Artificial Intelligence and Sustainability

A powerful tool we have to use more

The climate catastrophe is the greatest challenge facing humanity. But it is not enough to focus on solutions for this challenge alone.

We must achieve sustainable development.

Therefore the UN has defined 17 sustainability goals [1].

 

These go from the fight against hunger and poverty to health , education and equality to the preservation of our environment and nature and the fight against climate catastrophe. For all topics there are concrete goals to be achieved by 2030. The issues are interconnected and the complexity is high. Decisions in one area can result in positive or negative changes in other areas
Only if we keep all the goals in mind and address them successfully do we have a chance of a Sustainable Future for humanity.

AI will (have to) play a crucial role in this. Complex questions with lots of data are ideal conditions for the use of AI. There is more than enough of that here.

But AI is also part of the problem. By consuming energy in the development and use of AI. By using AI solutions with negative consequences for sustainability goals.

We need to look at both sides.

It’s clear to me that AI is much more of a solution than a problem. If we use AI technologies and are aware of the possible negative sides – and actively address this. The negative aspects will be looked at in more detail in a next post

This post is about the opportunities AI offers us today.
About examples of how AI can contribute to sustainability.
About how this is seen and applied (or not) in business.
And about the question of what we can do personally to make better use of AI’s possibilities.

How can AI help? Some examples.

There are many areas where AI is making a positive contribution to sustainability goals.

Some examples:

• Creating Global Transparency of Greenhouse Gas Emissions (https://www.climatetrace.org/).
• An early warning system to help farmers in Africa avoid the next plague of locusts (https://www.selinawamucii.com/kuzi/)
• Monitoring deforestation in the Amazon (https://www.maaproject.org/en/)
• A solution to the problem of lack of access to health care for half the world’s population (https://unimadx.com/findtb)
• Increasing the effectiveness of social spending (https://kimetrica.com/)

There are many other examples. Optimizing transportation and logistics, better diagnosing diseases and developing effective therapies and medicines, optimizing energy consumption and energy extraction.

The International Research Centre in Artificial Intelligence under the auspices of UNESCO (IRCAI) [2] has compiled a list of 100 particularly noteworthy examples of the use of artificial intelligence for sustainable development and for the benefit of humanity.

Examples for all UN SDG goals can be found here

IRCAI Global Top 100 Results

The World Economic Forum sees AI as a critical factor in the race to achieve the SDGs [3].

What is industry doing?

In industry, the topic of sustainability is becoming increasingly important

In a survey conducted by McKinsey at the end of 2021 [4], forty percent of expert respondents expect corporate sustainability programs to add value in the next five years – nearly twice as many as today.

Source: McKinsey

 

Sustainability is playing an increasingly important role in the quarterly reports of publicly traded companies. This is shown by statistics from GlobalData for Q1 2022 [5]

Source: InvestmentMonitor

 

In the new report from BCG and the AI for the Planet Initiative [6] on “How can AI be a Powerful Tool in the Fight against Climate Change” [7], 87% of respondents say AI can be a very helpful tool. However, only 43% of the organizations have an idea of how they can use AI. In Germany it is even only 30%.

 

Why we don’t yet use AI to the extent possible.

The survey [7] identifies 3 key reasons:

• Insufficient access to AI knowledge and experts inside or outside the organization
• Limited availability of AI solutions and products
• Lack of confidence in AI data and analytics.

 

In addition, from my point of view, in the industrialized countries, especially in Europe but also in the USA, there are the following additional reasons

• Skepticism in the population, the knowledge about AI is still limited to a small group.
• Access to data is often not available to develop AI solutions (examples health)
• Transfer of scientific knowledge into commercial solutions takes too long and is too complicated
• the few experts are often used for commercially successful but unsustainable developments (example social media consumption)

 

BCG shows in the study [7] an interesting framework for using AI to fight the climate crisis. This can be used for the topic of sustainability and can be used as a basis for discussions in and with companies.