In the following analysis, George Crowdy, Sustainable Fund Manager, Royal London Asset Management, explains why although still in its infancy, artificial intelligence (AI), is already transforming industries.
However, there are growing concerns about some of the ethical implications of generative AI in particular. This is different to previous technological shifts because humans will have much less of a role in the output that it produces. That comes with risks, and our role as investors, along with the wider industry, is to ensure that companies are innovating in a responsible and sustainable way.
This means ensuring that product development processes have strong governance from a broad selection of people with different backgrounds, to guard against inherent biases in the way generative AI produces responses and outcomes.
Because we are in such an early stage of AI growth, a lot of responsibility is being placed in the hands of a relatively small number of companies that have the capability to develop products at scale.
Even before generative AI, there was a real challenge determining what was genuine and what was fake content. Generative AI will clearly make it even more difficult for end users to distinguish.
The World Benchmarking Alliance’s (WBA) Collective Impact Coalition for Digital inclusion illustrated that the 2023 Digital Inclusion Benchmark showed that only 44 out of 200 digital technology companies disclosed the principles they follow in the development, deployment, and/or procurement of ethical AI tools. As signatories of the WBA’s Investor statement on Ethical AI, this gives us cause for concern.
It came as no surprise that in 2024 the importance of AI resolutions at Annual General Meetings has surged, reflecting AI’s growing impact on business operations and governance. As AI technologies rapidly advance, such resolutions can help ensure that businesses leverage these technologies ethically, sustainably, and strategically.
By mandating clear guidelines and oversight mechanisms, these resolutions can prevent misuse, such as bias in algorithms or invasion of privacy.
Given the pace of change, regulation will struggle to keep up with the new technological shifts, therefore we want to see companies setting standards and guardrails to ensure that outcomes are as responsible as possible.
We also want to see companies innovating to reduce the resource dependency of their products and product ranges using fewer resources but doing more.
One example of this is Adobe working on text-to-image and text-to-video generation. There is a huge risk of inherent bias in this area. If you prompt AI to show you a picture of a doctor, you don’t necessarily want to be presented with a picture of a man in a white coat.
The way Adobe has handled this is to use its own library of stock images to train its AI – unlike other text-to-image models, which are often simply ‘scraping’ the internet for content. This gives Adobe a genuine competitive advantage because its customers know the models are being developed responsibly.
When it comes to enablers like software company Nvidia, one of the key sustainability issues is around the resources needed to produce computing advancements. Making chips is hugely resource-intensive from an energy and water perspective. The vast majority of advanced semiconductor chips are produced in Taiwan, which is a water-constrained region.
Here we want to see companies innovating to reduce the resource dependency of their products. We want to see a company’s next product range using fewer resources but doing more. Nvidia’s latest semiconductor chip provides up to a 30X performance increase and reduces cost and energy consumption by up to 25X versus its predecessor for inference workloads.
There are many ways to sustainably play the AI theme. Hundreds of billions will be spent on building data centres over the coming years and making these environmentally friendly will be hugely important. Any industry that has manual repetitive tasks that involve data – for example, the banking industry – could be huge beneficiaries. If you’re not doing smart things with data when it comes to assessing people for credit in the banking industry, you will quickly be left behind.
Importantly, sustainable investors can push companies to integrate AI in ways that enhance efficiency and innovation while mitigating risks. This proactive approach can lead to competitive advantages, such as improved decision-making processes, streamlined operations, and better customer experiences.
We believe it’s incumbent on investors to drive responsible AI development and enhance corporate governance to position companies for sustainable growth in a technology-centric future.
