While some think that AI will take away jobs,AI can actually help everyone do their job better and more effectively. It is enabling today’s organizations to be proactive and not reactive, helping them improve their business processes by using historical data and combining that with current data to make predictions about the future.
As part of our series about the women leading the Artificial Intelligence industry, I had the pleasure of interviewing Richa Yadav of Blue Yonder.
Richa is a data scientist at Blue Yonder, helping organizations leverage artificial intelligence and machine learning to gather insights and make smarter business decisions. Outside of Blue Yonder, Richa coaches female students at her alma mater who are just starting their STEM journey. She reviews their resumes, helps them prepare interview questions and boosts their morale to secure their first job in the 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?
After I graduated with my MBA, I entered the corporate world and began working in the financial sector, analyzing the viability of financial projects. While I didn’t use any formal analytical tools or technology in that role, it exposed me to working with data and numbers. I knew then that I wanted to work with data on a deeper level.
I decided to take the next step and seek formal knowledge to hone my skills. I enrolled for my Master of Science at ASU to learn analytics and took courses to learn about machine learning (ML), artificial intelligence (AI), and data science, as well as the tools used in each discipline. Each day, I practiced my skills on various Kaggle data sets. Kaggle is an online community of data scientists and machine learning practitioners. It is a great platform that allows users who are new in the data science field to build models on public datasets (COVID-19 data, public tweet data, etc.) in a web-based, data science environment.
In 2016, I joined Blue Yonder, leader in digital supply chain and omni-channel commerce fulfillment, to assist with building the enterprise data warehouse (EDW) for our internal use. I worked with a team to build ETL (extract, transform, and load) data processes, write standard procedures to store clean data in the form of tables in the EDW, and then make those tables available to our internal business users for analysis. While working on data cleaning and storage projects, I started identifying the need for using AI internally within the organization. We were making the data available to our internal business teams to do descriptive and diagnostic analytics, but at the time, lacked the ability to identify patterns from the historical data and make predictions about the future. I then identified potential projects across Associate Success (our version of Human Resources) and Sales and built a proof of concept. Fast forward to today, I am leading this effort at Blue Yonder to transform internal operations in my company using AI and ML.
What lessons can others learn from your story?
You do not have to be a science student or an engineer to be in this field. You just need to be a passionate learner. I have gotten to where I am today by being an avid reader and risk-taker, in addition to having a love for working with data.
Can you tell our readers about the most interesting projects you are working on now?
I am currently working on a project to improve Blue Yonder’s customers’ experiences and improve the likelihood of contract renewal. We are leveraging data across customer touchpoints — from their first interaction with Blue Yonder, to the time they officially become our customers. We want to learn from our customer’s journey to provide better service, and in turn help them better service their customers.
We are also working on building a recommender system for our support analyst team that provides them with guidance on how to respond to a customer escalation or reported issue. The data is received from our customer case management system that tracks sentiments about working with Blue Yonder.
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’m particularly grateful for my mentor in my previous job. In addition to encouraging and supporting me in my initiatives, he taught me the importance of goal setting, specifically: documenting your goals, breaking down each goal by time period, making your goals public, and holding yourself accountable for each goal set.
What are the 5 things that most excite you about the AI industry? Why?
- While some think that AI will take away jobs,AI can actually help everyone do their job better and more effectively. It is enabling today’s organizations to be proactive and not reactive, helping them improve their business processes by using historical data and combining that with current data to make predictions about the future.
- AI can help you accomplish more, but in a shorter time span. It can automate some of your daily projects and give you more time back to explore new projects.
- AI can help companies provide better service to their customers by getting a better understanding of how they feel about the organization, products, and people. This can be done by using Natural Language Processing (NLP) technique, which extracts opinions/sentiment from text. This includes customer reviews, social media, technical support tickets opened by our customers, etc.
- AI can revolutionize sports. Statistics has played a central role in the game for a long time. Now, AI is being used to provide real-time feedback and personalized athletic training programs for players. For example, the NBA’s Sacramento Kings purchased a Connexion kiosk that uses AI and sensor technology to analyze a player’s health data to keep the team informed of injuries and other setbacks. AI is going to increase the competitiveness in sports by a big margin.
- AI is proving to be a game changer in healthcare. One of the major trends in AI is using deep learning in medical diagnosis to detect breast cancer. Per studies published by the Journal of the National Cancer Institute and Healthcare IT news, AI alone showed improved accuracy in breast cancer detection comparable to an average breast radiologist.
What are the 5 things that concern you about the AI industry? Why?
AI doesn’t concern me, but there are certain areas of AI that could potentially hinder widespread adoption and use:
- Misuse of personal data and data privacy: AI projects require training data to build the model, and transactional data when the model is put to work. While live data is clearly a valuable corporate asset, it can be easy to overlook pools of training data that also contains sensitive information. I know firsthand that data scientists working on AI projects can become very data hungry. But, focusing on business outcomes can help limit the data that is made available to the data science teams.
- Lack of guidance: we are taking steps in the right direction with GDPR in Europe and CCPA in California; however, there needs to be similar mandates in countries worldwide.
- Breaking the data silos: AI projects, and their ability to transform business operations, are highly dependent on the quality and quantity of data. Therefore, data silos, or keeping data separate from larger data sets, are detrimental to the future of successful implementation and widespread organizational use.
- Data quality: We have heard the term ‘garbage in, garbage out.’ The output from any AI model is highly dependent on good, quality data. The main reasons for inconsistent data or poor data quality are: 1) human error while entering data into the system, 2) migrating data to a new system, and 3) instructions on how data should be entered is open to interpretation and can causes mixed entries by multiple users.
- Lack of Trust: Many people do not trust the power of AI. They cannot comprehend how a specific set of inputs can devise a solution for different problems. We need to emphasize the positive potential of AI and bring awareness to the fact that AI is integrated within our everyday lives such as smartphones, smart TV’s, banking, streaming services like Netflix, cars, etc.
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?
AI is smart, but it needs humans to learn. A New York Times article from August 2019 highlights how much AI is indebted to humans because many people are needed to help an AI system learn so that it can eventually act on its own. Therefore, humans are the consciousness of AI — they give it the power of creative and spontaneous thinking and innovating. At the same time, we need to be conscious about the way humans continue to use AI. It must be leveraged in a productive way that helps us, not harms us.
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?
Questions or concerns surrounding AI are generally informed by what we see in TV shows and movies, which often portray the power of AI in a scary or menacing light.
In my opinion, it is the fear of the unknown that usually frightens us about new innovations. As data scientists, we need to do a better job of educating people about AI by creating content in a very simple, easy-to-learn language that explains the benefits and possibilities. We have come a long way in creating awareness about AI, but there is still a lot more educating we need to do.
As AI becomes more mainstream and integrated into more job categories and industries, we also must encourage people to advance their skills and learn how to work with the technology. It will not take every job away, but the nature of most jobs will change and require new skills.
How have you used your success to bring goodness to the world? Can you share a story?
While volunteering at a local food bank, I realized that we could offer assistance to these groups (and other similar organizations) by contributing insights from our AI technology. At Blue Yonder’s annual innovation event for its associates, I pitched this as a project idea and won first place. I am now working with a team to operationalize the project. We are partnering with a few food banks around the U.S. and Mexico to develop an AI-enabled software/tool that helps them to operate more efficiently.
Currently, we are gathering data across food banks, as well as information on their most pressing challenges. The goal is that, with enough data, the AI will identify trends on the organization’s operations to help them reduce food waste improve resource allocation and save time.
As you know, there are not that many women in your industry. Can you share 3 things that you would advise to other women in the AI space to thrive?
We all are “Wonder Women,” so do not underestimate yourself. Per studies, men tend to overestimate themselves, and women tend to underestimate themselves. As a result, this tends to impact a women’s performance negatively. As women, we need to have confidence in our abilities and recognize and promote the skills we bring to the table.
Get out of your comfort zone. Start self-nominating yourself for new projects and initiatives. Do not be complacent and laid back in your job. With change, comes growth.
Help other women. I like to mentor other women without letting them know. As they become more comfortable, they will reach out to me and seek help/advice because of the relationship we’ve established. I encourage these women to in-turn spread the knowledge and help other women.
Can you advise what is needed to engage more women into the AI industry?
Every organization needs to make a paradigm shift and a conscious effort to hire a gender diverse team. It is not a pipeline problem (i.e., less female applicants for the job), but our culture is more inclined to hire a male coder, a male engineer, a male applicant — myself included. I am making a more conscious effort to include more women in the efforts I lead. I am proud that Blue Yonder is also making a conscious effort around this effort as well.
We need to give women a chance in the AI industry for them to thrive. This includes building women support groups internally and externally at your organization. One-on-one meetings and direct counseling are especially helpful for women at very early stages in their career. We need to elevate them, give them an opportunity to learn, and acknowledge their progress.
What is your favorite “Life Lesson Quote”? Can you share a story of how that had relevance to your own life?
My favorite quote that changed my life is from Bob Marley: “You never know how strong you are, until being strong is the only choice you have.” This was shared by my sister when I was very content in my professional life and happy in my comfort zone. This quote helped initiate a turning point in my life and fight the status quo. It encouraged me to enroll in my second masters and do something I was very passionate about.
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. 🙂
My movement will be to make a conscious effort to give back to society. I would encourage everyone to use their skills, knowledge, and talent to give back in some way. I am really inspired by Bill and Melinda Gates. We all can do our tiny bit in giving back to the community to spread goodness and make this world a better place.
How can our readers follow you on social media?
I am on LinkedIn: https://www.linkedin.com/in/richay/