Can we ever really trust algorithms to make decisions for us? Previous research has proved these programs can reinforce society’s harmful biases, but the problems go beyond that. A new study ...

There are three key reasons why predictive algorithms can make big mistakes. 1. The Wrong Data An algorithm can only make accurate predictions if you train it using the right type of data.

For example, users can feed their locally stored data into a large language model (LLM), such as Llama. The so-called SIFT algorithm (Selecting Informative data for Fine-Tuning), developed by ETH ...

But with the recent rise of generative AI tools like Chat GPT, which run on large language models (LLM), and the image-making system DALL-E 2, companies have taken to training their algorithms on ...

Making algorithms completely transparent could create other problems, however. In 2006, for example, Netflix offered $1 million to the developers who submitted the best possible recommendation ...

For example, the kidney allocation system is an algorithm-based protocol used to prioritize patients for kidney transplants on the basis of the amount of time they have been on the national ...

Adam Aleksic talks about his new book 'Algospeak,' which details how algorithms are changing our vocabulary; plus, we check in with Hennessy + Ingalls bookstore.