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 ...

How social media algorithms warp our perceptions A key question is what can be done to make algorithms foster accurate human social learning rather than exploit social learning biases.

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 ...

It doesn’t take much to make machine-learning algorithms go awry The rise of large-language models could make the problem worse ...

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 ...

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