Author

Vrushali Sawant
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Data Scientist, Data Ethics Practice

Vrushali Sawant is a data scientist with SAS's Data Ethics Practice (DEP), steering the practical implementation of fairness and trustworthy principles into the SAS platform. She leads the marketing initiatives from a responsible innovation perspective for the DEP. With a background in technology consulting, data management, and data visualization, she has been helping customers make data driven decisions for a decade.

Artificial Intelligence
Vrushali Sawant 0
3 attributes of human centricity in trustworthy AI development

AI tools should, ideally, prioritize human well-being, agency and equity, steering clear of harmful consequences. Across various industries, AI is instrumental in solving many challenging problems, such as enhancing tumor assessments in cancer treatment or utilizing natural language processing in banking for customer-centric transformation. The application of AI is also

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Data Management | Predictions
Vrushali Sawant 0
3 industries set to benefit from ethical synthetic data generation in 2024

In 2024, we will witness the proliferation of synthetic data across industries. In 2023, companies experimented with foundational models, and this trend will continue. Organizations see it as an emerging force to reshape industries and change lives. However, the ethical implications can't be overlooked. Let’s explore some industries I think

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English
Banking | Health Care | Life Sciences
Analytics | Artificial Intelligence | Data for Good
Vrushali Sawant 1
Inclusivity: A guiding principle for responsible innovation

AI – just like humans – can carry biases. Unchecked bias can perpetuate power imbalances and marginalize vulnerable communities. Recognizing the potential for bias is one of the first steps toward responsible innovation. Doing so allows users to include diverse needs and perspectives in building inclusive and robust products. Through

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Analytics
Vrushali Sawant 0
The ethics of responsible innovation: Why transparency is key

In today's world, data-driven systems make significant decisions across industries. While these systems can bring many benefits, they can also foster distrust by obscuring how decisions are made. Therefore, transparency within data driven systems is critical to responsible innovation. Transparency requires clear, explainable communication. Since transparency helps people understand how

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English