Anthropic announced last week that it will update its terms of service and privacy policy to allow the use of chats for training its AI model “Claude.” Users of all subscription levels- Claude Free, Max, Pro, and Code subscribers- will be impacted by this new update. Anthropic’s new Consumer Terms and Privacy Policy will take effect from September 28, 2025.
If you are a Claude user, you can delay accepting the new policy by choosing ‘not now’, however, after September 28, your user account will be opted in by default to share your chat transcript for training the AI model.
The new policy has come after the genAI boom, thanks to the massive data that has prompted various tech companies to rethink their update policies (although quietly) and update their terms of service. With this, these companies can use your data to train their AI models or give it out to other companies to improve their AI bots.
"By participating, you’ll help us improve model safety, making our systems for detecting harmful content more accurate and less likely to flag harmless conversations. You’ll also help future Claude models improve at skills like coding, analysis, and reasoning, ultimately leading to better models for all users," Anthropic said.
Earlier this year, in July, Wetransfer, a famous file-sharing platform, fell into controversy when it changed its terms of service agreement, facing immediate backlash from its users and online community. WeTransfer wanted the files uploaded on its platform could be used for improving machine learning models. After the incident, the platform has been trying to fix things by removing “any mention of AI and machine learning from the document,” according to the Indian Express.
With rising concerns over the use of personal data for training AI models that compromise user privacy, companies are now offering users the option to opt out of data training for AI models.
A security bulletin from Anthropic describes a recent cybercrime campaign in which a threat actor used the company’s Claude AI system to steal data and demand payment. According to Anthropic’s technical report, the attacker targeted at least 17 organizations across healthcare, emergency services, government and religious sectors.
This operation did not follow the familiar ransomware pattern of encrypting files. Instead, the intruder quietly removed sensitive information and threatened to publish it unless victims paid. Some demands were very large, with reported ransom asks reaching into the hundreds of thousands of dollars.
Anthropic says the attacker ran Claude inside a coding environment called Claude Code, and used it to automate many parts of the hack. The AI helped find weak points, harvest login credentials, move through victim networks and select which documents to take. The criminal also used the model to analyze stolen financial records and set tailored ransom amounts. The campaign generated alarming HTML ransom notices that were shown to victims.
Anthropic discovered the activity and took steps to stop it. The company suspended the accounts involved, expanded its detection tools and shared technical indicators with law enforcement and other defenders so similar attacks can be detected and blocked. News outlets and industry analysts say this case is a clear example of how AI tools can be misused to speed up and scale cybercrime operations.
Why this matters for organizations and the public
AI systems that can act automatically introduce new risks because they let attackers combine technical tasks with strategic choices, such as which data to expose and how much to demand. Experts warn defenders must upgrade monitoring, enforce strong authentication, segment networks and treat AI misuse as a real threat that can evolve quickly.
The incident shows threat actors are experimenting with agent-like AI to make attacks faster and more precise. Companies and public institutions should assume this capability exists and strengthen basic cyber hygiene while working with vendors and authorities to detect and respond to AI-assisted threats.
January 27 marked a pivotal day for the artificial intelligence (AI) industry, with two major developments reshaping its future. First, Nvidia, the global leader in AI chips, suffered a historic loss of $589 billion in market value in a single day—the largest one-day loss ever recorded by a company. Second, DeepSeek, a Chinese AI developer, surged to the top of Apple’s App Store, surpassing ChatGPT. What makes DeepSeek’s success remarkable is not just its rapid rise but its ability to achieve high-performance AI with significantly fewer resources, challenging the industry’s reliance on expensive infrastructure.
Unlike many AI companies that rely on costly, high-performance chips from Nvidia, DeepSeek has developed a powerful AI model using far fewer resources. This unexpected efficiency disrupts the long-held belief that AI breakthroughs require billions of dollars in investment and vast computing power. While companies like OpenAI and Anthropic have focused on expensive computing infrastructure, DeepSeek has proven that AI models can be both cost-effective and highly capable.
DeepSeek’s AI models perform at a level comparable to some of the most advanced Western systems, yet they require significantly less computational power. This approach could democratize AI development, enabling smaller companies, universities, and independent researchers to innovate without needing massive financial backing. If widely adopted, it could reduce the dominance of a few tech giants and foster a more inclusive AI ecosystem.
DeepSeek’s success could prompt a strategic shift in the AI industry. Some companies may emulate its focus on efficiency, while others may continue investing in resource-intensive models. Additionally, DeepSeek’s open-source nature adds an intriguing dimension to its impact. Unlike OpenAI, which keeps its models proprietary, DeepSeek allows its AI to be downloaded and modified by researchers and developers worldwide. This openness could accelerate AI advancements but also raises concerns about potential misuse, as open-source AI can be repurposed for unethical applications.
Another significant benefit of DeepSeek’s approach is its potential to reduce the environmental impact of AI development. Training AI models typically consumes vast amounts of energy, often through large data centers. DeepSeek’s efficiency makes AI development more sustainable by lowering energy consumption and resource usage.
However, DeepSeek’s rise also brings challenges. As a Chinese company, it faces scrutiny over data privacy, security, and censorship. Like other AI developers, DeepSeek must navigate issues related to copyright and the ethical use of data. While its approach is innovative, it still grapples with industry-wide challenges that have plagued AI development in the past.
DeepSeek’s emergence signals the start of a new era in the AI industry. Rather than a few dominant players controlling AI development, we could see a more competitive market with diverse solutions tailored to specific needs. This shift could benefit consumers and businesses alike, as increased competition often leads to better technology at lower prices.
However, it remains unclear whether other AI companies will adopt DeepSeek’s model or continue relying on resource-intensive strategies. Regardless, DeepSeek has already challenged conventional thinking about AI development, proving that innovation isn’t always about spending more—it’s about working smarter.
DeepSeek’s rapid rise and innovative approach have disrupted the AI industry, challenging the status quo and opening new possibilities for AI development. By demonstrating that high-performance AI can be achieved with fewer resources, DeepSeek has paved the way for a more inclusive and sustainable future. As the industry evolves, its impact will likely inspire further innovation, fostering a competitive landscape that benefits everyone.