As I write this, two contrasting regulations on the development of artificial intelligence — namely generative AI — are making their way through the European and British parliaments. The British approach is very simple — looking to ensure AI companies fit into existing laws governing technology companies.
In contrast, the EU approach, as White & Case analysis describes, is an entirely new piece of legislation, and is risk-based — looking to counter the most serious risks that come with developing more advanced AI. Whether that is data scraping, infringements on individual liberty, as well as fake news and election involvement.
There will be other opportunities to do this, for example with future funding programmes, but there is little to highlight an EU push for the advancement of AI and its positive use cases. In fact, former MEP Marietje Schaake is already calling for an AI tax based on the perceived risk of future job losses and economic disruption.
Safeguarding AI innovation along with democracy
In a year when most of the world’s democracies have a major election — including the US, likely the UK, France, Germany, and India — it’s critical that we ensure AI doesn’t have the type of negative impact that bots and fake news had on elections in 2016.
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But, it’s also critical that we have a meaningful discussion about how we can harness AI for good — namely, to help speed up our response to the climate crisis. At World Fund, we’re particularly excited about AI’s climate applications, and have already made two investments in the space and another we will soon disclose.
Why? Well, for the most part, solving the climate crisis will come from significant investments in deeptech, hardware, and fundamentally new technologies. This is why we’ve been busy raising a larger first-time fund, with the ability to back deeptech and hardware startups like IQM, next-gen battery-recycling company cylib, and many more.
From deeptech to software stacks
But, software will also play a role in solving the climate crisis, quickly and potentially cheaply. AI can fundamentally make quick changes to how we use energy resources across industry, highlighting inefficient use and quickly — without human input. That’s why we invested in Cologne-based aedifion, which helps the built sector reduce energy consumption and CO2 emissions.
Across biotech and biochemical industries, AI can accelerate research into cell-free alternatives to fossil fuels. In biodiversity terms, AI will also help us better understand wildfire trends — and help us protect the natural world through enhanced weather modelling. It can also help us understand and reduce waste in our supermarkets by more effectively understanding consumer buying trends — that’s why we invested in Berlin-based Freshflow.
At a political level, we’d like to see some understanding that there can and should be a positive correlation between the development of AI and adopting some of its use cases in our response to the climate crisis. The risk-based approach, which the EU is currently spearheading, needs softening in due course so we can start this more positive discussion.
This will come in the form of initial public debate, then parliamentary debate, regulatory amendments to the broader AI bills being debated at present, and later down the line, the building of AI into climate policy — and with it, climate investment packages.
This should — hopefully — lead to meaningful AI that helps us optimise existing industrial and economic structures, so they have a drastically reduced climate impact. The development of this wave of artificial intelligence is still in its infancy, but to get climate impact from AI, we need to start talking about how we can positively make use of this new technology, too.