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How women are navigating challenges and taking centre stage in the AI-powered technology landscape
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How women are navigating challenges and taking centre stage in the AI-powered technology landscape

Harsha Solanki • March 8, 2024, 16:13:01 IST
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By working together, we can move towards the common goal of shaping a progressive future of AI that has diverse perspectives, equal representation and an inclusive landscape

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How women are navigating challenges and taking centre stage in the AI-powered technology landscape
Women can contribute a lot in the AI-driven world. Image courtesy stockholm.liberalerna.se

Amid rapid digitization, Artificial Intelligence (AI) is no longer a buzzword but has emerged as a priority for businesses across industries. Whether it is voice assistants like Siri and Alexa fulfilling our wishes at a simple voice command, the ETA of cabs we book, or Natural language processing (NLP) and Machine learning (ML) algorithms-enabled chatbots resolving our queries instantly, AI is revolutionizing different aspects of our lives. However, to ensure its impactful development, equal and inclusive participation is essential. And women are rising to the occasion to explore prospective opportunities and break barriers with a vision to shape the future of AI.

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Pivotal role of women in AI-powered technology fields

In an industry historically dominated by men, women have defied bias to occupy a prominent position in the STEM (Science, Technology, Engineering, Mathematics) sector. They have made significant strides in facilitating AI and ML advancements. In fact, women are credited with being one of the most prominent pioneers in the field of AI. Dating back to the mid-19th century, Ada Lovelace, known as the world’s first computer programmer, worked collaboratively with Charles Baggage on the design of the Analytical Engine. Even in the mid-20th century, Katherine Johnson was instrumental in the success of the first manned space flights and went on to become a role model for women in the STEM field.

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Closer home, several women are leading the AI revolution. India has the highest skill penetration rates, and women are contributing by being at the forefront of AI research and development. Take Aakanksha Chowdhery, for instance. She is a staff research scientist at Google DeepMind whose extensive research and contributions extend to fields like signal processing, ML, edge computing, etc. Additionally, strong-headed women like Tessy Thomas at the Defence Research and Development Organisation (DRDO), Ishu Jain leading central analytics at Swiggy and Divya Mittal, Director of data science at American Express, among others, are shining examples of female excellence in the field.

Addressing the gender gap in the field of AI

Despite women leading prominent initiatives and occupying board positions, they often face discrimination at various levels and are being underrepresented in the STEM field. As of last year, women comprised 28 per cent of India’s STEM workforce. There are several reasons for this gap, like unconscious bias, lack of mentors for guidance, and fewer opportunities for women to develop the skills they need. In fact, gender gap is a major roadblock, as highlighted at a UN Women’s HeForShe Summit last year. Moreover, stereotypes  about gender suitability in STEM end up pushing girls to lookout for other lucrative options.

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Empowering women India’s AI landscape

India has the third-largest AI talent pool across the globe, showcasing its promising position in the landscape. The country is also empowering women with AI skills, showing India’s commitment to battling issues like gender diversity and inclusivity in the sector. For instance, the success of Chandrayaan 3 was attributed to the strong team driven by females, who worked tirelessly and actively contributed to the successful execution of the mission. Even the ISRO chairman, S Somanath expressed the need for increased women’s representation in space missions to inspire young women to pursue the tech industry.

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To address the challenges faced by women, solutions must focus on early exposure to the field with an engaging and immersive approach. Young girls should also have access to mentors and allyship. Organizations must include targeted reskilling and upskilling programs to enhance women’s participation and retention.

Notably, UNESCO’s Social and Human Sciences Sector launched the Women 4 Ethical AI Platform at the 67th Session of the Commission on the Status of Women (CSW67) last year. One of the key objectives of this initiative includes increased women’s participation in STEM and ICT (Internet and communication technology) fields. The Indian government, too, has outlined its vision for ‘Make AI in India’ and ‘Make AI work in India’. They will set up centres of excellence in top educational institutions to boost female participation. Various schemes like VigyanJyoti and Overseas Fellowship ensure women’s participation in the tech field. Currently, the representation of women in STEM stands at 43 per cent, one of the highest in the world.

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Various homegrown companies in the AI-powered tech space are also making concerted efforts to drive India’s economic growth by providing opportunities to women to navigate organizational growth with their expertise and skillsets.

To conclude

Achieving gender parity requires a holistic approach and collective efforts at the grassroots level. Organisations play a crucial role in creating a vibrant and diverse environment and giving opportunities to talented individuals, irrespective of their gender. Companies can empower individuals through mentorship and skill development programs to help them excel in their respective fields. By working together, we can move towards the common goal of shaping a progressive future of AI that has diverse perspectives, equal representation and an inclusive landscape.

The author is VP GM Asia, Infobip. Views expressed in the above piece are personal and solely that of the author. They do not necessarily reflect Firstpost_’s views_.

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Ada Lovelace artificial intelligence gender gap International Women's Day Machine Learning Natural Language Processing
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