#FactCheck: Viral Video of Chandra Arya Speaking Kannada Unrelated to Canadian PM Nomination

Introduction

Generative AI models are significant consumers of computational resources and energy required for training and running models. While AI is being hailed as a game-changer, however underneath the shiny exterior, cracks are present which significantly raises concerns for its environmental impact. The development, maintenance, and disposal of AI technology all come with a large carbon footprint. The energy consumption of AI models, particularly large-scale models or image generation systems, these models rely on data centers powered by electricity, often from non-renewable sources, which exacerbates environmental concerns and contributes to substantial carbon emissions.

As AI adoption grows, improving energy efficiency becomes essential. Optimising algorithms, reducing model complexity, and using more efficient hardware can lower the energy footprint of AI systems. Additionally, transitioning to renewable energy sources for data centers can help mitigate their environmental impact. There is a growing need for sustainable AI development, where environmental considerations are integral to model design and deployment.

A breakdown of how generative AI contributes to environmental risks and the pressing need for energy efficiency:

• Gen AI during the training phase has high power consumption, when vast amounts of computational power which is often utilising extensive GPU clusters for weeks or at times even months, consumes a substantial amount of electricity. Post this phase, the inference phase where the deployment of these models takes place for real-time inference, can be energy-extensive especially when we take into account the millions of users of Gen AI.
• The main source of energy used for training and deploying AI models often comes from non-renewable sources which then contribute to the carbon footprint. The data centers where the computations for Gen AI take place are a significant source of carbon emissions if they rely on the use of fossil fuels for their energy needs for the training and deployment of the models. According to a study by MIT, training an AI can produce emissions that are equivalent to around 300 round-trip flights between New York and San Francisco. According to a report by Goldman Sachs, Data Companies will use 8% of US power by 2030, compared to 3% in 2022 as their energy demand grows by 160%.
• The production and disposal of hardware (GPUs, servers) necessary for AI contribute to environmental degradation. Mining for raw materials and disposing of electronic waste (e-waste) are additional environmental concerns. E-waste contains hazardous chemicals, including lead, mercury, and cadmium, that can contaminate soil and water supplies and endanger both human health and the environment. 

Efforts by the Industry to reduce the environmental risk posed by Gen AI 

There are a few examples of how companies are making efforts to reduce their carbon footprint, reduce energy consumption and overall be more environmentally friendly in the long run. Some of the efforts are as under:

• Google's TPUs in particular the Google Tensor are designed specifically for machine learning tasks and offer a higher performance-per-watt ratio compared to traditional GPUs, leading to more efficient AI computations during the shorter periods requiring peak consumption. 
• Researchers at Microsoft, for instance, have developed a so-called “1 bit” architecture that can make LLMs 10 times more energy efficient than the current leading system. This system simplifies the models’ calculations by reducing the values to 0 or 1, slashing power consumption but without sacrificing its performance.
• OpenAI has been working on optimizing the efficiency of its models and exploring ways to reduce the environmental impact of AI and using renewable energy as much as possible including the research into more efficient training methods and model architectures.

Policy Recommendations

We advocate for the sustainable product development process and press the need for Energy Efficiency in AI Models to counter the environmental impact that they have. These improvements would not only be better for the environment but also contribute to the greater and sustainable development of Gen AI.  Some suggestions are as follows:

• AI needs to adopt a Climate justice framework which has been informed by a diverse context and perspectives while working in tandem with the UN’s (Sustainable Development Goals) SDGs.
• Working and developing more efficient algorithms that would require less computational power for both training and inference can reduce energy consumption. Designing more energy-efficient hardware, such as specialized AI accelerators and next-generation GPUs, can help mitigate the environmental impact. 
• Transitioning to renewable energy sources (solar, wind, hydro) can significantly reduce the carbon footprint associated with AI. The World Economic Forum (WEF) projects that by 2050, the total amount of e-waste generated will have surpassed 120 million metric tonnes.
• Employing techniques like model compression, which reduces the size of AI models without sacrificing performance, can lead to less energy-intensive computations. Optimized models are faster and require less hardware, thus consuming less energy.
• Implementing scattered learning approaches, where models are trained across decentralized devices rather than centralized data centers, can lead to a better distribution of energy load evenly and reduce the overall environmental impact.
• Enhancing the energy efficiency of data centers through better cooling systems, improved energy management practices, and the use of AI for optimizing data center operations can contribute to reduced energy consumption.

Final Words

The UN Sustainable Development Goals (SDGs) are crucial for the AI industry just as other industries as they guide responsible innovation. Aligning AI development with the SDGs will ensure ethical practices, promoting sustainability, equity, and inclusivity. This alignment fosters global trust in AI technologies, encourages investment, and drives solutions to pressing global challenges, such as poverty, education, and climate change, ultimately creating a positive impact on society and the environment. The current state of AI is that it is essentially utilizing enormous power and producing a product not efficiently utilizing the power it gets. AI and its derivatives are stressing the environment in such a manner which if it continues will affect the clean water resources and other non-renewable power generation sources which contributed to the huge carbon footprint of the AI industry as a whole.  

References

• https://cio.economictimes.indiatimes.com/news/artificial-intelligence/ais-hunger-for-power-can-be-tamed/111302991
• https://earth.org/the-green-dilemma-can-ai-fulfil-its-potential-without-harming-the-environment/ 
• https://www.technologyreview.com/2019/06/06/239031/training-a-single-ai-model-can-emit-as-much-carbon-as-five-cars-in-their-lifetimes/
• https://www.scientificamerican.com/article/ais-climate-impact-goes-beyond-its-emissions/ ‍
• https://insights.grcglobalgroup.com/the-environmental-impact-of-ai/

Introduction

You must have heard of several techniques of cybercrime up to this point. Many of which we could never have anticipated. Some of these reports are coming from different parts of the country. Where video calls are being utilised to cheat. Through video calls, cybercriminals are making individuals victims of fraud. During this incident, fraudsters film pornographic recordings of both the victims using a screen recorder, then blackmail them by emailing these videos and demanding money. However, cybercriminals are improving their strategies to defraud more people. In this blog post, we will explore the tactics involved in this case, the psychological impact, and ways to combat it. Before we know more about the case, let’s have a look at deep fake, AI, and Sextortion and how fraudsters use technology to commit crimes.

Understanding Deepfake

Deepfake technology is the manipulation or fabrication of multimedia information such as videos, photos, or audio recordings using artificial intelligence (AI) algorithms, and profound learning models. These algorithms process massive quantities of data to learn and imitate human-like behaviour, allowing for very realistic synthetic media development.

Individuals with malicious intent may change facial expressions, bodily movements, and even voices in recordings using deepfake technology, basically replacing a person’s appearance with someone else’s. The produced film can be practically indistinguishable from authentic footage, making it difficult for viewers to distinguish between the two.

Sextortion and technology

Sextortion is a sort of internet blackmail in which offenders use graphic or compromising content to compel others into offering money, sexual favours, or other concessions. This information is usually gained by hacking, social engineering, or tricking people into providing sensitive information.

Deepfake technology combined with sextortion techniques has increased the impact on victims. Deepfakes may now be used by perpetrators to make and distribute pornographic or compromising movies or photographs that seem genuine but are completely fake. As the prospect of discovery grows increasingly credible and tougher to rebut, the stakes for victims rise.

Cyber crooks Deceive

In this present case, cyber thugs first make video calls to people and capture the footage. They then twist the footage and merge it with a distorted naked video. As a result, the victim is obliged to conceal the case. Following that, “they demand money as a ransom to stop releasing the doctored video on the victim’s contacts and social media platforms.” In this case, a video has emerged in which a lady who was supposedly featured in the first film is depicted committing herself because of the shame caused by the video’s release. These extra threats are merely intended to inflict psychological pressure and coercion on the victims.

Sextortionists have reached a new low by profiting from the misfortunes of others, notably targeting deceased victims. The offenders want to maximise emotional pain and persuade the victim into acquiescence by generating deep fake films depicting these persons. They use the inherent compassion and emotion connected with tragedy to exact bigger ransoms from their victims.

This distressing exploitation not only adds urgency to the extortion demands but also preys on the victim’s sensitivity and emotional instability. They even pressurize the victim by impersonating them, and if the demands are fulfilled, the victims may land up in jail.

Tactics used

The morphed death videos are precisely constructed to heighten emotional discomfort and instil terror in the targeted individual. By editing photographs or videos of the deceased, the offenders create unsettling circumstances that heighten the victim’s emotional response.

The psychological manipulation seeks to instil guilt, regret, and a sense of responsibility in the victim. The notion that they are somehow linked to the catastrophe increases their emotional weakness, making them more vulnerable to the demands of sextortionists. The offenders take use of these emotions, coercing victims into cooperation out of fear of being involved in the apparent tragedy.

The impact on the victim’s mental well-being cannot be overstated. They may experience intense psychological trauma, including anxiety, depression, and post-traumatic stress disorder (PTSD). The guilt and shame associated with the false belief of being linked to someone’s death can have long-lasting effects on their emotional health and overall quality of life, others may have trust issues.

Law enforcement agencies advised

Law enforcement organisations were concerned about the growing annoyance of these illegal acts. The use of deep fake methods or other AI technologies to make convincing morphing films demonstrates scammers’ improved ability. These tools are fully capable of modifying digital information in ways that are radically different from the genuine film, making it difficult for victims to detect the fake nature of the video.

Defence strategies to fight back: To combat sextortion, a proactive approach that empowers individuals and utilizes resources is required. This section delves into crucial anti-sextortion techniques such as reporting events, preserving evidence, raising awareness, and implementing digital security measures.

• Report the Incident: Sextortion victims should immediately notify law enforcement. Contact your local police or cybercrime department and supply them with any important information, including specifics of the extortion attempt, communication logs, and any other evidence that can assist in the investigation. Reporting the occurrence is critical for keeping criminals responsible and averting additional harm to others.
• Preserve Evidence: Preserving evidence is critical in creating a solid case against sextortionists. Save and document any types of contact connected to the extortion, including text messages, emails, and social media conversations. Take screenshots, record phone calls (if legal), and save any other digital material or papers that might be used as evidence. This evidence can be useful in investigations and judicial processes.

Digital security: Implementing comprehensive digital security measures can considerably lower the vulnerability to sextortion assaults. Some important measures that one can use:

• Use unique, complicated passwords for all online accounts, and avoid reusing passwords across platforms. Consider utilising password managers to securely store and create strong passwords.
• Enable two-factor authentication (2FA) whenever possible, which adds an extra layer of protection by requiring a second verification step, such as a code delivered to your phone or email, in addition to the password.
• Regular software updates: Keep your operating system, antivirus software, and programmes up to date. Security patches are frequently included in software upgrades to defend against known vulnerabilities.
• Adjust your privacy settings on social networking platforms and other online accounts to limit the availability of personal information and restrict access to your content.
• Be cautious when clicking on links or downloading files from unfamiliar or suspect sources. When exchanging personal information online, only use trusted websites.

Conclusion:

Combating sextortion demands a collaborative effort that combines proactive tactics and resources to confront this damaging practice. Individuals may actively fight back against sextortion by reporting incidences, preserving evidence, raising awareness, and implementing digital security measures. It is critical to empower victims, encourage their rehabilitation, and collaborate to build a safer online environment where sextortionists are held accountable and everyone can navigate the digital environment with confidence.

Introduction

‍

We inhabit an era where digital connectivity, while empowering, has also unleashed a relentless tide of cyber vulnerabilities, where personal privacy is constantly threatened, and crimes like sextortion are the perfect example of the sinister side of our hyperconnected world. Social media platforms, instant messaging apps, and digital content-sharing tools have all grown rapidly, changing how people communicate with one another and making it harder to distinguish between the private and public domains. The rise of sophisticated cybercrimes that use the very tools meant to connect us is the price paid for this unparalleled convenience. Sextortion, a portmanteau of “sex’ and “extortion”, stands out among them as a particularly pernicious kind of internet exploitation. Under the threat of disclosing their private information, photos, or videos, people are forced to engage in sexual behaviours or provide intimate content. Sextortion’s psychological component is what makes it particularly harmful, it feeds on social stigma, shame, and fear, which discourage victims from reporting the crime and feed the cycle of victimisation and silence. This cybercrime targets vulnerable people from all socioeconomic backgrounds and is not limited by age, gender, or location. 

‍

The Economy of Shame: Sextortion as a Cybercrime Industry

‍

A news report from June 03, 2025, reveals a sextortion racket busted in Delhi, where a money trail of over Rs. 5 crore was identified by different teams of the Crime branch. From synthetic financial identities to sextortion and other cyber frauds, a recipe for a sophisticated cybercrime chain was found. To believe this is an aberration is to overlook the reality that it is symptomatic of a much wider and largely uncharted criminal framework. According to the FBI’s 2024 IC3 report, “extortion (including sextortion)” has skyrocketed to 86,415 complaints with losses of $143 million reported in the United States (US) alone. This indicates that coercive image-based threats are no longer an isolated cybercrime but an everyday occurrence. Sextortion is no longer an isolated cybercrime; it has metamorphosed into a systematic, industrialised criminal enterprise. Another news report dated 19th July, 2025, where Delhi Police has detained four people suspected of participating in a sextortion scheme that targeted a resident of the Bhagwanpur Khera neighbourhood of Shahdara. The suspected people were allegedly arrested on a complaint wherein the victim was manipulated and fell prey to a dating site. 

The threat is amplified by the usage of deepfake technology, which allows offenders to create obscene content that looks believable. The approach, which relies on the stigma attached to sexual imagery in conservative societies like India, is that victims frequently give in to requests out of fear of damaging their reputations. The combination of cybercrime and cutting-edge technology highlights the lopsided power that criminals possess, leaving victims defenceless and law enforcement unable to keep up. 

‍

Legal Remedies and the Evolving Battle Against Sextortion

‍

Given the complexity of these crimes, India has recognised sextortion and similar cyber-enabled financial crimes under a number of legal frameworks. A change to recognising cyber-enabled sexual exploitation as an organised criminal business is shown by the introduction of specific provisions like Section 111 in the Bhartiya Nyaya Sanhita (BNS), 2023, which classifies organised cybercrimes including extortion and frauds which fall under its expansive interpretation, as a serious offence. Similarly, Section 318 (2) criminalises cheating with a maximum sentence of three years in prison or a fine, whereas Section 336 (2) makes digital forgery a crime with a maximum sentence with a maximum sentence of two years in prison or a fine. In addition to these regulations, cheating by personation through computer resources is punishable by the Information Technology Act, 2000, specifically Section 66D, which carries a maximum sentence of three years in prison and a maximum fine of Rs. 1 lakh. Due to issues with attribution, cross-border jurisdiction, and the discreet nature of digital evidence, enforcement is still inconsistent even with current statutory restrictions. 

The government and its agencies recognise that laws achieve real impact only when backed by awareness initiatives and accessible, localised mechanisms for redressal. Several Indian states and the Department of Telecommunications launched numerous campaigns to educate the public about and safeguard their mobile communication assets against identity theft, financial fraud, and cyberscams. Initiatives like Cyber Saathi Initiative and Cyber Dost by MHA, with the goal of improving forensic and victim reporting skills.

‍

Conclusion

‍

At CyberPeace, we understand that the best defence against online abuse is prevention. Our goal is to provide people with the information and resources to identify, avoid and report sextortion attempts like CyberPeace Helpline and organise awareness campaigns on safe digital habits. In order to remain updated with the constantly looming danger, our research and policy advocacy also focus on developing more robust legal and technological safeguards. 

To every reader: think before you share, secure your accounts, and never let shame silence you. If you or someone you know becomes a victim, report it immediately, help is available, and justice is possible. Together we can reclaim the internet as a space of trust, not terror. 

‍

References 

‍

• https://www.hindustantimes.com/india-news/delhi-police-busts-sextortion-cyberfraud-rackets-6-held-101748959601825.html 
• https://timesofindia.indiatimes.com/city/delhi/delhi-police-arrests-four-for-sextortion-and-blackmail-in-shahdara/articleshow/122767656.cms ‍
• https://cdn.ncw.gov.in/wp-content/uploads/2025/05/CyberSaheli.pdf