ML Conference
The Conference for Machine Learning Innovation

Building Ethical AI: A Guide for Developers on Avoiding Bias and Designing Responsible Systems

The intersection of philosophy and artificial intelligence may seem obvious, but there are many different levels to be considered. We talked to Katleen Gabriels, Assistant Professor in Ethics and Philosophy of Technology and author of the 2020 book “Conscientious AI: Machines Learning Morals”. We asked her about the intersection of philosophy and AI, about the ethics of ChatGPT, AGI and the singularity.

OpenAI Embeddings

Embedding vectors (or embeddings) play a central role in the challenges of processing and interpretation of unstructured data such as text, images, or audio files. Embeddings take unstructured data and convert it to structured, no matter how complex, so they can be easily processed by software. OpenAI offers such embeddings, and this article will go over how they work and how they can be used.

Address Matching with NLP in Python

Discover the power of address matching in real estate data management with this comprehensive guide. Learn how to leverage natural language processing (NLP) techniques using Python, including open-source libraries like SpaCy and fuzzywuzzy, to parse, clean, and match addresses. From breaking down data silos to geocoding and point-in-polygon searches, this article provides a step-by-step approach to creating a Source-of-Truth Real Estate Dataset. Whether you're in geospatial analysis, real estate data management, logistics, or compliance, accurate address matching is the key to unlocking valuable insights.

AI is a Human Endeavor

As AI advances, calls for regulation are increasing. But viable regulatory policies will require a broad public debate. We spoke with Mhairi Aitken, Ethics Fellow at the British Alan Turing Institute, about the current discussions on risks, AI regulation, and visions of shiny robots with glowing brains.
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