Innovative private sector solutions will be important in addressing challenges such as ageing populations in a way that helps reduce the burden on public purses. Products and services that enable better societal outcomes at a lower cost can benefit from long‑term structural drivers of demand and grow across economic cycles.
In this article [1], Impax Asset Management, a delegated manager of BNP Paribas Asset Management, discusses three areas that illustrate such opportunities and points out that artificial intelligence can accelerate the transition to a sustainable economy.
- Growing emphasis on wellbeing and quality of life
Technology that enables people to take better care of themselves from fitness centres to over‑the‑counter medicines can improve health outcomes and help prevent burdening healthcare systems. Self‑care products and associated services can avoid an estimated USD 119 billion in global healthcare costs each year and deliver 41 billion days in gained productivity.
- Better access to finance
Especially in emerging markets, access to solutions such as simple accounts and loans can remove barriers to opportunity. Life insurance can protect workers from unforeseen circumstances and retirement solutions can help them save for their futures. Population ageing and the growing middle class in emerging markets provide tailwinds for innovative solutions in this sector.
- Advancing more inclusive careers
Digital technologies are enabling high-quality, personalised learning and recruitment services that connect people with the skills and professional roles they aspire to. Affordable childcare solutions help overcome barriers to returning to work.
AI can accelerate the sustainability transition
The efficiencies that technological advances are unlocking could transform whole sectors and ways of work — possibly even ways of life. Regulation will be needed to manage risks, but the opportunities for AI to address environmental and social challenges should be harnessed.
We are particularly interested in AI’s potential to enable new and improved solutions to pressing challenges. Considering environmental solutions first, there are three areas where we perceive opportunities for progress.
- AI has been leveraged to accelerate and improve the development of environmental technologies. For example, a major wind turbine maker is using an AI‑driven system to improve wind farm design and maximise clean electricity generation. The ability to predict the structures of new materials could unlock innovation in areas including batteries and semiconductors.
- AI is being used to optimise the efficiency of energy‑intensive sectors such as building and transport, reducing greenhouse gas emissions. Networks of connected sensors already help adjust buildings’ heating, ventilation, and air conditioning (HVAC) systems and lighting. AI modelling can predict how energy may be used, reducing waste.
- AI models have surpassed the ability of supercomputers to accurately predict the weather. Better weather forecasts can help agricultural output and, in extreme cases, save lives.
Extrapolating from this, AI could be used to help predict the physical impacts of climate change more robustly, and so guide better decisions on climate adaptation‑related investments.
AI as a solution
AI is already being applied to improve the accuracy of cancer diagnosis and predict different forms of cancer using genetic data and samples. For example, an algorithm that studied tissue imaging and genetic changes achieved a 97% accuracy rate in diagnosing lung cancer, versus 83% for previous leading computational methods.
Drugmakers are leveraging AI to speed up the drug development process as more accurate simulation and more precise patient identification should enable success or failure of drug trials much more quickly.
More broadly, AI is already demonstrating its capacity to improve productivity in the workplace. A leading software maker’s tool can automate tasks such as email writing and slideshow creation and speed up tasks including research and writing.
Challenges and environmental implications
The risks arising from disinformation and deepfakes are real. AI products can incorporate many sources of bias and discrimination, and distort information, with real‑world societal consequences.
Concerns that AI could lead to mass redundancies also have some credibility: unlike previous technological revolutions, AI may displace workers beyond manual, labour‑intensive tasks.
The environmental implications of the AI revolution — arising from the energy intensity of complex computation — are more manageable. Powering and cooling the servers and other hardware used in datacentres consumed 0.9% to 1.3% of global electricity in 2021.
Energy use will rise with the capabilities and complexity of AI models, but energy efficiency solutions — from better‑designed chips to systems management — should keep a lid on energy needs, and so emissions. Indeed, AI models are themselves being employed to optimise energy management in datacentres.
References
1 This is an extract from Outlook 2024 – Why prospects for a more sustainable economy remain undimmed.
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