Can Social Media Posts Reveal Hidden Depression Risk?
New research shows that artificial intelligence can assess a user’s risk of depression by analyzing their language on social media platforms.
Science
Decoding the Forecast: A Window into AI Weather Models
![The study demonstrates that cosine similarity of latent feature vectors-calculated both with a limited set of the most activated channels and the full channel set-effectively captures forecast relationships, exhibiting distinct patterns when analyzed across regions-specifically, one mirroring the analysis region of Figure 1 and another centered at [latex]50^{\circ}N, 48^{\circ}W[/latex] with a [latex]5.81^{\circ}[/latex] radius-thereby highlighting the spatial dependence of forecast correlations.](https://arxiv.org/html/2604.20467v1/x3.png)
Researchers have developed a new visualization tool to explore the inner workings of artificial intelligence systems used for weather prediction.
The AI Reshaping Wall Street: Beyond Automation to Augmented Finance
New research suggests the rise of intelligent agents in finance isn’t simply about replacing workers, but fundamentally changing how financial work is organized and performed.
The Wisdom of the Crowd, Bottlenecked by AI
New research explores the limits of artificial intelligence in harnessing collective knowledge, even in structured environments like prediction markets.
AI Detects Deception: Machines Prove Better at Spotting Financial Fraud Than Humans
New research reveals that artificial intelligence consistently outperforms people in identifying fraudulent claims and resists being swayed by biased investor pressure.
When Institutions Fail: Modeling the Path to Economic Collapse
New research uses computational modeling to reveal how flawed governance structures can drive economic systems toward predictable breakdowns, while decentralized designs foster lasting growth.
Tracking AI’s Blind Spots: A New Approach to Incident Analysis
A novel framework adapts public health surveillance methods to move beyond simple incident counts and understand the underlying dynamics of AI-related risks.
Contagion in Global Markets: How Network Structure Fuels Systemic Risk
![The simulation, parameterized with [latex]\theta = 0.3[/latex], demonstrates that a shock to a specific Brazilian asset ([latex]VIVT3.SA[/latex]) triggers a localized cascade of defaults within the Brazilian financial subnetwork, while developed-market assets remain insulated from contagion, underscoring the inherent vulnerabilities of emerging economies.](https://arxiv.org/html/2604.19796v1/figure_7.png)
New research reveals that the way global equity markets are connected, combined with the potential for extreme losses, is a primary driver of systemic risk, rather than a broad, uniform threat.
When Algorithms Codify Inequality
New research reveals how machine learning systems used in higher education can inadvertently reinforce existing inequities throughout their entire lifecycle.
Beyond the Hype: Why Graph Networks Struggle with Real-World Fraud
A new analysis of Bitcoin transaction data reveals that complex graph neural networks don’t always outperform simpler models in detecting fraudulent activity.