We all know that tech is largely dominated by men, and sub-domains of tech like data science, AI and analytics follow the same trend. Though in recent years, we have seen more and more young women showing interest in making a career in these new-age technologies, the number is still quite low.
To encourage more women to pursue these so-called “non-traditional job roles”, we bring out stories of women breaking the stereotypes and making successful careers in tech.
Today, we look at the journey of Arunima Sarkar. What makes her journey unique is that she has seen a mix of both worlds—spending around two decades in corporate with 13 years in Accenture holding positions like Global Applied Intelligence Research Lead, Growth and Strategy, to policymaking and technology governance currently at World Economic Forum as the Lead Artificial Intelligence, Global Assignments, Centre for Fourth Industrial Revolution.
From technology research to leadership in Accenture
Sarkar adds, “I started my career from a technology research perspective. I was interested in understanding the impact of technology on the economy, society and the different opportunities it creates for the different industries and regions. I started off with roles in such research consulting firms focusing on technology like Gartner. At that time, the Indian IT outsourcing industry was just coming up, and I was deeply involved in developing India’s first BPO study that was done back in those days with Gartner. I was closely working in the IT, BPO and telecom market.”
She continued with her interest in broad IT services and then joined Accenture back in 2006. She has spent over a decade there where she built the analytics, AI and data research team within the company and was leading that globally for several years.
Strong advocate of responsible AI
Sarkar says, “Around six years back, the company also started looking at responsible AI. It was an important aspect, and Accenture wanted to make it an integral part of everything they did in artificial intelligence at the organisation. At that time, I was representing Accenture at PAI (Partnership on AI), a private-public partnership based in the US, working specifically in the area of responsible AI.
Sarkar also started looking at the societal impact of such technologies and their policy implications. She spent time working on areas not only around applied AI but also responsible AI. She wanted to answer this critical question—how can this technology be built, designed and deployed in a responsible and ethical manner? Then she moved out of the private sector and joined the World Economic Forum.
Impact of tech on society
Sarkar leads the codesign of governance protocol and technology policy frameworks for artificial intelligence as well as quantum computing governance frameworks for developing principles for responsible innovation and use of the technology.
She also leads several sectoral projects that have multiple stakeholders and are global in nature. WEF brings in experts from the public sector, private sector, academia, research and civil society together to understand what are the pressing societal challenges, what are the policy and technology governance gaps and where technology can be applied for achieving larger societal benefits.
Developing India’s responsible AI strategy with NITI Aayog
Sarkar has had a long and illustrious career with several milestones. But when asked to identify her biggest achievements if she could look back, she has two very special projects in mind.
Sarkar led the roadmap from WEF’s side along with NITI Aayog to develop India’s Responsible AI strategy. It puts together a national-level roadmap on how AI can be designed, developed and deployed responsibly in the country. The roadmap helps understand and create awareness about the ethical challenges and potential risks of this technology, what kind of considerations need to be kept in mind by different stakeholders and how to implement such guidelines in the country.
She adds, “The potential of the technology is known and talked about and quantified, but the responsible use of this technology is critical. It is very important to build that awareness in the country. India is representative of a huge part of the work population, and if such technologies are implemented properly, it can create best practices for the entire world to follow.”
First set of quantum computing guidelines
Another big achievement for Sarkar has been leading the governance track of the quantum computing initiative at WEF. Last year was a year of intense hard work for Sarkar and her team to bring out the first set of quantum computing governance principles for the responsible development of this technology.
Sarkar states, “We see investments coming from the private sector, venture capital funding in quantum technology and national level programs being rolled out. We are at the stage when quantum computing in the lab is in the PoC stage, just before commercialisation starts happening in this tech. It is the right time for us to look at the criteria that are needed to develop this technology.”
Good mix of business and tech skills
As someone who has hired many AI professionals and worked with data scientists in various leadership roles, Sarkar feels that in order to build AI that is impactful and beneficial for all, it is very important for a data scientist to understand the business needs and the use case the AI application is targeting. A data scientist should have a good mix of tech and business skills and a problem-solving mindset.
More success stories need to be out in the public
Sarkar feels that this trend of lesser women in the AI and analytics space is a continuation of the trend for the tech space. A stereotype exists, and there are not enough success stories that are talked about enough.
She adds, “We need to build more awareness right from the educational level and within the organisation as well. Sharing success stories and mentoring women to build up their career in this space can be greatly helpful in bridging the gender gap.”
We need social scientists, lawyers, ethicists to work with data scientists to build responsible AI applications
Sarkar gives an interesting perspective on the various aspects of AI that one can build a career in.
She says, “AI needs multidisciplinary experts-data scientists, social scientists, lawyers, ethicists to build responsible AI applications that can be deployed. Most large organisations are recognising the needs, and many startups are understanding this too. There are multiple ways in which one can approach this field with allied career paths around AI.
Sarkar says that it is time to embed data science and AI curriculum in schools and colleges. Children should be made aware that such a career path is available to them. It does not have to be taught only to students pursuing Science but Arts as well. AI needs a combination of both.
Man and machine will learn how to augment each other
Sarkar concludes that in the near future, AI is going to become more and more pervasive in literally every aspect of our lives. We will see it impacting every industry, and there will be new ways in which man and machine will learn how to augment each other. The greater spread of the use of this tech will help in solving many problems in varying capacities—from critical problems like climate change to day-to-day issues.
