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Artificial Intelligence and Sustainability: AI4Good or AI4Bad?

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Artificial Intelligence and Sustainability: AI4Good or AI4Bad?

Leading with AI
Dec 2, 2021
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Artificial Intelligence and Sustainability: AI4Good or AI4Bad?

leadingwithai.substack.com

By Hasna Abdelwahab*

How often do we link terms like data science, artificial intelligence (AI), and machine learning with futuristic advancement, such as highly sophisticated robots and space ships as public transport?

Why do we not associate them with a greener area, cleaner air, or flourishing biodiversity?

Fourth Industrial Revolution technologies such as AI are enabling humanity to harness information and data to revolutionise education, energy, healthcare, agriculture, transportation, and many other service areas. AI helps us makes the world a better place, from traffic management in urban mobility to enhancing the efficiency of renewable energies to predict crop needs and other innovative solutions in smart agriculture. AI is becoming a key tool for facilitating a circular economy and building smart cities that use their resources efficiently.

Linking AI with the Sustainable Development Goals (SDGs) contributes to design for a healthier planet, addressing current needs without compromising future generations due to climate change or other major challenges. According to a study published in Nature (2020) AI could help achieve 79% of SDGs, indicating that AI may act as an enabler on 134 targets across all SDGs, generally through a technological improvement, which may allow to overcome certain present limitations.

However, driving a positive change with AI could also have a negative impact on the three pillars of sustainable development (society, economy, and environment). Starting with the environment, the climate impact of AI was noticed in machine learning (ML) programmes that require increasing energy power and that favour accuracy over efficiency, resulting in big experiments that often run without attention to their digital carbon footprints.

A well-known study by Emma Strubell, Ananya Ganesh, and Andrew McCallum (2019) illustrated that the process of training a single, deep learning, natural language processing (NLP) model can lead to approximately 300,000 kg of carbon dioxide emissions. This is the same amount of carbon dioxide emissions produced by five cars over the cars’ lifetime. Land exploitation is also an issue, including metal extraction and e-waste that result from the need to collect, store, analyse all that data, requiring significant amounts of processing power and an increase in energy consumption.

The use of AI across sectors is expected to increase the global GDP up to 14% in 2030. Although AI is seen as an engine for development and economic growth, AI might lead to widening gap between developed and developing countries, causing more negative economic impacts. Unemployment is a great concern for humanity as robots replace people and new production processes that no longer need humans change the labour market, redefine jobs, and lead to greater inequality.

AI has a long way to go when it comes to global regulations and public policies, as there are no international laws that regulate the recent technology. A lack of governance over AI is one of the reasons that AI is bias. Who builds the AI, and who develops intentional-biased algorithms? Seventy-five percent of all new digital innovation and patents are produced by just 200 firms from the West. Out of the 15 biggest digital platforms people use, 11 are from the United States and the rest are Chinese.

The lack of gender, racial, and ethnic diversity in the AI workforce is one of the reasons AI is bias. The injustice of inequality and lack of inclusion in datasets is another problem.

Sustainable AI requires more effort when it comes to the triple bottom line of people, planet and profit to achieve sustainable development. Harnessing the technological advancement for the greater good has to be carefully addressed and wisely progressed, so that the Fourth Industrial Revolution will not be the last.

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*Hasna Abdelwahab is a young sustainability and social impact professional who has led private sector entities to impactful community development projects as well as introduced the concept of corporate sustainability in few operations. She worked in DAL Group, MTN, Haggar Group & Morouj Commodities. She has implemented hundreds of social responsibility projects and worked to remodel the concept of CSR from charitable giving to sustainable Impact. She is also a climate change activist, taking part in various international platforms such as conferences and panels. Hasna holds a masters degree in renewable energy.

Hasna is an active member in Sudan Environmental Forum, and he Global Shapers Community. She also served as coordinator in the IEEE, organiser in TEDx and Coordinator in SDG Hub.

As a communication enthusiast, she writes for newspapers and magazines on issues of interest.

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Artificial Intelligence and Sustainability: AI4Good or AI4Bad?

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