About The Study: This survey study found that artificial intelligence (AI) use was significantly associated with greater depressive symptoms, with magnitude of differences varying by age group. Further work is needed to understand whether these associations are causal and explain heterogeneous effects.

In a new paper, researchers from Columbia Engineering describe a new method for extracting lithium that could dramatically shorten processing time, unlock reserves that existing methods can’t tap, and reduce environmental impact. Their technique uses a temperature-sensitive solvent to extract lithium directly from the brines found in deposits across the world. Unlike the current technologies, this approach can efficiently extract lithium even when the mineral is found in very low concentrations and contaminated with similar materials.

A research team led by Prof. LI Bing from the Institute of Metal Research of the Chinese Academy of Sciences, together with collaborators, has overcome a longstanding bottleneck in refrigeration technology. Their findings, published in Nature on January 22, introduce a novel cooling method based on the "dissolution barocaloric effect," which offers a promising zero-carbon alternative to traditional refrigeration.

Biases in AI’s models and algorithms can actively harm some of its users and promote social injustice. Documented biases have led to different medical treatments due to patients’ demographics and corporate hiring tools that discriminate against female and Black candidates.

New research from Texas McCombs suggests both a previously unexplored source of AI biases and some ways to correct for them: complexity.

“There’s a complex set of issues that the algorithm has to deal with, and it’s infeasible to deal with those issues well,” says Hüseyin Tanriverdi, associate professor of information, risk, and operations management. “Bias could be an artifact of that complexity rather than other explanations that people have offered.”

U.S. forests have stored more carbon in the past two decades than at any time in the last century, an increase attributable to a mix of natural factors and human activity, finds a new study.

Due to their error-prone hardware, quantum computers have not yet found practical use. One promising solution is quantum error correction: special methods are used to find and correct errors in the calculations of quantum computers in order to achieve reliable results. In the snaQCs2025 project, neQxt GmbH, Fraunhofer IAF and Point 8 GmbH are working on the coordinated development of quantum error correction methods and quantum algorithms. The project aims at significantly advancing the practical applicability of quantum computers. The project kick-off took place in Cologne on January 14, 2026. The BMFTR is funding snaQCs with €2.5 million over three years.