AI and ESG: a new frontier for financial innovation?
Discover a fascinating debate between two Artificial Intelligence experts: Dr Luc Julia and Dr Carmine de Franco
ESG data is hard to exploit. Analysts outperform AI if they are only looking at a few dozen firms. But the algorithm does better once we start talking about thousands of firms."
|Dr Luc Julia
Senior Vice-President of Innovation, at Samsung, and co-founder of voicecontrolled digital assistant, Siri, has worked at MIT, the CNRS and for Apple and Samsung.
|Dr Carmine de Franco
Scientist by education and heads fundamental and ESG research at Ossiam
What is AI?
In truth, AI is just maths, logic and statistics. It allows us to build high-performance tools that will help people achieve great things: making daily life easier for everyone, improving their productive capacity. This intelligence is systematically controlled by people and can be used in any field. And this has been happening since the dawn of time.
Machine learning is one class of predictive models within the AI family. It concerns algorithms that, fed with a series of similar cases (in the form of datasets), can then extrapolate on their own a number of predictions by first identifying the structures and relationships embedded within their learning data.
The key to these systems is recognition of knowledge. To work efficiently, machine learning needs a lot of data, which also has to be high-quality so as not to bias future results. AI has come a long way in visual and voice recognition but still has its limits. This is where it differs from human intelligence. AI is discrete and specific. It invents nothing and can only do a defined task. Human intelligence is superior - diverse, complex and flexible.
To fix this, we made the algorithm more human, giving it the feel of talking to a real person. If you like, we added a bit of artificial stupidity. So, when Siri didn't understand, it responded with a joke.
How far can AI take us as human beings?
What is the environmental impact of AI?
What can AI do for finance?
AI, in contrast, means we do not have to define systematic ‘rules’, as it can pick out these rules, or patterns, autonomously based on its learning. Given the size of the databases now available, AI means we will be able, by cross-referencing data, to identify links that would be hard for a human to spot between various data sources and the behaviour of financial assets. Correlations can emerge. But algorithms also have their own biases, deriving from the choice of data they use to learn.
LJ: That's true. Microsoft's Tay chatbot, which was able to interact via Twitter, was taken offline less than 24 hours after launch, when it started tweeting sexist and racist comments. It turned out the algorithm had been primed with data from conversations happening in the southern states of the US during the 60s. It is hard to find high-quality annotated conversational data.
CdF: You educate an algorithm like a child. You have to feed it high-quality data so it can ’learn’ on its own.
Why is AI better than a human when analysing ESG data?
ESG data is hard to exploit. Analysts outperform AI if they are only looking at a few dozen firms. But the algorithm does better once we start talking about thousands of firms. For instance, an algorithm can identify that a certain ESG profile is often linked to a specific financial behaviour (eg performance) and can then segment stocks by profile type. Machine learning incorporates this profile and others on different ESG issues to create something like a panel of virtual experts, able to determine whether an investment is a risk or an opportunity.
Machine learning applies ex ante rules and observes patterns. At Ossiam, we restrict the space that machine learning can explore. We build in filters via a systematic allocation that allows for the risk that the selection will ultimately happen. So the human being remains in control.
Do you look at the future with optimism or pessimism?
People will not be replaced by a machine. Ever. We will always have experts. Some specific tasks will be replaced. And new jobs will be created around these new technologies, as has happened since the dawn of time.
This communication is for information only and is intended for investment service providers or other Professional Clients. The analyses and opinions referenced herein represent the subjective views of the author as referenced unless stated otherwise and are subject to change. There can be no assurance that developments will transpire as may be forecasted in this material.
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