What's Exactly Sustainable AI? Discover Why Required, It's Features, Elements, Application and Benefits+ Much More...!!

Abstract:

As the scale and urgency of the economic and human health impacts from our deteriorating natural environment grows, we have an opportunity to look at how AI can help transform traditional sectors and systems to address climate change, deliver food and water security, build sustainable cities, and protect biodiversity and human wellbeing.

Keywords:

Environment, Climate Change, AI for Food, AI for Water Security, Build Sustainable Future, Green AI 

Learning Outcomes:

After undergoing this article you will be able to understand the following

1. What's Sustainable AI?

2. Why sustainable AI is necessary?

3. What features should exist in Sustainable AI?

4. What's the elements of sustainable AI?

5. Where is Sustainable AI be  applied?

6. What's the advantages of sustainable AI?

7. What's the Limitations of sustainable AI?

8. Strategies for implementing sustainable AI

9. Conclusions

10. FAQs

References

1. What's Sustainable AI?

Sustainable AI refers to creating and using trustworthy AI systems that deliver long-term benefit to business, people, and the planet. Sustainable AI methods aim to ensure ethical and responsible use of AI through increased awareness and management of the risks and impacts of AI systems.

2. Why sustainable AI is necessary?

On digging deeper, we understand the impact it has on various areas such as the environment, economy and ultimately our lives.

a. Environmental Impact: AI technologies, while powerful, can be energy-intensive during training and operation. Training an AI model requires a huge amount of energy; sometimes even as high as lifetime average of five American cars: this is just an example of where we can be more considerate with our resources.

By adopting sustainable AI practices, organizations can reduce their carbon footprint, optimize energy consumption, and contribute to a greener future.

b. Social Impact: The deployment of AI can inadvertently perpetuate biases and social inequalities. Sustainable AI fosters inclusivity by prioritizing fairness, equity, and diversity in data collection, model training, and decision-making processes.

c. Economic Impact: A recent study suggested that employing sustainable AI practices can contribute upto $5.2 Trillion in global economy by 2030. Embracing sustainable AI not only safeguards an organization’s reputation but also minimizes legal and financial risks.

By avoiding unethical practices and negative consequences, businesses can ensure long-term growth and sustainability.

d. Ethical Considerations: Unchecked AI development can lead to ethical dilemmas, ranging from privacy breaches to the loss of human agency. Sustainable AI entails ethical decision-making throughout the AI product lifecycle, ensuring that technology respects human values and rights.

3. What features should exist in Sustainable AI?

AI uses multiple technologies that equip machines to sense, comprehend, plan, act, and learn with human-like levels of intelligence. Fundamentally, AI systems perceive environments, recognize objects, contribute to decision making, solve complex problems, learn from past experiences, and imitate patterns.

These are the features of AI that make it unique:

• Eliminate dull and boring tasks
• Data ingestion
• Imitates human cognition
• Futuristic
• Prevent natural disasters
• Facial Recognition and Chatbots

Similarly, the features of sustainable AI must carry above unique characteristics.

4. What's the elements of sustainable AI?

AI tech consists of four main components — learning, reasoning and decision making, problem solving, and perceptions.

Sustainable intelligence is defined as individuals' ability to apply their knowledge and experience to demonstrate pro- environmental behavior toward sustainable tourism

Sustainable AI work includes building appropriately measures for transparency, security, accountability, and auditability of AI systems while ensuring that their intended benefits are realised.

Sustainable AI, most commonly known as 'Green AI' or 'Eco-friendly AI', what refers to the practice of developing and deploying AI technologies in a manner that minimizes their environmental impact and maximizes their long-term sustainability.

5. Where is Sustainable AI be  applied?

AI technologies can help with sustainable building design, precision agriculture, air pollution and even in reducing climate warming vapour trails. Yet AI systems have the tendency to consume a lot of energy themselves.

The application of sustainable AI is as follows

1. Data analysis for sustainability

2. Sustainable agriculture

3. Preparedness for natural disasters

4. Biodiversity monitoring

5. Fighting air pollution

6. Less defective production

7. Better leak detection in production

8. Reduced energy consumption

9. Safer workplace

10. Optimized and sustainable logistics

6. What's the advantages of sustainable AI?

The advantages of sustainable AI are as follows

• 24/7 availability. One of AI's biggest, and most cited, advantages is its 24/7 availability. ...
• Scalability. ...
• Improved accuracy and reduced rate of error. ...
• Enhanced safety. ...
• Performs mundane and repetitive tasks.
• Zero Risks

7. What's the Limitations of sustainable AI?

The lack of clarity in AI's decision-making process makes it challenging to identify errors or anticipate how the artificial intelligence will perform with new data. This uncertainty complicates efforts to improve or adapt AI systems for various applications, which limits their potential benefits.

The top 6 limitations of AI are

• Lacks Creativity. AI systems are excellent at pattern recognition and can generate solutions based on past data. ...
• High Costs. ...
• Amplify Biases. ...
• Requires Monitoring. ...
• Limited Understanding of Context. ...
• Job Displacement. ...

8. Strategies for implementing sustainable AI

So, it’s vital for you to design, develop, deploy, and use AI sustainably.Explore five strategies for achieving sustainable AI.

1. Use renewable energy sources

AI requires a significant amount of energy to process data and train algorithms. As a result, it is essential for you to use renewable energy sources, such as solar or wind power, to reduce your carbon footprint.

2. Consider the entire lifecycle of AI systems

It’s crucial to consider the entire AI lifecycle, from development to decommissioning.

AI models require continuous training and updating, generating a significant amount of data and consuming energy. You can reduce their environmental impact by using efficient algorithms, compressing data, and recycling old hardware. Practically, you could do so by:

• researching the most efficient means for sourcing and managing data;
• requiring your third-party developers to make sustainability part of their development process; and
• engaging with hardware providers that have a programme for recycling unusable hardware.

3. Prioritise ethical AI

 Sustainability is not just about the environment but also about social responsibility. It means prioritising ethical AI to ensure your AI systems are fair, transparent, and unbiased.

By taking this approach, you can avoid negative social and environmental impacts that may arise from AI systems.

4. Develop beneficial AI

Sustainable AI requires you to develop AI systems that benefit society.

You can use AI to address some of the world’s most significant environmental and social challenges. For example, you could use AI to optimise energy usage, reduce waste, and improve sustainability in supply chains. 

5. Cultivate collaboration

Collaboration is essential to achieving sustainable AI. Ideally, it would be best if you collaborated with other organisations, research institutions, and governments to share best practices and develop new solutions. By working together, you can contribute to AI that will benefit current and future generations.

9. Conclusions

Artificial intelligence (AI) has a tremendous potential to accelerate organizations’ sustainable transformation journeys and create business value. AI can help automate ESG data collection and increase the accuracy of reporting, improve operational efficiencies and anticipate and respond to supply chain risks.

10. FAQs

What is Green AI for sustainable development?

Ans.

Green AI represents a promising alternative to integrate sustainability aspects into the development of AI processes and applications without neglecting economic interests. The term "Green AI" refers to AI research that aims to reduce environmental impact by using resources more efficiently

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