It’s a Wrap on the Women in Data Science  Conference at Intuit

The event brought together over 80 data science professionals, providing a valuable platform for knowledge sharing and career advancement
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Intuit India recently concluded the Women in Data Science (WiDS) conference held at their Bangalore office on June 20. The event brought together over 80 data science professionals, who left feeling empowered and inspired by the insightful sessions that took place. WiDS featured a variety of speakers, including leading data scientists, entrepreneurs and educators. 

The year marked a significant milestone as WiDS introduced an engaging mentoring session with accomplished women leaders in the data science field, giving the participants an opportunity to gain insights and tips for excelling in the industry from the leaders themselves.

The event consisted of a variety of informative tech talks, keynote sessions, fireside chats, networking sessions, and much more. 

Here is a quick synopsis of the sessions – 

Keynote – Data Efficient Matching

The WiDS Ambassador Note was presented by Sravyasri Garapati from Intuit, followed by an enlightening session on ‘Data Efficient Matching’ by Soma Biswas, an Associate Professor at the Indian Institute of Science (IISc) and a senior member of IEEE. 

Data Efficient Matching involves the effective pairing of data across diverse sources or entities despite having limited data at hand. It tackles the difficulties posed by sparse or incomplete information by leveraging sophisticated methodologies like machine learning, probabilistic modelling, and data fusion. 

The objective is to streamline the matching procedure while minimising data requirements, enabling successful matching even when only a small amount of information is accessible. This approach finds applications in various domains, such as identity resolution, recommendation systems, and data integration, where efficient matching plays a vital role in ensuring precise and dependable outcomes.

Structured Data to Analytical Text Generation

Google researcher Preksha Nema delivered an insightful speech on ‘Structured Data to Analytical Text Generation’. Nema’s research primarily focuses on understanding and generating purposeful ads, particularly in multilingual and low-resource contexts. In 2017, she received the Google PhD India Fellowship. 

Structured data to analytical text generation refers to the conversion of structured data, such as organised databases or spreadsheets, into comprehensible analytical text through natural language processing (NLP). 

This process employs NLP methods to translate numerical information into meaningful narratives or summaries. By extracting significant findings and trends from the structured data, this technique allows for the creation of concise and coherent textual explanations, enhancing comprehension and interpretation of the original data. It proves to be an invaluable resource for data-informed decision-making, generating reports, and effectively communicating intricate information to diverse audiences.

Role of Analytics in Data Governance

Kalapriya Kannan, representing Hewlett Packard Enterprise, discussed the ‘Role of Analytics in Data Governance’. Her expertise lies in machine learning, natural language systems, and their applications. Analytics plays a pivotal role in the realm of data governance by facilitating efficient management and utilisation of data assets. It harnesses the power of insights derived from data to establish robust policies and procedures governing data quality, integrity, and usage patterns. 

Through the application of analytics, organisations can identify irregularities within data, track its origin and evolution, ensure adherence to regulatory requirements, and make well-informed decisions based on reliable and precise information. 

Analytics further aids in the continuous monitoring of data governance processes, measuring performance indicators, and driving ongoing enhancements in data management practices. Ultimately, analytics empowers organisations to optimise the value of their data while upholding its integrity and security.

Fireside conversation – Gender Bias in AI – Whom Do We Blame: Data, Model, Applications or Society?

An interesting fireside chat on ‘Gender Bias in AI – Whom Do We Blame: Data, Model, Applications or Society?’ featured Kalika Bali from Microsoft Research in conversation with Shreya Mukhopadhyay

The topic delved into the attribution of responsibility regarding the presence of gender bias in artificial intelligence. It examined whether the culpability lay with the training data employed, the AI models utilised, the applications that utilise them, or the societal prejudices ingrained in the data. 

This discourse highlighted the intricate interaction among these elements and underscored the importance of shared accountability in acknowledging and rectifying gender bias within AI systems. “I had the privilege of participating in the fireside chat, unsure of how the audience would respond. To my delight, numerous individuals approached me, eager to contribute and learn more about making a social impact. Their genuine curiosity and willingness to take action left me truly thrilled,” said Bali. 

Kalika Bali from Microsoft Research in an engaging conversation with Shreya Mukhopadhyay

Responsible AI in Gaming

Rukma Talwadker from Games24x7 delivered the closing keynote on ‘Responsible AI in Gaming’. “I had an incredible opportunity to present my research on identifying excessive gameplay patterns during an amazing session. The engagement and appreciation from the audience were truly gratifying. Kudos to Intuit for organising a well-executed event with excellent session choices,” said Talwadker.

Responsible AI in gaming involves ethically and thoughtfully incorporating AI technologies into the gaming sector. It encompasses principles like equitable and inclusive portrayal, transparent algorithms, and mitigating adverse effects. Game developers aim to craft AI-infused gaming experiences that celebrate diversity, prevent bias, safeguard user privacy, and prioritise player welfare. Responsible AI in gaming strikes a harmonious equilibrium between innovation and ethical standards, ensuring that AI enriches gameplay while upholding players’ rights and values.

The conference concluded with a highly impactful mentoring session, leaving all participants enriched and empowered.  With engaging discussions and meaningful connections, WiDS served as a catalyst for personal and professional growth for participants, solidifying its place as a remarkable gathering in the field.

Watch out for the next edition of the Women in Data Science Conference, at Intuit where industry pioneers share cutting-edge knowledge, empowering you to thrive in a rapidly evolving landscape.

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Shritama Saha
Shritama is a technology journalist who is keen to learn about AI and analytics play. A graduate in mass communication, she is passionate to explore the influence of data science on fashion, drug development, films, and art.

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