Mamta Aggarwal is the VP - Head of AiDa (AI-ML Products & Platforms) - AI Labs, American Express. Prior to this she has held a pivotal position as the Managing Director Global AI Hub, Accenture India. She has worked in prominent organizations such as ICICI Bank Ltd, Dunnhumby, and Adobe System India Pvt. Ltd. She is an AI and ML mentor on various analytics forums to help upcoming DS, MLE & DE talent. Mamta holds several research papers, patents and industry accolades in her name. 

Can you tell us about your AI journey? 

I have always been passionate about solving math problems since my school days. Numbers and data have always caught my attention. In university, I obtained my bachelor’s in Mathematics and Economics (especially Econometrics) in my masters. My higher education helped pave the path for me to start my career in data and analytics. I started my career at ICICI Bank to handle secured loan portfolio analytics for both risk and marketing teams. In those days, SAS used to be the bread and butter for all analytics professionals. However, sometime around 2010 a few analytics practitioners started using open-source coding software mainly R project (especially because SAS had become extremely expensive). This was the beginning of the industry’s transformation; it opened the doors for crowd sourcing libraries, packages and more. This shift made machine learning possible for everyone. On one side, machines were becoming heavy compute-ready and on the other, open-source coding allowed academics (with plethora of knowledge) and students (with talented curious minds) the ability to contribute to the industry. I found myself at the center of this transition. I happened to try my hands in R (very light version) while writing a term paper during my post-graduation. This experience gave me confidence to try R in my work and hence started my AI-ML journey. At that time, the industry was short of professionals with R skills. I was hired at Accenture to lead a project which used R for all ML modeling. There was no stopping thereafter, we built ML models, developed Bots, filed patents, wrote papers, created with new offerings on ML powered AI solutions. We started using all the latest and greatest tools like python, spark, pyspark etc. Today, I lead an enterprise-wide AI-ML products and platforms team at American Express’s AI Labs. I truly feel that the best of AI in the industry is yet to come! 

What is your area of expertise in AI, and what made you choose it? 

With wide applicability of data and analytics across all aspects of the business, AI is the only way through which we can achieve the increasing demand of productionalizing analytical solutions at scale. Over the last few years, I have been helping businesses in their enterprise-wide digital transformation initiatives and enabling them to put data behind all their business decisions. Recently, I became Head of AiDa at AI Labs, American Express where my team and I are creating best in class AI-ML products and platform for the modelers in our organization. We help decision science teams solve business problems through our capabilities and at the same time provide the right governance and monitoring processes around them to ensure we are being responsible in our AI game. With that being said, I consider my expertise mainly in helping businesses attain no-regret sustainable solutions to their business challenges. Today, I am helping them solve these problems by ML powered AI solutions, tomorrow it may be using something even more advanced. The key is to keep learning what’s best in the industry and help businesses achieve their goals through these learnings. 

Can you say something about your current role and your handling projects?    

I lead the AiDa products and platform team at Amex AI Labs which is developing and managing AI-ML products and platforms for our internal Amex Decision Science teams. Modelers in their modeling journey want to have an experience that is fully integrated across model development, governance, deployment and monitoring. In my role, I am building and maintaining a product that is user-focused and brings latest and greatest tools, technologies and processes. We create awareness about the product features among the users, take early on inputs and feedback, drive adoption, and create strong user support systems and processes to enhance user satisfaction. Governance and regulatory bodies are extremely strong in banking industries hence our product not only brings the latest and greatest to the table, but we do it in the right way that can be governed and monitored well. The best part is Amex has always been among the pioneers in leveraging AI-ML for its business decisions and thus, it always gives me opportunities to keep myself ahead of the industry in the AI-ML game. 

Describe some challenges you have faced in reaching where you are now.   

Establishing yourself as a leader in a male-oriented world comes with its challenges. I think you won't find any seasoned female professional who hasn’t faced this. However, these challenges should not stop any of us from learning and growing. In fact, we should take that as a challenge to contribute to the cause so that we make this world better for future female professionals. At my previous organization, I was the I&D sponsor for the entire department to foster the culture where we are fully Inclusive and respect diversity. Currently,  I am leading few DE&I efforts for a variety of teams at Amex, where our objective is to create safe spaces for our colleagues to make stronger connections, voice their opinion and feel heard. 

Do you see enough female leadership roles in corporates? In your opinion, what should change? 

There are a lot of industries and areas where women still find it difficult to become a part of the mainstream workforce, let alone leadership positions. However, I am glad to see that we have started moving in the right direction at renowned organizations like Amex, Accenture, Microsoft, Unilever, Google, and many more. They have realized the benefits of having diverse workforce at all levels. There is strong awareness about not having enough women in leadership positions. While these organizations offer more women-focused career growth programs to create opportunity, there are many other organizations which still have a long way to go.  

Discrimination by AI is a genuine concern while ensuring data integrity - does this exist? If so, how can it be addressed?    

Machines learn what data teaches them; at times we don’t have enough data for underrepresented groups so unmonitored AI can possibly be biased or discriminatory. Traditionally there weren’t many girls taking up STEM courses, so the historical data would underrepresent them and hence would always predict that girls have lower likelihood to take up or excel at STEM courses. Through right monitoring and using balanced data, these biases can be avoided. Putting human intelligence in training AI is extremely important. It creates ML models which are responsible, fair and well monitored. We shouldn’t let human bias form a base for our AI driven processes, our models should be totally interpretable. Modeling regulatory bodies especially in financial services and health industries are enforcing strong responsible AI processes. For example, there are regular audits to measure transparencies. Non-compliance is not an option anymore; organizations are themselves becoming conscious about being transparent in their AI practices. Gone are the days when ML used to be a black box, we now have ways to break this black box theory.  

What do you want to say to women who want to build a career in AI and other tech-related fields? 

The world is changing very fast, there are unlimited opportunities and possibilities. Keep learning and sharing. Find a purpose for yourself. Remember the only one person who can stop you from achieving great things is yourself. AI or tech fields have nothing to do with one’s gender, its only about what skills you bring to the table. Don’t let anyone decide what career you choose based on any gender stereotype. If you enjoyed studying STEM courses, AI can be a rewarding career choice for you.