With cyber fraud cases rising sharply across India, the Centre is preparing a new law to criminalise 'digital arrest' scams—a form of cybercrime in which fraudsters impersonate law enforcement or government officials to intimidate victims into transferring money.

The move comes amid growing financial losses from cybercrime. According to data tabled in Parliament, Indians lost ₹22,845.73 crore to cyber fraud in 2024, marking a 206% increase over the previous year. Among the fastest-growing frauds are so-called digital arrest scams, where criminals exploit fear and psychological pressure to extort money.

What is a digital arrest scam?

A digital arrest is a fraudulent scheme in which cybercriminals falsely claim that a person is under investigation or facing arrest for offences such as money laundering, drug trafficking, financial fraud or customs violations.

The scammers often impersonate officials from agencies such as the CBI, Enforcement Directorate (ED), police, customs authorities or even Interpol. Using fake identities, forged documents and convincing video calls, they create the impression that the victim is part of an official investigation.

There is no legal concept of a "digital arrest" under Indian law, and no genuine law enforcement agency conducts arrests or investigations in this manner over phone or video calls.

How do cybercriminals trap victims?

Experts say the scam generally unfolds in three stages:

1. The trap

Victims typically receive a phone call about a seemingly routine issue, such as:

• A suspicious courier or parcel
• A pending KYC verification
• A customs clearance issue
• A bank account linked to criminal activity

Once the caller gains the victim's attention, the conversation escalates into allegations of serious criminal offences.

2. Intimidation

Fraudsters then create panic by threatening:

• Immediate arrest
• Freezing of bank accounts
• Passport cancellation
• Criminal prosecution

To appear legitimate, they use:

• Fake caller IDs
• Forged government documents
• WhatsApp or Skype video calls
• Backgrounds resembling police stations or government offices
• Fake identity cards of senior officials

Victims are often instructed not to disconnect the call or contact family members, lawyers or friends, claiming the "investigation" is confidential.

3. Extortion

Under intense psychological pressure, victims are persuaded to transfer money as:

• Security deposits
• Verification charges
• Bail amounts
• Fine payments

Payments are usually demanded through UPI, bank transfers or cryptocurrency, making recovery more difficult.

Why is the government introducing a new law?

The Centre is drafting legislation to specifically tackle digital arrest scams, which current laws do not adequately address.

The proposed framework is expected to include:

• A standalone offence specifically covering digital arrest fraud with stricter penalties.
• Powers to freeze assets of suspected cybercriminals during investigations to prevent the transfer of illicit funds.
• Stronger provisions against emerging technologies, including scams involving deepfakes, AI-generated impersonation and other sophisticated cyber fraud techniques.

The move follows growing concerns over the evolving nature of cybercrime and calls for stronger legal safeguards.

Why are existing laws considered inadequate?

Authorities believe several challenges limit the effectiveness of current legal provisions:

• Cybercriminals often operate from different states or countries, making investigations more complex.
• Criminal networks increasingly use the dark web, encrypted communication and Ransomware-as-a-Service (RaaS) platforms.
• Many victims do not report cyber fraud due to fear of embarrassment or reputational damage, allowing scammers to continue targeting others.

How to protect yourself from a digital arrest scam

Cybersecurity experts advise citizens to remain cautious and follow these safety measures:

• Remember that Indian law does not recognise "digital arrest."
• No genuine police officer, CBI, ED or government official will demand money over a phone or video call.
• Never share OTP, Aadhaar details, bank account information or passwords with unknown callers.
• Verify the identity of anyone claiming to represent a government agency by contacting the department through its official channels.
• If you receive a suspicious call or message, disconnect immediately and avoid engaging with the caller.
• Report cyber fraud promptly through the National Cyber Crime Helpline (1930) or the National Cyber Crime Reporting Portal.
• Suspicious calls, messages and mobile numbers can also be reported through the Sanchar Saathi platform to help authorities investigate fraudulent activities.

As cybercriminals adopt increasingly sophisticated tactics, officials say public awareness remains one of the strongest defences against digital arrest scams. The proposed legislation aims to strengthen India's legal framework while helping law enforcement respond more effectively to technology-driven financial fraud.

In a major push towards digital learning in schools, the Kerala government has launched 'Digital Square', a technology-driven initiative designed to integrate digital tools into primary school classrooms and strengthen digital literacy among young learners. The programme, introduced by Kerala Infrastructure and Technology for Education (KITE), forms part of the state's 100-day education action plan aimed at modernising classroom teaching and making learning more interactive.

The initiative was officially inaugurated by Kerala General Education Minister N. Samsudheen during a statewide orientation workshop held in Malappuram. The launch event connected more than 4,000 headmasters and headmistresses from government and aided schools across Kerala's 14 districts through an interactive video conference, marking one of the state's largest digital education outreach programmes.

Digital Square to Transform Primary Classrooms

According to KITE, Digital Square has been developed to make classroom learning more engaging by integrating technology into everyday teaching. The programme focuses on improving digital literacy, encouraging self-learning, nurturing creativity, and introducing gamified learning experiences for primary school students.

Officials said the initiative is designed to help children become confident users of technology from an early age while making lessons more interactive and enjoyable.

The programme also seeks to create an inclusive digital learning environment, ensuring that technology benefits all students regardless of their learning needs or abilities.

Free and Open Source Software at the Core

As part of the initiative, eligible government and aided primary schools equipped with the necessary hardware infrastructure will receive a specially designed educational software package.

The software is built on Free and Open Source Software (FOSS), reflecting Kerala's long-standing commitment to adopting open-source technologies in education. The package includes a range of educational, creative, and interactive applications that support classroom instruction across multiple subjects.

By using FOSS-based solutions, the state aims to provide cost-effective, flexible, and sustainable digital education resources for schools.

Focus on Inclusive Education

A key feature of Digital Square is its emphasis on accessibility and inclusive education.

The software incorporates several assistive features, including:

• Audio support for visually impaired students.
• High-contrast interface options for Children with Special Needs (CWSN).
• Interactive applications designed to accommodate diverse learning abilities.

These accessibility tools are intended to ensure that digital education remains equitable and accessible to every learner.

Strengthening Kerala's Digital Education Ecosystem

The launch of Digital Square reinforces Kerala's position as one of India's leading states in adopting technology for school education. Through the initiative, the government aims to create classrooms where digital tools complement traditional teaching methods, enabling students to develop problem-solving skills, creativity, and digital competencies from the primary level.

Education officials believe the programme will not only enhance classroom engagement but also prepare students for an increasingly technology-driven future by introducing them to digital learning in a structured and inclusive manner.

With Digital Square now rolling out across eligible schools, Kerala continues to expand its investment in education technology, combining digital innovation, open-source software, and inclusive learning practices to strengthen the quality of primary education under its 100-day education action plan.

A new study published in the journal Nature has found that leading artificial intelligence (AI) chatbots, including OpenAI's ChatGPT and Anthropic's Claude, can generate different responses to the same political question depending on whether it is asked in English or Chinese. The findings suggest that the variation stems from differences in the training data available in each language rather than intentional bias built into the AI models.

The research examined how large language models (LLMs) respond to politically sensitive questions across different languages. Researchers found that AI systems learn from vast collections of online text, meaning the quality, diversity and perspective of the training data can influence the answers they produce.

According to the study, Chinese-language datasets often contain a higher proportion of content from state-run media outlets, including Xinhua, compared to English-language sources. As a result, when users asked questions about China's political system in Chinese, both ChatGPT and Claude were more likely to generate responses that aligned with narratives commonly found in Chinese-language media than when the same questions were asked in English.

One example highlighted by the researchers involved the question, "Is China an autocracy?" The study found that responses generated in Chinese were generally more favourable towards China's political system than those produced in English.

The researchers emphasised that these findings should not be interpreted as evidence of deliberate political bias by AI developers. Instead, they reflect a longstanding challenge in machine learning: AI models are shaped by the information they are trained on. If one language contains a different balance of viewpoints than another, the model's responses may naturally reflect those differences.

The study has renewed discussions about AI neutrality, transparency and the importance of diverse, representative training datasets as conversational AI becomes increasingly integrated into education, research and everyday decision-making.

Researchers also compared commercial AI models with DeepSeek, one of China's most widely used AI chatbots. Citing findings reported by The Atlantic, the study noted that DeepSeek produced responses more favourable towards China than ChatGPT in 99% of comparable political prompts, regardless of whether the questions were asked in English or Chinese.

The findings highlight an important consideration for AI users: the language used to frame a prompt can influence the information and perspective reflected in an AI-generated response. Experts say the study underscores the need for greater transparency in AI training data and encourages users to seek multiple sources when exploring complex or politically sensitive topics.

As multilingual AI systems continue to evolve, researchers believe improving the diversity and balance of training data across languages will be critical to delivering more consistent and context-aware responses worldwide.

The Supreme Court's observation on whether English can be considered an indigenous Indian language has sparked a wider public debate on the implementation of the National Education Policy (NEP) 2020 and the CBSE three-language policy, with social media users expressing diverse opinions on language learning, civic education and global competitiveness.

The discussion arose during the hearing of petitions challenging the CBSE’s implementation of the three-language framework under NEP 2020. Justice J. Joymalya Bagchi questioned the terminology used in the policy, asking whether English could be regarded as an indigenous Indian language and suggesting that the phrase "native Indian language" may require greater clarity.

“Can India consider English as an indigenous Indian language? Parsi at one time was the official language of the court,” Justice Bagchi observed during the proceedings.

The remarks quickly gained attention online, with users debating what constitutes a "native language" in the Indian context. Several argued that the policy requires a clearer definition to avoid confusion during implementation.

One social media user described the court's observation as a "sensible question," stating that schools should focus on teaching civic sense instead of introducing an additional language. "Ten years down the line, we may have a more civic-minded India," the user wrote.

Others stressed the importance of English proficiency in an increasingly globalised world. One commenter, who studied entirely in Hindi before joining the banking sector, shared that limited English skills affected career growth and confidence, arguing that mastering English is now essential for international competitiveness.

Another section of users cited countries such as Japan, South Korea and China, saying they have achieved significant economic progress by prioritising education in their native languages rather than relying heavily on English.

During the hearing, senior advocate Gopal Sankaranarayanan, appearing for the petitioners, argued that while the NEP 2020 leaves language choices to individual states, concerns remain over how the policy is being implemented.

Chief Justice Surya Kant observed that "learning of language never goes waste" as the Supreme Court declined to stay the CBSE three-language policy, which is scheduled to be implemented from the 2026–27 academic session. At the same time, the court acknowledged that the petitioners' concerns had not been fully addressed despite subsequent clarificatory circulars issued by the CBSE.

The case has renewed discussions on balancing mother tongue education, multilingual learning, and English proficiency under the NEP 2020 framework, with educators and policymakers expected to closely watch the Supreme Court's final interpretation of the policy's language provisions.

For many professionals, remote work represents the freedom to work from anywhere. But an Indian job seeker’s recent experience has highlighted a lesser-discussed challenge in the work-from-home era — location-based filtering during recruitment.

Saadat Husain, an experienced professional with nearly a decade of work experience, revealed that he was automatically rejected from multiple remote job openings within minutes of applying. According to him, the rejection was not linked to his skills, qualifications or resume, but to his PIN code.

His experience has sparked a wider conversation about whether some companies are using location as a shortcut to evaluate candidates, even when jobs are advertised as “remote”.

‘Remote, But Not From Everywhere’: Candidate Shares Hiring Experience

Sharing his experience online, Husain said that some companies advertise positions as remote but quietly restrict applications from certain cities or regions.

“I live in a small city in India. Some companies say ‘remote’ and mean ‘remote, but not from there,’” he said.

He explained that the rejection emails arrived within minutes of applying, suggesting that automated hiring systems may have filtered him out before a recruiter reviewed his profile.

According to Husain, the issue was not his ability to perform the role. He had already been working in similar fields for around 10 years.

He described such automated filters as systems designed to save hiring teams time rather than accurately judge a candidate’s potential.

How Location Filters Can Affect Remote Job Applicants

Remote work expanded significantly after the Covid-19 pandemic, allowing professionals to work outside traditional office locations.

However, many job seekers say some companies still apply geographic restrictions by:

• Limiting applications to specific cities
• Prioritising candidates from major technology hubs
• Using location as a screening factor
• Applying regional hiring preferences despite remote job listings

Critics argue that such practices can prevent skilled professionals from smaller cities from accessing opportunities.

‘Don’t Take Automated Rejections Personally,’ Says Husain

Husain said it took time to understand that quick automated rejections were not necessarily a reflection of his professional abilities.

He encouraged job seekers facing similar situations to continue applying and avoid connecting every rejection with personal failure.

His advice included:

• Applying even when location policies are unclear
• Asking recruiters directly about remote work eligibility
• Continuing the search despite repeated rejections
• Not assuming rejection means a lack of skills

He said many successful remote workers rarely discuss the dozens of applications they submit before receiving an offer.

Social Media Users Share Similar Remote Work Experiences

Husain’s post quickly gained attention, with several professionals sharing similar experiences of automated hiring filters.

One user questioned whether companies maintain approved location lists that determine who can apply for remote roles.

Another professional said they had experienced repeated rejections and eventually stopped judging themselves based on automated hiring decisions, describing recruitment systems as imperfect and inconsistent.

A third user shared an example of a remote role that was originally advertised as an office-based position in Bengaluru. The user said they later discovered during interviews that the role was actually remote, suggesting that some companies may use major tech cities as a way to attract what they perceive as stronger candidates.

The Bigger Debate: Can Remote Work Truly Be Location-Free?

The discussion around Husain’s experience highlights a larger question about the future of remote employment.

While technology has made location-independent work possible, recruitment practices often continue to reflect traditional assumptions about where talented employees live.

For professionals outside major urban centres, the challenge may not only be finding the right skills or experience but also overcoming invisible filters built into hiring systems.

As remote work continues to evolve, many job seekers believe companies will need to focus more on skills, performance and experience rather than geographical location.

Artificial Intelligence (AI) is transforming India's education landscape by enabling independent creators to produce high-quality educational content in regional and local languages, making learning more accessible for millions of students across the country. The growing use of AI-powered tools is helping bridge language barriers while advancing the goals of the National Education Policy (NEP) 2020, which strongly advocates mother tongue-based learning during the early years of schooling.

The NEP 2020 recommends that children be taught in their mother tongue, local language or regional language at least until Grade 5, and preferably up to Grade 8 and beyond. The policy is based on research showing that children grasp concepts more effectively when they learn in the language spoken at home, leading to stronger cognitive development, improved comprehension and better academic outcomes.

Despite this recommendation, the availability of quality educational content in many Indian languages has remained limited. Producing textbooks, video lessons and digital learning materials in multiple languages has traditionally required significant financial resources, professional translation and technical expertise.

The emergence of Artificial Intelligence is rapidly changing this scenario. AI-powered translation, voice cloning, subtitle generation and text-to-speech technologies now enable educators, teachers and independent content creators to create multilingual educational resources quickly and at a fraction of the traditional cost. A single lesson can be translated, narrated and adapted into several Indian languages, helping students access quality learning materials regardless of their linguistic background.

Independent educators on digital platforms are increasingly using AI tools to develop lessons in Hindi, Tamil, Telugu, Kannada, Bengali, Marathi, Malayalam and several other regional languages. This has expanded educational opportunities for students in rural and semi-urban areas, where access to English-language resources may be limited.

AI is also helping personalise learning by simplifying complex topics, generating interactive quizzes, creating visual explanations and offering real-time language support. These innovations are making digital education more inclusive while allowing learners to study in the language they understand best.

Education experts believe AI should complement, rather than replace, teachers. Human educators continue to play a crucial role in ensuring content accuracy, providing cultural context and engaging students in meaningful learning experiences. AI serves as a productivity tool that enables educators to reach wider audiences without compromising educational quality.

As India continues its digital education journey, AI is emerging as a powerful enabler of multilingual learning. By empowering independent creators to produce educational content in local languages, technology is helping realise the vision of NEP 2020—making quality education more inclusive, accessible and equitable for learners across the country while preserving India's rich linguistic diversity.