As you’re building up your skills, find ways to apply them to projects and document the process. Building this type of portfolio will bring visibility to the work that you’re doing and it’s a fun way to develop your skills.
As part of our series about the women leading the Artificial Intelligence industry, I had the pleasure of interviewing Merav Yuravlivker.
Merav has over a decade of experience in the education field, from classroom teaching to instructional design and building online learning platforms. As a co-founder and the current CEO of Data Society, she helps companies save millions of dollars with instructionally sound and effective data science training programs. Merav is passionate about transforming how professionals use data and how companies invest in their staff.
Thank you so much for joining us in this interview series! Can you share with us the ‘backstory” of how you decided to pursue this career path in AI?
My career path was not traditional. I started my career as a teacher in New York City Public Schools and spent several years in the classroom. While I saw tremendous growth in my students, I wanted to make an impact beyond a single classroom. Next, I worked at the International Baccalaureate Organization, training teachers and developing online training programs.
A few years after that, I was thinking about broadening my impact again and that’s when I met one of my co-founders, Dmitri Adler. He had spent his career on Wall Street, drowning in data and Excel spreadsheets. In the process of looking at more efficient ways to do his work, he discovered a way to condense several weeks of work into an afternoon by building an automated script. I knew that I was looking to take my impact to the next level and this conversation sparked my interest. He had already been working with our third co-founder, John Nader, who is now our COO and general counsel, to build the strong foundations of our company.
Even though I didn’t know much about data science, I started coming in after work and on the weekends to learn how to program and design the best practices for our student experience, which is the cornerstone of who we are. Six months later, I quit my full-time job.
It was a risk, but I had faith in our idea and our team. Over the past seven years, we’ve built customized, industry-tailored training solutions and have partnered with numerous organizations to educate, equip and empower their workforce with the skills to achieve their goals and expand their impact.
What lessons can others learn from your story?
I didn’t have the traditional background that many other founders had in the tech space. I didn’t know how to program, nor did I know how to build a team. But I am a teacher at heart, and I love solving challenges. Education is my passion and is the core of our business. The desire to see others benefit from learning is a strong motivator and has been the driving force for me to take on endeavors from which others may turn away. I set a goal, put my head down, and accomplish what I set out to do. My desire to help others overpowered any doubts that I had, including fear of failure, so that I could focus on building a company that shifts the way professionals and organizations use data.
Can you tell our readers about the most interesting projects you are working on now?
The COVID pandemic has shifted the way that we work and think about productivity. While our data science programs have developed data-empowered workforces and helped thousands of professionals unlock new potential to help further their organizational goals, we’ve also seen how important it is to feel connected to something bigger and how motivating it is to learn with friends and colleagues. Time and time again, our programs have driven impact and innovation thanks to the connections that students make in class. Especially with new techniques and technologies, having others learning alongside us is key to building a culture of continuous learning.
One of the projects we’re working on now is a User Community Platform that will create a centralized hub for students to view new learning opportunities and communicate with their colleagues. It is powered by AI and ML to identify skills gaps between a professional’s current and desired states and provides customized learning programs for that individual. There are many other features that we’ll roll out by the end of this year and into 2022, but what I’m most excited about is supplementing our interactive instructor-led programs with additional support and resources to create a holistic and supportive ecosystem.
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?
The support network that I have around me is so vast, it’s difficult to select one person. From my co-founders to my family and friends, they’ve cheered me on through countless challenges. But beyond them, I always look to the professionals we train who continue to show me the impact that our company has beyond our team.
Early in our company’s history, we were in conversations with a large company to bring in our data science training programs to train their staff. During the meeting (which was pre-COVID and in person), one of their directors came into the room. She said, “I hate to interrupt, but I just wanted to meet you. The reason I am here today is because of the classes that you taught me. I gained the skills that I needed to build a strong data science foundation and improve my confidence in continuing my education. So, I wanted to thank you for the amazing work that you do.”
To see the impact and innovation that our programs have is an incredible motivator — we’ve seen so many of our students get promoted and build larger projects. We’re developing data-empowered employees with the skills they need to succeed in the present and future. They’ve gone on to predict COVID outbreaks in nursing homes, develop comprehensive data dashboards for their executive team, identify sentiments and behavioral trends in stakeholders, and even create new revenue streams for their organizations. It’s been such an amazing experience to see the hard work that Data Society does translate into real change and help further organizational goals.
What are the 5 things that most excite you about the AI industry? Why?
- The increased focus on transparency and bias in data — with the amount of AI and ML in the world, we need to implement it responsibly to avoid adverse effects of inequality.
- The trend to make AI and ML more accessible to all — data literacy is so important to help everyone speak the same language and inspire them to find new ways to solve critical challenges. We are developing the workforce of the future and making data literacy attainable to professionals at all levels.
- Incorporating AI-assisted technology like neuroprostheses help individuals regain nervous system functions, such as movement and speech.
- Using AI and predictive models to develop vaccines on a much faster timeline by analyzing vast amounts of data and trial results.
- Incorporating AI into fighting climate change, from predicting wildfire risk to optimizing energy efficiency, there is massive potential for us to reduce our impact on the environment.
- The trend to make AI and machine learning more accessible to all — data literacy is so important to help everyone speak the same language and inspire them to find new ways to solve critical challenges
What are the 5 things that concern you about the AI industry? Why?
- The transparency of algorithms still has a long way to go before we can anticipate and mitigate any negative impacts of AI.
- Data privacy and ownership are still important debates, and we need to make sure that people have control of their own information.
- Using AI to create sophisticated fake videos and information will make it increasingly difficult for people to distinguish factual content and create a bigger societal divide.
- The ethical use of data and algorithms is not well-regulated due to the speed of innovation, which could lead to harmful effects on the population at-large.
- There is no defined responsible party when it comes to misuse of data — is it the data scientists, their managers, their executive leadership? Without clear guidelines, it’s harder to hold people accountable, which makes it harder to monitor and enforce.
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?
There is validity in both sides of the argument. While it’s true that we’re at the infancy of AI and its development, the algorithms and models that we build and will continue to build have strong limitations that would prevent them from acting destructively without human input. AI is powerful because it can ingest an incredible amount of data and identify patterns that no human could do in a reasonable amount of time. But it’s still a machine that needs our guidance and parameters to operate. When we’ve heard stories of AI acting unpredictably, it’s not because it’s started to think independently. It is because the model has successfully identified a new way of achieving a goal that we haven’t thought of before, but the answer is still within its programming. At this point, I’m more concerned about humans creating a danger to humanity, not machines.
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 key to preventing these concerns is to clearly define ethical use of data and AI, identify who responsible parties are for misuse of AI algorithms, and create appropriate ramifications when those lines are crossed. Education will also play a significant role in preventing concerns around AI and demystifying how it works. Starting with data literacy training for everyone and taking the unknowns out of this equation will help alleviate people’s fears.
How have you used your success to bring goodness to the world? Can you share a story?
A core part of Data Society as a company is finding ways to give back to our community. We developed a School ResourceMapper pro bono as part of the White House Opportunity Project initiative, which helped the city of Philadelphia identify where they needed to add more community services and helped parents see resources for their children near their schools. We’ve also partnered with World Central Kitchen, a non-profit organization that provides food and resources during natural disasters, to develop a data tool that recommended and enhanced food product suggestions to chefs in disaster areas.
As the pandemic started and we saw that people were running out of supplies, we partnered with a startup to help consumers find high-need items at grocery stores. We also sponsored a Gather for Good trivia event for our staff to raise awareness about food insecurity and raise money for Rise Against Hunger, a non-profit that provides meals and mitigates food deserts.
In addition to these initiatives, a key area of focus for me has been on increasing diversity in the data science field. I am on the founding team of Gender Diversity Across The Axis (GDATA, formerly Women Data Scientists DC) and I’m also part of DCFemTech, a coalition of women leaders aimed at amplifying the efforts of women in tech organizations.
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?
- Find support groups and look to engage other females in the tech industry. If you cannot do so, create a supportive community! For example, and as mentioned above, I was an early member of DCFemTech in Washington DC which shares resources and brings leaders together in tech to close the gender gap.
- As you’re building up your skills, find ways to apply them to projects and document the process. Building this type of portfolio will bring visibility to the work that you’re doing and it’s a fun way to develop your skills.
- Kick that intimidation to the curb! The best programmers I know still look on StackOverflow or Google to find an answer to their question. Many people on our team come from ‘unconventional’ professional backgrounds and their diversity has only strengthened our company.
Can you advise what is needed to engage more women into the AI industry?
- Just like this publication, we need to find more ways to highlight the work that women are doing in the industry. When we see more representation of women and minorities, others can see themselves reflected and the goal to enter the field becomes more achievable.
- Companies and conferences need to make more concerted efforts to reach beyond their networks, which tend to look most like themselves. It’s important to be deliberate about recruitment to ensure that you’re creating a broad talent pool that is reflective of our society.
- Hire based on potential, not just past performance. Since it can be harder for women and minorities to get relevant experience, you can ask questions about their problem-solving process and their passion projects. We’ve found that if someone’s self-taught in a programming language or technique, they’re more likely to learn other skills quickly, so it matters less what they know and more what they can pick up.
- Never make employees choose between their work and their families. Over 60% of our company is made up of women, and we have many parents (both men and women) on the team. Being a former teacher, I understood the overwhelming challenge of suddenly being responsible for a child’s education. When COVID hit, I made sure that we provided as much flexibility as possible to our team so they could take care of their families. We have the luxury of being able to work from home and we focus on results, as opposed to a 9–5 schedule. This flexibility, along with supportive policies such as three months of paid parental leave, gives everyone on our team the ability to work and still have a life outside of it.
What is your favorite “Life Lesson Quote”? Can you share a story of how that had relevance to your own life?
“Time is the one resource that you’ll never get back.”
Early in starting Data Society, I couldn’t work hard enough or fast enough. I poured myself into the company to the detriment of my relationship with my family and friends. While they were still supportive, it was difficult for me to justify taking time away from the business. During my first year, I remember reading this quote and thinking that I will never feel like I have enough time for my company. But at the same time, it was a jarring reminder that we only have a limited number of days with our loved ones. So, I started blocking off more of my time to spend with them. There will always be more work (if things go well!). It’s important to prioritize your tasks so that you maximize the value of your time in the workplace, but you need to set aside time to focus on the relationships that are important to you. If Data Society were to disappear tomorrow, I would still have an amazing community of family and friends and I am incredibly grateful for that.
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. 🙂
Education is the key to unlocking our potential and it truly is the great equalizer. If I could start a movement, it would be to build up that value here in the U.S. and shift the way that we view and treat teachers. If we truly believed in the importance of education, we’d provide more training and higher salaries for our educators. We’d make it a more prestigious career choice and make sure that our schools have the resources they need to train their students on the latest technologies. Every teacher I’ve met is passionate about their students and wants them to succeed. Great teachers can make all the difference in a child’s life — we should want the same for our educators.
How can our readers follow you on social media?
This was very inspiring. Thank you so much for joining us!