Scale By the Bay Scale By the Bay

Friday, October 29, 2021

- PDT
Continous integration of ML products and UX design
Adarsa Sivaprasad
Adarsa Sivaprasad
Independent, Senior Data Scientist

As ML and deep learning algorithms are increasingly coming out from research and being integrated into products, the conventional product design is also learning to adapt to it. Data-centric product design in the last decade has concentrated on data warehousing, scalability of pipelines for big data, and interpretation through KPIs and dashboards. Integrating ML products and involving artificial intelligent learning systems in the product additionally demands, emphasis on data quality, data exploration, and model explainability. Concerns of data privacy, data democratization, and bias within business and users too need to be possibly built into the design. In this context, the talk would explore these aspects by considering two common scenarios. A typical telemetry summarizer (a core data product) and a recommendation engine(a user-facing product with reinforcement learning). The talk aims at exploring the following aspects: - How might we use UX and design to make ML models more explainable and interpretable - How to use UX for ensuring data quality and identifying bias in data collection pipeline - How might we use data science techniques to inform and drive UX design decisions