The Ultimate Question: What is AI and Can it be Sustainable?

According to the Lawrence Livermore National Laboratory which is backed by the US Department of Energy, the concept of Artificial Intelligence (AI) was first posed in the 1950s by English mathematician and computer science pioneer, Alan Turing.

Since the 1950s, AI has adapted and derived into many different concepts, all of which pose skills for alternative methods.

So, what actually is AI?

The history of AI

According to a timeline from IBM, the foundation of AI was laid in the 1950s

AI was created to be “Human intelligence exhibited by machines”, linking heavily to Turing’s vision.

In the 1980s, AI developed into machine learning. This is when AI systems began to incorporate historical data and the knowledge or databases behind them expanded.

In 1997, IBM’s Deep Blue defeated the world chess champion at the time, Garry Kasparov, creating a huge milestone for AI, according to Amazon Web Services (AWS).

The 2010s saw AI delve into deep learning, when AI models started to mimic human brain function and become less robotic.

Today’s AI models are known as generative AI models, incorporating deep learning models to create human-like original content.

“In 2022, chatbots that use AI and natural language processing (NLP) to have human-like conversations and complete tasks like OpenAI's ChatGPT became widely known for its conversational abilities, further boosting AI interest and development,” says AWS.

What is AI? According to Google Cloud

AI is a collection of technologies that allow computers to perform complex tasks such as recognising images, understanding and translating language, analysing data and generating recommendations.

It underpins much of today’s digital innovation, creating value for both individuals and businesses.

A practical example is optical character recognition (OCR), which applies AI to extract text and data from images and documents, converting unstructured content into structured information that can deliver meaningful insights.

AI is the science of developing computers and machines that can reason, learn and act in ways that usually require human intelligence, or process data at a scale beyond human capability.

It is a wide-ranging field that draws on disciplines such as: 

• Computer science
• Data analytics
• Statistics
• Engineering
• Linguistics
• Neuroscience
• Philosophy
• Psychology

In business, AI is applied through technologies based largely on machine learning and deep learning. 

These are used for tasks including data analysis, prediction and forecasting, object recognition, natural language processing, personalised recommendations and intelligent information retrieval.

Google Cloud explains how AI works

Although AI techniques differ, they all share a common foundation in data. 

By processing large datasets, AI systems learn, adapt and uncover patterns or connections that may escape human analysis.

At the heart of this process are algorithms, sets of rules or instructions that direct how data is analysed and how decisions are made. 

In machine learning, a leading branch of AI, algorithms are trained on labelled or unlabelled data to classify information or generate predictions.

“The future of AI is not about replacing humans, it’s about augmenting human capabilities,” explains Sundar Pichai, CEO of Google.

Deep learning takes this further, using multi-layered artificial neural networks modelled on the human brain to process information. 

With ongoing exposure and refinement, these systems steadily improve, enabling applications such as image recognition, language translation and many others.

What are the negative impacts of AI?

According to Earth.Org, AI is often hailed as transformative, yet its environmental impact is a growing concern. 

The development, maintenance and disposal of AI technologies carry a significant carbon footprint, driven largely by the enormous energy demands of training increasingly complex models, with emissions from the Information and Communications Technology (ICT) industry expected to reach 14% of global totals by 2040. 

Studies show that training large models can emit as much carbon as hundreds of transcontinental flights, while the growing volume of electronic waste adds further risks through toxic materials contaminating ecosystems. 

Beyond emissions and e-waste, AI-driven applications such as autonomous vehicles, drones and intensive agricultural tools can accelerate consumption, degrade biodiversity and raise ethical issues. 

Earth.Org deems there to be a lack of transparency around AI development, limiting accountability and obscuring the true scale of its impact. 

"Addressing these challenges requires energy-efficient hardware and algorithms, responsible design standards, ethical disposal practices and stronger regulation, supported by collaboration between businesses, researchers and policymakers to ensure innovation progresses without compromising environmental sustainability," explains Earth.Org.

Can AI be sustainable?

According to Intel, AI has the potential to be a powerful driver of sustainability when applied responsibly. 

Leading companies are already using AI to shrink their environmental footprint, support decarbonisation and uncover opportunities for efficiency and growth. 

Just as IT was central to digital transformation, AI and technologists now play a pivotal role in sustainable transformation, helping organisations cut the carbon impact of their IT operations and harness technology to reach net zero. 

From optimising supply chains and energy grids to enabling precision agriculture and smarter data centres, AI can accelerate progress towards environmental, social and governance goals while delivering new business value and long-term resilience.