Embracing Change
Abeba discusses the challenges of formalizing cognition and language within machine learning, emphasizing the need for tools and theories to remain adaptable and open to revision. The conversation highlights the tension between reductive labels in predictions and the importance of understanding the dynamic nature of context, advocating for a focus on continual learning and adaptation rather than finality.In this clip
From this podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Algorithmic Injustices and Relational Ethics with Abeba Birhane - #348
Related Questions
What are some insights from cognitive science on the process of thinking in sentences?
What are some insights from cognitive science on the process of thinking in sentences as discussed in the episode 96 - Question Answering as an Annotation Format, with Luke Zettlemoyer and the clip Machine Understanding Challenge?