In the following analysis, George Crowdy, Sustainable Fund Manager, Royal London Asset Managementt, explains why, although still in its infancy, artificial intelligence (AI) is already transforming industries.
However, there are growing concerns about the ethical implications of generative AI. This technological evolution is different from previous ones, as humans will play a much smaller role in the outcomes it produces. This carries risks, and our role as investors, as well as that of the industry as a whole, is to ensure that companies innovate responsibly and sustainably.
This means ensuring that product development processes have strong governance, driven by a broad range of people from different backgrounds, to guard against biases inherent in how generative AI produces responses and outcomes.
Given that we are at an early stage of AI growth, much of the responsibility is placed in the hands of a relatively small number of companies that have the capacity to develop products at scale.
Even before generative AI, it was already difficult to distinguish authentic content from fake content. Generative AI will clearly make the distinction even more difficult for end users.
The World Benchmarking Alliance (WBA) Collective Impact Coalition for Digital Inclusion has shown that the Digital Inclusion Benchmark 2023 found that only 44 out of 200 digital technology companies have disclosed the principles they follow in developing, deploying and/or procuring ethical AI tools. As signatories to the WBA Investor Statement on Ethical AI, this concerns us.
It is no surprise that in 2024, the importance of AI-related resolutions at annual general meetings has increased, reflecting the growing impact of AI on corporate operations and governance. As AI technologies advance rapidly, such resolutions can help ensure that companies operate these technologies ethically, sustainably and strategically.
By imposing clear guidelines and oversight mechanisms, these resolutions can prevent abuses, such as bias in algorithms or invasion of privacy.
Given the pace of change, regulation will struggle to keep up with new technological developments. That’s why we want to see companies establish standards and safeguards to ensure outcomes are as responsible as possible.
We also want to see companies innovate to reduce the resource dependency of their products and product lines by using fewer resources but doing more.
For example, Adobe is working on generating text in images and text in videos. The inherent risk of bias in this area is enormous. If you ask AI to show you a photo of a doctor, you don’t necessarily want to see a photo of a man in a white coat.
Adobe has addressed this by using its own image library to train its AI, unlike other text-to-image models, which often simply “scrape” content from the internet. This gives Adobe a real competitive advantage because its customers know that the models are developed responsibly.
For companies like Nvidia, one of the biggest sustainability issues is the resources needed to produce new computing technologies. Chip manufacturing is a resource-intensive business, both in terms of energy and water. The vast majority of advanced semiconductor chips are produced in Taiwan, a region with limited water resources.
We want to see companies innovate to reduce the resource dependency of their products. We want to see a company’s next product line use fewer resources but do more. Nvidia’s latest semiconductor chip delivers up to a 30x performance increase and reduces cost and power consumption by up to 25x compared to its predecessor for inference workloads.
There are many ways to play sustainably on the AI theme. Hundreds of billions will be spent on building data centers in the coming years and it will be extremely important to make them environmentally friendly. Any sector that performs repetitive manual tasks involving data – for example, banking – could benefit enormously. If you don’t use data intelligently when it comes to assessing people for credit in banking, you will quickly be left behind.
It is important for sustainable investors to be able to incentivize companies to integrate AI in ways that improve 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 is up to investors to drive responsible AI development and improve corporate governance to position companies for sustainable growth in a technology-centric future.
