Image by Victoriano Izquierdo, from Unsplash
U.S. Sues Robot Toy Maker Over Illegal Collection of Kids’ Data
- Written by Kiara Fabbri Former Tech News Writer
- Fact-Checked by Sarah Frazier Former Content Manager
The U.S. Department of Justice filed a lawsuit against Apitor Technology, accusing the Chinese toy company of allowing a third party to obtain children’s location data without parental authorization.
In a rush? Here are the quick facts:
- Apitor allowed a Chinese third party to collect children’s location data.
- Children’s geolocation data was collected without parental consent, violating COPPA.
- Apitor sells robot toys for children aged 6-14 with a free Android app.
The complaint, following a referral from the Federal Trade Commission (FTC), says Apitor violated the Children’s Online Privacy Protection Rule (COPPA).
BleepingComputer , who first reported the story, notes that toy robot manufacturer Apitor markets its products to children between 6 and 14 years old, and provides a free Android application for toy control. The application requires children to activate location sharing.
However, the app contains JPush, a third-party software kit from Jiguang (also known as Aurora Mobile), which has collected precise geolocation data of children since at least 2022. The collected data remains open to any possible usage, including promotional activities.
“After Android users have enabled location permissions for the Apitor App, the app begins collecting their precise geolocation data in the background and transmitting it to JPush internet servers,” the complaint reads.
“At no point does Defendant disclose to users that the app allows a third party to collect precise geolocation data, nor does it seek verifiable consent from parents to collect precise geolocation data from their children,” the complaint adds
“Apitor allowed a Chinese third party to collect sensitive data from children using its product, in violation of COPPA,” said Christopher Mufarrige, Director of the FTC’s Bureau of Consumer Protection.
“COPPA is clear: Companies that provide online services to kids must notify parents if they are collecting personal information from their kids and get parents’ consent—even if the data is collected by a third party,” Mufarrige added.
The proposed settlement requires Apitor to verify that all third-party software meets COPPA requirements, to obtain parental consent before data collection, to notify parents about data collection, to delete personal information upon request, and to maintain data only when necessary.
The $500,000 penalty against Apitor remains suspended because of financial challenges, but will become active if the company provides deceptive financial information.
The DOJ submitted the complaint to the U.S. District Court for the Northern District of California, as part of the FTC’s ongoing efforts to safeguard children’s online privacy.
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.
