Artificial Intelligence can be looked upon as a tool (but remember: a fool with a tool is still a fool!) or as a totally new technology that like wheel, steam engine, electricity and internet will lift mankind to the next level. If the latter is right, what can AI do to mitigate our climate crisis, to speed up renewable energy, foster a cradle-to-cradle economy and replace harmful materials like plastics?
There exist numerous scientific efforts and competitions to reach the 17 SDGs. But the basis for many solutions is data. To turn big data from thousands of sources into smart data we definitely need AI in all of its variants: Machine Learning and – soon to come – General AI combined with quantum computing.
These self-learning machines with an incredible calculation power and velocity will be able to fulfil tasks of the complexest manner within minutes for what we would need years nowadays.
To find a vaccine against a formerly unknown virus would not need 9 months but – with all human tests and possible side effects and their probabilities already simulated – just a few days.
To replace harmful material means in many cases to get rid of the existing harmful ones by granulating them into their raw materials for recycling or downcycling. To combine the knots logistically to assure the right materials in the needed quality with the correct volume at the right time is also a great task for AI – perfectly informed by tracing sensors and marker molecules.
To monitor climate change myriads of data from satellites, wheather stations, ships, airplanes etc. must be collected and fed into complex simulation models to predict global and regional impacts. Here also AI can do a good job, even if it is mostly pattern comparison what is done today.
But to foster renewable energy in the most efficient way also AI is needed and useful: „The primary goal of AI integrated systems is to minimize the forecasting challenges and efficiently integrate renewable energy into the central energy grid. AI can also help renewable energy suppliers to design effective strategies and policies around current energy consumption and demands.“1)
In any case humans should remain in the loop here to monitor the results and act upon them. This is the big underlying demand of all ethic guidelines, especially the EU ethical guidelines by the HLEG (High Level Expert Group) on Artificial Intelligence, published in 2020.2)
Autonomy is of course the big challenge for our future cars. But the infrastructure to guarantee seemless Car2X communication has not been established, apart from a sufficient net of loading stations for electric vehicles. One of the preliminaries for the introduction of autonomous cars was the promise of zero casualties from accidents. Therefore, the day is coming where all individual driving (in a car with a man-handled steering wheel) will be forbidden because these racers in their unpredictability would endanger all smart drivers/passengers in their level 5 autonomous vehicles.
But back to our topic of sustainability. Without a mind shift in the decision makers heads in politics and economy, but also in consumption, a real change for the better cannot be reached. Billions of Euros/Dollars/Rinminbi/Yen are necessary to even keep the 1,5 degrees until 2050 and the window of opportunity is closing. AI can only deliver decision basics in shape of measured facts, simulations and predictions – all decision makers must act, officially and privately, accordingly.
For further reading:
https://www.brandeins.de/magazine/brand-eins-thema/it-dienstleister-2021/eine-geschichte-aus-europa
https://www.nasdaq.com/articles/big-tech-is-big-on-esg-2020-12-10
https://www.climate-kic.org/opinion/ai-and-climate-change-the-promise-the-perils-and-pillars-for-action/
https://algorithmwatch.org/jahresrueckblick-2020/
© Thomas Andersen
Thomas Andersen is a startup consultant since 2004 with a background of Sales and Marketing Management in the FMCG industry. He is a lecturer in two Berlin universities and a member of the German Standardization Association where he is engaged in the AI working group. He consults talenteco since 2017 and is an ardent networker.