Telegram Faces Backlash Over New Policy to Share User Data with Authorities

The recent changes to Telegram’s privacy policy have ignited significant concerns regarding user privacy, marking a departure from the company’s longstanding commitment to protecting user data. On September 23, Telegram CEO Pavel Durov announced that the platform would begin sharing user data, such as IP addresses and phone numbers, with authorities in response to lawful requests. This shift has raised eyebrows among privacy advocates and experts alike.

Balancing Regulatory Compliance and User Privacy

A central issue in this policy change is the tension between adhering to regulatory requirements and safeguarding user data. Anndy Lian, an intergovernmental blockchain expert, argues that Telegram’s move could set a dangerous precedent, potentially prompting other privacy-focused services to lower their privacy standards. By sharing user information with law enforcement, Telegram might pave the way for increased surveillance and diminished user privacy across the tech industry.

Motivations Behind the Policy Shift

Telegram’s decision to alter its privacy policy follows mounting concerns over the misuse of the platform for illegal activities. This policy update came shortly after Durov’s arrest in France on August 24, further underscoring the urgency for Telegram to address law enforcement concerns. To mitigate criminal activities, Telegram has also incorporated artificial intelligence algorithms and human moderators to remove problematic content from Telegram Search, aiming to make the platform less appealing for illicit use.

Comparisons with Other Messaging Apps

While Telegram’s new policy has sparked debate, it is not an outlier among major messaging apps. WhatsApp and Meta’s Messenger have long shared user data with authorities when legal requests are made. WhatsApp’s privacy policy explicitly notes that in cases of imminent risk of serious physical injury, the app may disclose information to law enforcement. Meta has been complying with legal data requests for years, sharing user data in over 77% of the 528,000 requests it has received since July 2013.

The Broader Trend in Privacy Policies

Telegram’s recent adjustments to its privacy policy have sparked considerable concern about user privacy, signaling a noticeable shift from the company’s traditional stance on safeguarding user data. On September 23, Telegram CEO Pavel Durov revealed that the messaging platform would now cooperate with authorities by sharing user information, such as IP addresses and phone numbers, in response to legitimate legal requests. This move has caused a stir among privacy advocates and experts, who have long regarded Telegram as a stalwart defender of privacy.

Historically, the app has been celebrated for its robust encryption and dedication to user privacy, making it a preferred choice for those who highly value their digital security. The new policy marks a significant deviation from these values, prompting questions about the future direction of the platform and its impact on user trust. Experts argue that this change undermines the pledge of confidentiality that initially attracted millions of users to Telegram, potentially making it less appealing as a secure communication tool. The debate continues as users and specialists consider the implications of this policy update.

Explore more

Agentic AI Redefines the Software Development Lifecycle

The quiet hum of servers executing tasks once performed by entire teams of developers now underpins the modern software engineering landscape, signaling a fundamental and irreversible shift in how digital products are conceived and built. The emergence of Agentic AI Workflows represents a significant advancement in the software development sector, moving far beyond the simple code-completion tools of the past.

Is AI Creating a Hidden DevOps Crisis?

The sophisticated artificial intelligence that powers real-time recommendations and autonomous systems is placing an unprecedented strain on the very DevOps foundations built to support it, revealing a silent but escalating crisis. As organizations race to deploy increasingly complex AI and machine learning models, they are discovering that the conventional, component-focused practices that served them well in the past are fundamentally

Agentic AI in Banking – Review

The vast majority of a bank’s operational costs are hidden within complex, multi-step workflows that have long resisted traditional automation efforts, a challenge now being met by a new generation of intelligent systems. Agentic and multiagent Artificial Intelligence represent a significant advancement in the banking sector, poised to fundamentally reshape operations. This review will explore the evolution of this technology,

Cooling Job Market Requires a New Talent Strategy

The once-frenzied rhythm of the American job market has slowed to a quiet, steady hum, signaling a profound and lasting transformation that demands an entirely new approach to organizational leadership and talent management. For human resources leaders accustomed to the high-stakes war for talent, the current landscape presents a different, more subtle challenge. The cooldown is not a momentary pause

What If You Hired for Potential, Not Pedigree?

In an increasingly dynamic business landscape, the long-standing practice of using traditional credentials like university degrees and linear career histories as primary hiring benchmarks is proving to be a fundamentally flawed predictor of job success. A more powerful and predictive model is rapidly gaining momentum, one that shifts the focus from a candidate’s past pedigree to their present capabilities and