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Generative AI: Beyond technicalities – an ethical perspective

south hall 2b
30 minutes


Machines have become smarter than ever before. Recently, we have started using computers for solving problems beyond computations, and it might not be wrong to call them electronic creators. The future laptop might have a prompt based word application, replacing the current Word, where one has to type their thoughts and formulate an entire document from scratch. Similarly, we might see a prompt based Paint application, instead of the typical Paint program, that generates the paintings for us. In my opinion, AI-based applications are not in fiction anymore, and we may soon be using them on our computers. However, there is a possibilty that the Generative AI can be potentially harmful for society. We need to explore the ethical concerns, and how the AI can impact our society. In this talk, we will try to understand how Generative AI is becoming a part of our future and how we can use it in a responsible and ethical manner.

TalkPyData: Ethics in AI


In the current rat race of building AI, the hype is being created to show that AI can take over the world and it can perform better in some aspects than humans. People are scared that they will not have their jobs anymore as they might get automated by GPT. There's also a belief that AI might develop sentience after ingesting so much data. This talk aims at addressing such issues. As a Researcher, I want to discuss the ground truth and share what's possible and what's not. Ultimately, the talk will leave the audience with an understanding of the architectures of AI and why we should adopt an ethical approach in developing and deploying these models.

The speaker

Bhawna Singh

Bhawna Singh

Bhawna Singh is a Data Scientist at CeADAR (UCD). She holds a Bachelors and a Masters Degree in Computer Science. During her masters, she pursued research to identify gender bias in Energy Policy data across the EU. Previously, she worked as a Data Scientist at Brightflag in Ireland and as a Machine Learning Engineer at AISmartz in India. Bhawna has industry experience in E-commerce and LegalOPs. Throughout her career, Bhawna has built models over massive data sets of information and has developed smart systems that solve problems like customer churn, propensity prediction, sales forecasting, recommendation engine, customer segmentation, pdf validation, etc. She believes in making AI systems that are feasible and available to everyone, irrespective of race, gender, social status, or language.

Areas of Interest: Machine Learning, Natural Language Processing(NLP), Predictive Analytics, AI ethics, Fair AI, Explainable AI

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