#FactCheck-Air Taxi is a prototype and is not launched to commercial public

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/

Data localisation refers to restrictions in the data flow by limiting the physical storage and processing of data within a given jurisdiction’s boundaries.  

An obvious benefit contributing to the importance of data localisation is the privacy benefits it offers. In addition to this, data localisation also has the potential to safeguard sensitive data and decrease the probability of cyber-attacks. In India, data localisation has become a key issue in the last decade due to the increase in the discourse for data privacy. 

The Legal Framework in India

India passed the Digital Personal Data Protection Act of 2023 which directs the data fiduciaries (collectors and processors of digital personal data) to store the data of Indian citizens within India. This push for data localisation aligns with India’s position to enhance privacy, national security and regulatory control. It further requires data fiduciaries to adhere to the principles of data minimisation, purposeful limitation and consent of the data principles. Further, Section 17 of the Act prohibits the transfer of sensitive personal data to foreign jurisdictions unless they meet satisfactory privacy protection standards. 

The Reserve Bank of India, via a circular for Payments Data Regulation in 2018, has mandated that all payment data be stored in India, though it can be processed abroad. It requires the telecom sector to ensure local storage and local processing of subscriber information. It further prohibits the transferring of subscribers’ account information overseas.

MeitY’s Information Technology (Intermediary Guidelines and Digital Media Ethics Code) Rules, 2021, emphasise data localisation, specifically when it involves government or critical data. The main idea behind this is that data related to Indian citizens or government activities should remain accessible to Indian law enforcement agencies and is not subject to external jurisdiction.

Common Misinformation about Data Localisation and its Impact

Misconceptions fuel misinformation and influence public perception and policy debates. A common misconception is that all data must be stored in India. It should be noted that non-critical and non-sensitive data are not subject to localisation, and can be cleared for cross-border transfers under specific circumstances.

Another misconception is that data localisation alone ensures complete security. A robust cybersecurity approach, infrastructure and capabilities are what guarantee security and this holds true regardless of the location of where the data is stored. 

The notion that small businesses and startups will suffer the most is untrue. While data localisation policies may lead to increased costs, they foster innovation in the domestic infrastructure and services. This potentially fuels development and innovation in these small businesses and startups. Claims that data localisation will stifle global business are unfounded. 

Proper regulations for data transfers can help balance data flows, enabling international trade while ensuring data sovereignty.

Real Impact of Data Localisation

Data localisation impacts several domains and has both positive and negative outcomes.

• It can be a driver for investment in local data centres and infrastructure, thereby inducing employment generation and boosting the domestic economy. And in contrast, the compliance costs may rise especially for MNCs that need to maintain multiple data storage systems. 
• It can expedite the growth of local technology ecosystems while encouraging innovation in cloud computing and data storage solutions. On the other hand, small businesses might face struggles to afford the required infrastructure updates and upgrades.
• Law enforcement agencies will be able to gain access to data more swiftly while avoiding lengthy processes such as the Mutual Legal Assistance Treaties (MLATs). However, it should be noted that storing data locally does not automatically ensure that they are immune from attacks and breaches.
• A balance between sovereignty and global partnerships is a challenge that emerges with data localisation. International Trade Relationships are vulnerable to data localisations where countries favour a free data flow. This can hamper foreign collaborations with companies that rely on global data systems.

CyberPeace Outlook

It is important to clear misinformation about data localisation, some strategies that can be undertaken are:

• Launching public awareness campaigns to educate the stakeholders about the real requirements and the benefits of data localisation. Misinformation about data restrictions and security guarantees should be tackled fairly quickly. 
• A balanced approach that promotes local economic development while at the same time allowing for the necessary cross-border data flows and creating a flexible and friendly business environment is important.
• India should work on international frameworks to streamline the process of data-sharing with other nations. This would protect national interests while making global cooperation easier.

Conclusion

Data localisation in India presents a valuable opportunity to enhance privacy, bolster national security, and stimulate economic growth through local infrastructure investment. Yet, addressing common misconceptions is crucial; the belief that all data must be stored domestically or that localisation alone ensures security is misleading. 

It’s vital to pair local data storage with robust cybersecurity measures and foster international cooperation. Supporting small businesses, which may face challenges due to localisation requirements, is equally important. By addressing misinformation, promoting flexible regulations, and working towards global data-sharing frameworks, India can effectively manage the complexities of data localisation, safeguarding national interests while encouraging innovation and economic development. 

References

• https://www.thehindu.com/sci-tech/technology/are-data-localisation-requirements-necessary-and-proportionate/article66131957.ece 
• https://carnegieendowment.org/research/2021/04/how-would-data-localization-benefit-india?lang=en
• https://www.rbi.org.in/commonperson/English/Scripts/FAQs.aspx?Id=2995
• https://www.meity.gov.in/writereaddata/files/Information%20Technology%20%28Intermediary%20Guidelines%20and%20Digital%20Media%20Ethics%20Code%29%20Rules%2C%202021%20%28updated%2006.04.2023%29-.pdf 

Introduction

Recently the Indian Government banned the import of Laptops and tablets in India under the computers of HSN 8471. According to the notification of the government, Directorate General of foreign trade, there will be restrictions on the import of Laptops, tablets, and other electronic items from 1^st November 2023. The government advised the Domestic companies to apply for the license within three months. As the process is simple, and many local companies have already applied for the license. The government will require a valid license for the import of laptops and other electronic items.

The Government imposed restrictions on the Import of Laptops & other electronic products

The DGFT (The directorate General of foreign trade) imposed restrictions on the import of electronic items in India. And, there has been the final date has also been given that the companies only have 3 months to apply for a valid license, from November 1^st 2023there will be a requirement for a valid license for the import, and there will be a proper ban on the import of laptops & tablets, and other electronic items. The ban is on the HSN-8471. These are the products that indicate that they are taxable. It is a classification code to identify the taxable items. India has sufficient capacity and capability to manufacture their own IT hardware devices and boost production.

The government has notified production linked incentive, PLI Scheme 2.0, for the IT devices, which will soon be disclosed, and the scheme is expected to lead to a total of 29 thousand crore rupees worth of IT hardware nearly. And this will create future job opportunities in the five to six years.

The pros & cons of the import

Banning import has two sides. The positive one is that, it will promote the domestic manufacturers, local companies will able to grow, and there will be job opportunities, but if we talk about the negative side of the import, then the prices will be high for the consumers. One aspect is making India’s digital infrastructure stable, and the other side is affecting consumers.

Reasons Behind the ban on the Import of electronic items

There are the following reasons behind the ban on the Import of laptops and tablets,

• The primary reason why the government banned the import of laptops and other electronic items is because of security concerns about the data. And to prevent data theft a step has been taken by the Government.
• The banning will help the domestic manufacturer to grow and will provide opportunities to the local companies in India.
• It will help in the creation of Job vacancies in the country.
• There will be a curb down of selling of Chinese products.

The government will promote the digital infrastructure of India by putting a ban on imports. Such as there are domestic companies like Reliance recently launched a laptop by the name of Jio Book, and there is a company that sells the cheapest tablet called Aakash, so the import ban will promote these types of electronic items of the local companies. This step will soon result in digital advancement in India.

Conclusion

The laptop, tablets, and other electronic products that have been banned in India will make a substantial move with the implications. The objective of the ban is to encourage domestic manufacturing and to secure the data, however, it will also affect the consumers which can not be ignored. The other future effects are yet to be seen. But the one scenario is clear, that the policy will significantly make a change in India’s Technology industry.