a traditional STEM education. I’m greeted with slack jawed surprise whenever people learn I majored in history. As Chris Reardon eloquently argued, the future of tech is STEAMD (STEM + Arts and Design) and not just STEM. As we move into the future, I see […]

Doing technical work as a woman or any other person doesn’t require a traditional STEM education. I’m greeted with slack jawed surprise whenever people learn I majored in history.

As Chris Reardon eloquently argued, the future of tech is STEAMD (STEM + Arts and Design) and not just STEM.

As we move into the future, I see the nature of work and what we do will change greatly. Today, we already see no and low-code user interfaces overtaking what used to require programming. Many basic coding jobs (that you can go to a bootcamp to learn) will change/disappear. There will, however, always be the systems builders, with jobs that are heavy in math, making 3D engines, operating systems, etc.

As computer science becomes increasingly technical and design influence and spending rises, we need to build strong communication and collaboration between these two disciplines, which can be like oil and water.

We need more K-12 enrichment focused on collaboration between the arts and sciences. Where is “Kids Who Tech” and not just code?


I had the pleasure to interview Michelle Gaseor. For nearly two years, Michelle has been at the forefront of advanced cognitive solutions as the first AI Intent Recognition Designer at IPsoft, the 20-year-old AI pioneer. In that role, Michelle is pushing the limits of how natural conversations between humans and AI can be, using a combination of design strategy and data science.

Michelle’s job includes everything from user research and building Amelia’s machine learning models to creating a unified dialogue content strategy to bring Amelia alive in different markets.

Most recently, Michelle partnered with a Fortune 500 insurance client. She established a five-person team focused on intent recognition design. With her leadership and training, the team exceeded pilot intent recognition goals on the project.

Michelle works in emerging technology because she loves the challenge of solving problems no one has cracked yet. She is also committed to fighting for representation in AI work. She breaks down barriers through inclusive education and coaching for clients, focused on removing the intimidation factor that disempowers less technical team members. Outside of work, Michelle is an active professional mentor for young women studying STEM subjects in college.


Thank you so much for doing this with us! Can you tell us a story about what brought you to this specific career path?

Technology as a force driving cultural change fascinates me. Growing up with a computer scientist dad and a teacher mom, I spent my childhood with Starfleet crews and Dr. Quinn Medicine Woman.

I’ve been chasing technology in my career ever since. First, as a history Ph.D. student, studying the late 1800s. Then, at McGraw-Hill Education, where I developed adaptive learning experiences driven by complex algorithms. Finally, at IPsoft, designing algorithmically-driven conversations for artificial intelligence.

Working on the kind of technology that inspired me as a kid energizes and inspires me still today.

Can you share the most interesting story that happened to you since you began at your company?

Six months after I started at IPsoft, I realized our organization — and our industry — lacked a critical role. No one specialized in creating scalable strategies for machine learning/intent recognition. This strategy would allow us to construct increasingly complex and conversationally sophisticated AI experiences. I spoke up, explaining why we needed these specialists. Originally, I thought I might be an understudy to these new specialists. Leaders in my company surprised me by saying that I should take on this new job myself. As I leapt headfirst into defining the new role, I studied more in those first six months than I did in probably four years of college. Flash forward a year, and we now have a diverse global team of five “intent recognition designers.” We’re driving best practices and pushing the limits of today’s AI technology across voice and chat experiences.

Can you share a story about the funniest mistake you made when you were first starting? Can you tell us what lesson you learned from that?

In school, engineers learn to communicate in very specific ways using unambiguous, explicit vocabulary. Using Given, When, Then scenarios to describe how features should work. Starting with streamlined answers to questions and trusting that other people will ask questions if they want to know more.

Engineering-style communication allows global teams to quickly get on the same page to get things done.

When I started my conversation designer role, my natural communication style gravitated to the polar opposite side of the spectrum. I told long, colorful stories to get my points across. And, as a result, I struggled to communicate designs effectively to my engineering counterparts.

It took some Eliza Doolittle-level coaching from one of my engineering colleagues to teach me to speak and write like an engineer.

The experience taught me one of the most important lessons of my career: communication isn’t one size fits all. You need to adjust your style to best accomplish your goals.

What do you think makes your company stand out? Can you share a story?

I think it’s the people and the culture of multidisciplinary collaboration that’s developing. As our design team has grown, we’ve shifted from being an entirely engineering-led company to one where design and engineering are becoming equal partners. We’re doing our most innovative and successful work when we’re working together to build new and impactful things with AI technology, all while keeping the end user top of mind.

Are you working on any exciting new projects now? How do you think that will help people?

Yes, we’re always beginning new enterprise and consumer-facing conversational AI projects. I’m currently designing a consumer-facing experience for an industry that’s just moving into AI. I can’t say much more about the project, but it requires gracefully handling a situation that requires high user empathy. Any time we can get people support faster and more seamlessly after trauma, I consider that a win.

Ok super. Thank you for all that. Let’s now shift to the main focus of our interview. Are you currently satisfied with the status quo regarding women in STEM? What specific changes do you think are needed to change the status quo?

As people working in Conversational AI, part of our job involves making sure that AI understands the complexity of human communication. This starts with recognizing that humans speak and write very differently based on a wide variety of factors, ranging from age, background, gender identity, region, and conversational interface, to name a few.

Think, for example, about the SNL skit for “Amazon Alexa Silver” — an Alexa designed for the “Greatest Generation” that responds to any name “remotely close” to Alexa and that repeats herself for people who are hard of hearing.

Conversational AI technology comes out of the box with a baseline understanding of language (or in our case languages). It then falls to your implementation team — people like me — to uncover 1) who will be using this product, 2) how they will interact with it, and 3) how it should interact with them. We have to plan for the nuances, for example, of how Canadian French might be different than the French people in France speak. A key part of what we do is finding and planning for the gaps between baseline conversational AI technology and the communication styles of users.

Effectively designing for the complexity of human communication requires having empathy for and matching that level of detail in how we build these technologies. Developing that sensitivity takes time and exposure, and unconscious bias can easily slip in. We don’t always realize what we don’t know or haven’t experienced. And, there are limits to how much empathy we as individual people can have for understanding the lived experiences of others.

How, then, can we match this complexity? Representation is an imperfect and partial solution.

Currently, a huge gap divides the people working in AI and the people using the technology. And, it’s a gap that is as complex and multi-faceted as how we communicate globally as humans in the case of conversational AI.

The AI Now Institute is leading research into this gap for the AI field in general. I find that their study findings (see page 3) — published in April 2019 — best speaks to the state of the industry.

In sum, they argue that a race and gender diversity crisis is leading us to create discriminatory AI systems and products that are “replicating patterns of racial and gender bias in ways that can deepen and justify historical inequality.”

I agree that our overwhelming focus on “women in tech” as part of the solution is too narrow and that it can privilege white women — like me — at the detriment of people with non-binary gender identities and other under-represented groups.

The AI Now Institute also recommends detailed solutions (see page 4) for how we can improve workplace diversity and address discrimination and bias in AI systems that I endorse based on my experience working in conversational AI.

One critical item they highlight is that diversity in product design and development only goes so far. We also need greater diversity at the decision making level to ensure we’re selecting the right use cases and the right solutions to build.

In your opinion, what are the biggest challenges faced by women in STEM or Tech that aren’t typically faced by their male counterparts? What would you suggest to address this?

Generally, research boils down the main challenges faced by women to:

  1. Role models and mentorship
  2. Work culture
  3. Work/life balance
  4. Leadership pipeline and promotion opportunities
  5. Confidence and visibility
  6. Unconscious bias

Ultimately, impacting these challenges starts with individuals.

As an individual, I mentally prepared myself to face these challenges when entering the AI market. But I also looked long and hard at my feelings about being a minority. Having the strength to take a stand for change ultimately comes from re-framing internal narratives about victimhood. It’s easy to feel like a victim as a minority in tech, but this puts you in a place of disempowerment and builds a self-limiting mental narrative. How you see yourself impacts how others see you as well. I see myself as a change agent with a voice and that keeps a smile on my face.

Keeping our perspective as individuals positions us to be the change we need in society and our organizations.

What are the “myths” that you would like to dispel about being a woman in STEM or Tech. Can you explain what you mean?

Doing technical work as a woman or any other person doesn’t require a traditional STEM education. I’m greeted with slack jawed surprise whenever people learn I majored in history.

As Chris Reardon eloquently argued, the future of tech is STEAMD (STEM + Arts and Design) and not just STEM.

As we move into the future, I see the nature of work and what we do will change greatly. Today, we already see no and low-code user interfaces overtaking what used to require programming. Many basic coding jobs (that you can go to a bootcamp to learn) will change/disappear. There will, however, always be the systems builders, with jobs that are heavy in math, making 3D engines, operating systems, etc.

As computer science becomes increasingly technical and design influence and spending rises, we need to build strong communication and collaboration between these two disciplines, which can be like oil and water.

We need more K-12 enrichment focused on collaboration between the arts and sciences. Where is “Kids Who Tech” and not just code?

What are your “5 Leadership Lessons I Learned From My Experience as a Woman in STEM or Tech” and why. (Please share a story or example for each.)

  1. You can’t help others without self-care: It’s easy to overextend yourself in the service of others. You may be helpful today, but if you’re exhausted and burnt out tomorrow, it can counteract all the good you did.
  2. Studying leadership gives you a framework to understand your experience: When I face leadership challenges, I turn to frameworks I’ve internalized through reading/listening to podcasts to make sense of them. Kim Scott and Jason Rosoff’s radical candor approach is one I return to frequently.
  3. Have a code and stick to it: Our intent recognition design team started gaining traction in our organization and with clients when we wrote and published a “playbook” manifesto. Holding ourselves to a higher standard gave us the strength to push for needed change and to convert others to our perspective.
  4. Nurture psychological safety: When people first think about safety, they think “nice and cozy.” But psychological safety is about giving people the confidence that they can speak with candor. Creating good dialogue on teams involves a combination of lifting good ideas, defending opportunities for exploration, amplifying quieter voices, and redirecting people when it’s time for them to step back and give others the floor.
  5. You don’t need a title to lead: At every step of my career, I’ve led teams, rallied for good ideas, and encouraged others without official leadership/management positions. Even now, as a consultant, I lead and influence by supporting others. Don’t let the fact that leading “isn’t in your job description” hold you back.

What advice would you give to other female leaders to help their team to thrive?

I didn’t begin to truly understand other people until I became a user researcher.

Leaders and user researchers rely on the same skills to make decisions and solve problems — active listening, careful observation, and empathy.

If you want to help your teams thrive, shaking up how you ask questions is a great place to start.

Understanding your team gives you the perspective to ideate on the right next steps together.

What advice would you give to other female leaders about the best way to manage a large team?

When I worked as an Ed Tech content strategist at McGraw-Hill, I maintained consistency across a product that involved coordinating the efforts of 20+ people per project.

At that scale, managing effectively boiled down to three main things:

  1. Understanding people’s communication and work styles. Build rapport by working with others on their terms whenever possible.
  2. Setting a clear, documented direction and then delegate. Ensure people understand when to come to you for help. As needed, check in at regular intervals to give feedback and to make sure everyone is working within the plan. Delegate to and trust in your people.
  3. Developing a centralized organizational system to keep track of team logistics. I had a particularly robust SmartSheet (cloud spreadsheet platform) with some automated reminders and some places where people could take a few seconds to keep me updated.

With large scale teams, your role after setting the vision bounces from serving as a compass to batting down people’s blockers.

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?

I’ve had help and support at every stage of my career. Great college professors, parents, neighbors, friends, co-workers, authors, and acquaintances who have taken time out to do informational interviews. I could fill a whole page with names and stories of people I’m grateful for in my life.

I want to call out one particular person, however, who isn’t listed above.

I believe in the transformative power of storytelling. Stories are the one type of inspiration and support that everyone has access to, in one way or another.

The storyteller I’m most grateful for in my life is Tamora Pierce. As one of the original feminist young adult fantasy writers, Pierce gave me role models of empowered women pursuing their dreams against impossible odds at an impressionable time in my life. Her influence helped me grow up into a confident, self-aware woman who takes risks and forges less traveled paths for herself and others. Here’s to you, Tammy!

How have you used your success to bring goodness to the world?

I’ve been an active mentor with an amazing organization called America Needs You since 2016.

Together, we fight for economic mobility for ambitious, first-generation college students, called Fellows, through transformative mentorship and intensive career development.

Through this organization, I’m spreading awareness about how women can be involved in STEM fields.

My first Fellow, Sandhya, is wrapping up her undergraduate degree this year in electrical and computer engineering. And I’ve recently started working with a new Fellow, Crystal, who is studying mechanical engineering. I’m proud of both of them.

Volunteering with America Needs You has been a fantastic experience all around. If you live in California, New York, New Jersey or Chicago, take a few minutes to check it out!

You are a person of enormous influence. If you could inspire 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’m a techno-optimist who believes that responsible tech can make the world a better place. I think we as millennials (and, dare I say it, Gen X-ers and Boomers) can do more to inspire and arm Gen Z to use tech to help take on our biggest challenges.

And, that begins with exposing kids to technologies like AI. These technologies pose existential risks and equally powerful opportunities to take on the major issues that face us today. Intimidation is one of the main factors holding people back from pursuing careers in AI. They worry that they need to be math experts or geniuses when the basic concepts can be boiled down for anyone to learn. As a consultant teaching AI to technical and non-technical people alike, spreading this message and confidence is central to what I do.

We need the future math genius AI algorithm writers as much as we need thoughtful designers, product owners, and ethicists who will ensure those algorithms make our world a better place. And, we need to teach these two groups of people how to collaborate and communicate from an early age so we can capitalize on this teamwork in the workplace.

Can you please give us your favorite “Life Lesson Quote”? Can you share how that was relevant to you in your life?

This is my new favorite quote. As women and people, we can struggle with failure. Sometimes it’s not until you feel unsafe that you take risks, and you stumble as you gain the clarity to solve problems:

“I’m saying when God slams a door on you it’s probably a shit storm. You’re gonna end up in rubble. But it’s OK because without all that crap overhead, you’re standing in the daylight … for sure you won’t find your way out of the mess if you keep picking up bricks and stuffing them in your pockets. What you have to do is look for blue sky.”

I recently heard an awesome discussion about this quote from Barbara Kingsolver’s book Unsheltered on the Nerdette podcast. Hats off to you Greta Johnsen and WBEZ Chicago!

We are very blessed that very prominent leaders read this column. Is there a person in the world, or in the US with whom you would love to have a private breakfast or lunch with, and why? He or she might just see this if we tag them 🙂

Ruth Bader Ginsberg. Ruth’s story as a woman making her way in a male-dominated profession energizes and motivates me.

Ruth’s legal career is the reason why women have equal protections and rights under the law to pursue careers like mine today.

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