Generative AI and Environmental Risks
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/
Related Blogs
Brief Overview of the EU AI Act
The EU AI Act, Regulation (EU) 2024/1689, was officially published in the EU Official Journal on 12 July 2024. This landmark legislation on Artificial Intelligence (AI) will come into force just 20 days after publication, setting harmonized rules across the EU. It amends key regulations and directives to ensure a robust framework for AI technologies. The AI Act, a set of EU rules governing AI, has been in development for two years and now, the EU AI Act enters into force across all 27 EU Member States on 1 August 2024, with certain future deadlines tied up and the enforcement of the majority of its provisions will commence on 2 August 2026. The law prohibits certain uses of AI tools, including those that threaten citizens' rights, such as biometric categorization, untargeted scraping of faces, and systems that try to read emotions are banned in the workplace and schools, as are social scoring systems. It also prohibits the use of predictive policing tools in some instances. The law takes a phased approach to implementing the EU's AI rulebook, meaning there are various deadlines between now and then as different legal provisions will start to apply.
The framework puts different obligations on AI developers, depending on use cases and perceived risk. The bulk of AI uses will not be regulated as they are considered low-risk, but a small number of potential AI use cases are banned under the law. High-risk use cases, such as biometric uses of AI or AI used in law enforcement, employment, education, and critical infrastructure, are allowed under the law but developers of such apps face obligations in areas like data quality and anti-bias considerations. A third risk tier also applies some lighter transparency requirements for makers of tools like AI chatbots.
In case of failure to comply with the Act, the companies in the EU providing, distributing, importing, and using AI systems and GPAI models, are subject to fines of up to EUR 35 million or seven per cent of the total worldwide annual turnover, whichever is higher.
Key highlights of EU AI Act Provisions
- The AI Act classifies AI according to its risk. It prohibits Unacceptable risks such as social scoring systems and manipulative AI. The regulation mostly addresses high-risk AI systems.
- Limited-risk AI systems are subject to lighter transparency obligations and according to the act, the developers and deployers must ensure that the end-users are aware that the interaction they are having is with AI such as Chatbots and Deepfakes. The AI Act allows the free use of minimal-risk AI. This includes the majority of AI applications currently available in the EU single market like AI-enabled video games, and spam filters, but with the advancement of Gen AI changes with regards to this might be done. The majority of obligations fall on providers (developers) of high-risk AI systems that intend to place on the market or put into service high-risk AI systems in the EU, regardless of whether they are based in the EU or a third country. And also, a third-country provider where the high-risk AI system’s output is used in the EU.
- Users are natural or legal persons who deploy an AI system in a professional capacity, not affected end-users. Users (deployers) of high-risk AI systems have some obligations, though less than providers (developers). This applies to users located in the EU, and third-country users where the AI system’s output is used in the EU.
- General purpose AI or GPAI model providers must provide technical documentation, and instructions for use, comply with the Copyright Directive, and publish a summary of the content used for training. Free and open license GPAI model providers only need to comply with copyright and publish the training data summary, unless they present a systemic risk. All providers of GPAI models that present a systemic risk – open or closed – must also conduct model evaluations, and adversarial testing, and track and report serious incidents and ensure cybersecurity protections.
- The Codes of Practice will account for international approaches. It will cover but not necessarily be limited to the obligations, particularly the relevant information to include in technical documentation for authorities and downstream providers, identification of the type and nature of systemic risks and their sources, and the modalities of risk management accounting for specific challenges in addressing risks due to the way they may emerge and materialize throughout the value chain. The AI Office may invite GPAI model providers, and relevant national competent authorities to participate in drawing up the codes, while civil society, industry, academia, downstream providers and independent experts may support the process.
Application & Timeline of Act
The EU AI Act will be fully applicable 24 months after entry into force, but some parts will be applicable sooner, for instance the ban on AI systems posing unacceptable risks will apply six months after the entry into force. The Codes of Practice will apply nine months after entry into force. Rules on general-purpose AI systems that need to comply with transparency requirements will apply 12 months after the entry into force. High-risk systems will have more time to comply with the requirements as the obligations concerning them will become applicable 36 months after the entry into force. The expected timeline for the same is:
- August 1st, 2024: The AI Act will enter into force.
- February 2025: Prohibition of certain AI systems - Chapters I (general provisions) & II (prohibited AI systems) will apply; Prohibition of certain AI systems.
- August 2025: Chapter III Section 4 (notifying authorities), Chapter V (general purpose AI models), Chapter VII (governance), Chapter XII (confidentiality and penalties), and Article 78 (confidentiality) will apply, except for Article 101 (fines for General Purpose AI providers); Requirements for new GPAI models.
- August 2026: The whole AI Act applies, except for Article 6(1) & corresponding obligations (one of the categories of high-risk AI systems);
- August 2027: Article 6(1) & corresponding obligations apply.
The AI Act sets out clear definitions for the different actors involved in AI, such as the providers, deployers, importers, distributors, and product manufacturers. This means all parties involved in the development, usage, import, distribution, or manufacturing of AI systems will be held accountable. Along with this, the AI Act also applies to providers and deployers of AI systems located outside of the EU, e.g., in Switzerland, if output produced by the system is intended to be used in the EU. The Act applies to any AI system within the EU that is on the market, in service, or in use, covering both AI providers (the companies selling AI systems) and AI deployers (the organizations using those systems).
In short, the AI Act will apply to different companies across the AI distribution chain, including providers, deployers, importers, and distributors (collectively referred to as “Operators”). The EU AI Act also has extraterritorial application and can also apply to companies not established in the EU, or providers outside the EU if they -make an AI system or GPAI model available on the EU market. Even if only the output generated by the AI system is used in the EU, the Act still applies to such providers and deployers.
CyberPeace Outlook
The EU AI Act, approved by EU lawmakers in 2024, is a landmark legislation designed to protect citizens' health, safety, and fundamental rights from potential harm caused by AI systems. The AI Act will apply to AI systems and GPAI models. The Act creates a tiered risk categorization system with various regulations and stiff penalties for noncompliance. The Act adopts a risk-based approach to AI governance, categorizing potential risks into four tiers: unacceptable, high, limited, and low. Violations of banned systems carry the highest fine: €35 million, or 7 percent of global annual revenue. It establishes transparency requirements for general-purpose AI systems. The regulation also provides specific rules for general-purpose AI (GPAI) models and lays down more stringent requirements for GPAI models with 'high-impact capabilities' that could pose a systemic risk and have a significant impact on the internal market. For high-risk AI systems, the AI Act addresses the issues of fundamental rights impact assessment and data protection impact assessment.
The EU AI Act aims to enhance trust in AI technologies by establishing clear regulatory standards governing AI. We encourage regulatory frameworks that strive to balance the desire to foster innovation with the critical need to prevent unethical practices that may cause user harm. The legislation can be seen as strengthening the EU's position as a global leader in AI innovation and developing regulatory frameworks for emerging technologies. It sets a global benchmark for regulating AI. The companies to which the act applies will need to make sure their practices align with the same. The act may inspire other nations to develop their own legislation contributing to global AI governance. The world of AI is complex and challenging, the implementation of regulatory checks, and compliance by the concerned companies, all pose a conundrum. However, in the end, balancing innovation with ethical considerations is paramount.
At the same hand, the tech sector welcomes regulatory progress but warns that overly-rigid regulations could stifle innovation. Hence flexibility and adaptability are key to effective AI governance. The journey towards robust AI regulation has begun in major countries, and it is important that we find the right balance between safety and innovation and also take into consideration the industry reactions.
References:
- https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=OJ:L_202401689
- https://www.theverge.com/2024/7/12/24197058/eu-ai-act-regulations-bans-deadline
- https://techcrunch.com/2024/07/12/eus-ai-act-gets-published-in-blocs-official-journal-starting-clock-on-legal-deadlines/
- https://www.wsgr.com/en/insights/eu-ai-act-to-enter-into-force-in-august.html
- https://www.techtarget.com/searchenterpriseai/tip/Is-your-business-ready-for-the-EU-AI-Act
- https://www.simmons-simmons.com/en/publications/clyimpowh000ouxgkw1oidakk/the-eu-ai-act-a-quick-guide
Executive Summary:
Recently, CyberPeace faced a case involving a fraudulent Android application imitating the Punjab National Bank (PNB). The victim was tricked into downloading an APK file named "PNB.apk" via WhatsApp. After the victim installed the apk file, it resulted in unauthorized multiple transactions on multiple credit cards.
Case Study: The Attack: Social Engineering Meets Malware
The incident started when the victim clicked on a Facebook ad for a PNB credit card. After submitting basic personal information, the victim receives a WhatsApp call from a profile displaying the PNB logo. The attacker, posing as a bank representative, fakes the benefits and features of the Credit Card and convinces the victim to install an application named PNB.apk. The so called bank representative sent the app through WhatsApp, claiming it would expedite the credit card application. The application was installed in the mobile device as a customer care application. It asks for permissions such as to send or view SMS messages. The application opens only if the user provides this permission.
It extracts the credit card details from the user such as Full Name, Mobile Number, complain, on further pages irrespective of Refund, Pay or Other. On further processing, it asks for other information such as credit card number, expiry date and cvv number.
Now the scammer has access to all the details of the credit card information, access to read or view the sms to intercept OTPs.
The victim, thinking they were securely navigating the official PNB website, was unaware that the malware was granting the hacker remote access to their phone. This led to ₹4 lakhs worth of 11 unauthorized transactions across three credit cards.
The Investigation & Analysis:
Upon receiving the case through CyberPeace helpline, the CyberPeace Research Team acted swiftly to neutralize the threat and secure the victim’s device. Using a secure remote access tool, we gained control of the phone with the victim’s consent. Our first step was identifying and removing the malicious "PNB.apk" file, ensuring no residual malware was left behind.
Next, we implemented crucial cyber hygiene practices:
- Revoking unnecessary permissions – to prevent further unauthorized access.
- Running antivirus scans – to detect any remaining threats.
- Clearing sensitive data caches – to remove stored credentials and tokens.
The CyberPeace Helpline team assisted the victim to report the fraud to the National Cybercrime Portal and helpline (1930) and promptly blocked the compromised credit cards.
The technical analysis for the app was taken ahead and by using the md5 hash file id. This app was marked as malware in virustotal and it has all the permissions such as Send/Receive/Read SMS, System Alert Window.
In the similar way, we have found another application in the name of “Axis Bank” which is circulated through whatsapp which is having similar permission access and the details found in virus total are as follows:
Recommendations:
This case study implies the increasingly sophisticated methods used by cybercriminals, blending social engineering with advanced malware. Key lessons include:
- Be vigilant when downloading the applications, even if they appear to be from legitimate sources. It is advised to install any application after checking through an application store and not through any social media.
- Always review app permissions before granting access.
- Verify the identity of anyone claiming to represent financial institutions.
- Use remote access tools responsibly for effective intervention during a cyber incident.
By acting quickly and following the proper protocols, we successfully secured the victim’s device and prevented further financial loss.
Introduction
A recent massive scam has been uncovered in the Indian state of Gujarat, where the Criminal Investigation Department (CID) has blacklisted 30,000 SIM cards that were used for illegal activities. The scam has created a huge uproar in the state, and its implications are significant. In this blog, we will discuss the details of the Gujarat scam and its impact on the state.
What is sim card fraud?
Sim card fraud occurs when someone uses a fake or cloned sim card to impersonate someone else. This allows the fraudster to gain access to sensitive information or conduct transactions on behalf of the victim. The use of fraudulent sim cards has become increasingly common in recent years, with scammers targeting individuals and businesses around the world.
The Gujarat Scam: The Gujarat scam involves the use of SIM cards for illegal activities such as extortion, blackmail, and cybercrime. The CID has identified that the SIM cards were obtained using fake documents and were used for illegal activities. The scam has been happening for a while, involving several individuals, including businessmen, politicians, and government officials.
The CID has conducted raids across the state and has arrested several individuals involved in the scam. They have also seized a significant amount of cash, mobile phones, and other electronic devices used for illegal activities. The investigation is ongoing, and more arrests are expected in the coming days.
The Gujarat scam is not an isolated incident, as similar scams have been reported in other parts of the country. The Telecom Regulatory Authority of India (TRAI) has also reported that several telecom operators are not following the regulations and are not verifying the authenticity of documents used to obtain SIM cards.
Impact on the State: The Gujarat scam has caused significant damage to the state’s reputation, and it has also affected the economy. The scam has highlighted the lack of regulation in the telecom industry, and it has exposed the loopholes in the system that criminals are exploiting.
The blacklisting of 30,000 SIM cards will affect several individuals who may have obtained them legally but were unaware of their use for illegal activities. The blacklisting may also impact businesses that rely on mobile phones for their operations.
The scam has also raised concerns about personal information and data safety. With the use of fake documents to obtain SIM cards, it is evident that personal information is not secure and can be easily misused. The government needs to take steps to ensure that personal information is protected and that the telecom industry is regulated to prevent such scams from happening in the future.
Steps Taken by the Government: The Gujarat scam has prompted the government to take action to prevent such incidents from happening in the future. The government has announced that it will implement stricter regulations in the telecom industry to prevent the misuse of SIM cards. The government has also announced that it will introduce a system to verify the authenticity of documents used to obtain SIM cards.
The government has also urged citizens to be vigilant and report any suspicious activity related to the misuse of SIM cards. The government has assured citizens that it will take strict action against those involved in the scam and that it will ensure the safety of personal information and data.
The TRAI has also taken steps to address the issue. It has directed telecom operators to verify the authenticity of documents used to obtain SIM cards and to follow the regulations. The TRAI has also introduced a new system to identify and deactivate inactive SIM cards.
Here are some key takeaways from the Gujarat Sim scam: These takeaways should be kept in mind to prevent such incidents from happening in the future and to ensure the safety of citizens and businesses.
Need for Stricter Regulations: The Gujarat Sim scam has highlighted the need for stricter regulations in the telecom industry. The government needs to ensure that telecom operators follow the regulations and verify the authenticity of documents used to obtain SIM cards. This will help prevent the misuse of SIM cards and illegal activities.
Importance of Personal Information Security: The scam has raised concerns about personal information and data safety. It is important to ensure that personal information is protected and that the telecom industry is regulated to prevent such scams from happening in the future.
Impact on Reputation and Economy: The Gujarat scam has caused significant damage to the state’s reputation, and it has also affected the economy. The blacklisting of 30,000 SIM cards will impact several individuals who may have obtained them legally but were unaware of their use for illegal activities. The scam has also raised concerns about the safety of businesses that rely on mobile phones for their operations.
Need for Vigilance: The government has urged citizens to be vigilant and report any suspicious activity related to the misuse of SIM cards. It is important for citizens to be aware of the regulations and to report any illegal activities to prevent such incidents from happening in the future.
Strong Action Against Criminals: The blacklisting of 30,000 SIM cards and the arrests made by the CID sends a strong message to those involved in illegal activities that they will not be spared. It is important for the government to take strict action against those involved in the scam to deter others from engaging in such activities.
Conclusion
The Gujarat scam has exposed vulnerabilities in the telecom industry and highlighted the need for stricter regulations to prevent such incidents from happening in the future. The blacklisting of 30,000 SIM cards has sent a strong message to those involved in illegal activities that they will not be spared. The government’s efforts to implement stricter regulations and ensure the safety of personal information and data are commendable. It is now up to the citizens to be vigilant and report any suspicious activity to prevent such incidents from happening in the future.
The telecom industry plays a vital role in the country’s development, and it is important to ensure that it is regulated to prevent the misuse of its services. Overall, the Gujarat Sim scam has highlighted the need for stricter regulations, personal information security, vigilance, and strong action against criminals.
