Data is “the new oil” or “the new gold”. In the context of AI systems, we often treat Data more like “the new bacon”: Bigger data is better data, and we overfeed AI systems with data as a cheap, infinitely available resource.
We want to fight data’s bacon-like image by promoting the concept of data minimalism for AI as a strategy to enhance both, quality and sustainability of AI systems. In order to survive as data minimalists, we compute the (monetary) value of single data points, and then try to just keep the valuable ones.
Implementing this concept is as challenging and as interesting as it sounds. As a corporate-scale example, we show how much data actually is wasted in an e-commerce recommender system, and how we also found toxic data while applying our data-minimalization strategies.
Topic was presented at a joint event of Munich Datageeks and Women in Big Data Munich
You can watch the recording of the presentation in our YouTube channel:
You can download the slides from SlideShare:
About Michaela Regneri
Michaela Regneri works as a Senior Expert for Artificial Intelligence & Cognitive Computing at OTTO (Hamburg). She is fascinated by AI, especially by its visual, linguistic and cognitive implications for human-computer interaction.
After her PhD in Computational Linguistics, she joined Der SPIEGEL as a R&D engineer, working on search and text mining for the newsroom. In 2016, she started to work at OTTO as a product manager for Business Intelligence Analytics, developing applications with and around data science.
In her current role, she continues to drive & challenge different areas of AI for e-commerce, with a particular interest in AI innovation processes and corporate digital responsibility.