Image by Nel Ranoko, from Unsplash

AI Weather Forecasts May Help Farmers Combat Climate Risks, But Bring New Concerns

• Written by Kiara Fabbri Former Tech News Writer
• Fact-Checked by Sarah Frazier Former Content Manager

AI is changing agriculture by helping farmers predict weather, manage crops, and streamline operations, however, high costs, social inequalities, and environmental risks mean it also comes with serious challenges

In a rush? Here are the quick facts:

• Traditional weather models are expensive and often unavailable to low-income countries.
• AI models provide accurate, localized forecasts at much lower computational costs.
• AI forecasts can guide planting decisions, fertilizer use, and pest management.

Every planting decision made by farmers involves multiple risks, which are becoming more severe as a result of climate change, as noted in a new analysis by The Conversation (TC).

Weather stands as a major risk factor, harming both agricultural production and farmers’ financial stability. TC gives the examples of how a delayed monsoon season compels South Asian rice farmers to either start over with new plantings or change their agricultural production, resulting in lost time and income.

This means that accessing reliable and timely weather forecasts can help farmers optimize their planting schedules and fertilizer usage. However, TC argues that many low- and middle-income nations face significant challenges accessing reliable forecasts since the technology tends to be very expensive.

A new wave of AI-powered weather forecasting models has the potential to change this divide. AI models can deliver accurate, localized predictions at a fraction of the computational cost of conventional physics-based models.

AI allows national meteorological agencies in developing countries to provide farmers with timely, localized information about changing rainfall patterns.

Unlike traditional models, which require expensive supercomputers and focus on temperate regions, AI models can run on laptops and provide forecasts globally.

TC reports that new systems such as Pangu-Weather and GraphCast demonstrate equivalent or superior performance to leading physics-based models for temperature forecasts. Once trained, AI models produce results within minutes rather than hours, enabling farmers to make swift, informed decisions.

The challenge is tailoring forecasts to real-world needs. “To unlock its full potential, AI forecasting must be connected to the people whose decisions it’s meant to guide,” TC notes.

Organizations like AIM for Scale, together with international entities, train users and create agricultural decision-focused forecasts for governments. In India, accurate monsoon forecasts helped farmers select optimal planting strategies, improving investments and reducing risk.

AI weather forecasting is now at a critical stage, and with proper support, low- and middle-income nations can provide farmers with essential timely information.

AI technology also drives significant changes beyond weather prediction. Tavant implements AI solutions that enhance farm management , supply chains, and sales operations.

Its AI Agent accelerators, developed with Microsoft Copilot Studio, include ‘Sales Assistant’, which lets farmers purchase seeds, fertilizers, and other supplies via email or messaging, and ‘Virtual Agronomist’, which provides AI-based real-time crop guidance.

Emerging tools such as MIT’s robotic pollinators and the University of Sydney’s SwagBot complement these solutions, illustrating a sustainable, high-tech agricultural future.

Recent research identifies three major AI-related issues: predictive dissonance between models, techno-indecisiveness causing decision delays, and readiness deficit from insufficient preparedness for AI disruptions. Overreliance can lead to poor management, including excessive fertilizer use, which harms soil health and long-term productivity.

Another scientific review reported that high costs prevent small farms from accessing AI, automation threatens jobs, and corporate control of data can create inequities. Additionally, the researchers point out that socially, AI can deepen digital divides, perpetuate biases, and erode traditional farming practices.

Furthermore, the research points out that ethical concerns include environmental damage and animal welfare, while complex algorithms make transparency difficult.

Addressing these risks requires equitable access, digital training, bias mitigation, data governance, and ethical guidelines for sustainable AI adoption.

Photo by Mohamed M on Unsplash

Report Reveals Open-Source Malware Captures Images Of Victims Watching Porn

• Written by Andrea Miliani Former Tech News Expert
• Fact-Checked by Sarah Frazier Former Content Manager

A recent report published by researchers at Proofpoint revealed that malicious actors have been using open-source malware labeled for “educational purposes” across multiple platforms to conduct cyberattacks. The experts discovered that this year, attackers employed automated infostealers in various campaigns, including taking pictures when users watch pornography for sextortion purposes.

In a rush? Here are the quick facts:

• Report reveals malicious actors have been using open-source malware available for “educational purposes” for cyberattacks.
• Stealerium and similar tools have been recently used for malicious campaigns.
• Some malware variants activate webcams and take screenshots when users view pornography for sextortion purposes.

According to the report published by Proofpoint on Wednesday, the open-source malware studied—Stealerium and similar variants—have been publicly available on platforms such as GitHub “for educational purposes only” for a long time. However, the researchers noticed recent malicious activity related to the infostealer.

“While open-source malware can be helpful for detection engineers and threat hunters to understand the patterns of behavior for which they can develop threat detection signatures, it also provides a different kind of education to malicious actors,” explained the researchers in the analysis. “These actors may adopt, modify, and possibly improve the open-source code, resulting in a proliferation of variants of the malware that are not so easy to detect or defend against.”

The researchers discovered multiple attacks targeting hundreds of organizations across the globe attributed to the threat actors TA2715 and TA2536, and linked to Stealerium. The campaigns used phishing emails with malicious attachments, impersonated organizations across various sectors, demanded payments, and applied social engineering tactics designed to instill fear and urgency.

In one case, malware installed on a victim’s device stole a wide range of data and included a pornographic-content detection feature. When adult content was recognized in a browser URL, it triggered screenshots and webcam captures.

“It’s able to detect adult content-related open browser tabs and takes a desktop screenshot as well as a webcam image capture,” wrote the researchers. “This is likely later used for ‘sextortion.’ While this feature is not novel among cybercrime malware, it is not often observed.”

Proofpoint warned of the risks posed by open-source malware and the likelihood of a new wave of cyberattacks, urging organizations to strengthen their defenses.

In recent weeks, multiple sextortion campaigns have been reported. In May, multiple outlets reported that the “Hello Pervert” campaign had been targeting many email users, and experts have also raised concerns about the use of AI for sextortion schemes on dating apps .