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If history is any guide, AI, like other general purpose technologies, is set to unleash waves of wealth creation, resource reallocation, and societal change. These are unpredictable in shape and speed, but as investors and custodians we can, and must, seek to guide them in the long-term interests of our clients and broader society. This is the essence of sustainability. In this report, we look at AI’s consequences for society through its effects on education, workplace productivity, and health.
AI can augment human capital through multiple, mutually reinforcing channels. This starts with great education, where AI can help to provide tailored learning for students and support for teachers. In the job market, about 40% of roles are highly exposed to AI. Some will be helped to become more productive, others are more likely to face automation. Lastly, healthcare, where AI has already been incorporated in many ways, but major improvements in delivery, diagnostics, drug discovery, and disease prevention are still to come.
Maximizing the gains from AI requires addressing the challenges that accompany its roll-out. These range from bias and explainability issues to concerns about privacy and safety. Risks of inaccuracy and low performance, and, just as importantly, from regulators and public backlash, are all likely to be higher in companies that are not taking proactive measures to optimize AI oversight and mitigate potential impacts.
AI should not be thought of as a discrete, stand-alone breakthrough. It is rather a catch-all term for a technology supercluster. Just as “the internet” is a combination of various innovations, from fiber-optic cables to search engines, so AI comprises many interdependent technologies that facilitate and amplify each other.
These combine to form the front-end that most of us will experience via consumer technologies like OpenAI’s Chat-GPT and the back-end underpinning of various services and infrastructure, from personalized medicine to smart power grids.
Simplified, non-exhaustive representation of the technological foundations which enable different forms of AI:
Source: UBS
A discussion on the social risk and opportunities in the AI-transition.
Richard Mylles talks about the social implications of the AI-transition with a particular focus on the opportunities and risks in education, work, and healthcare.
As the AI roll-out gathers pace, we find ourselves at an inflection point. The decisions taken in the next few years will decide whether AI's upsides are fully realized and its risks adequately mitigated.
Our white paper contains insights on how to optimize AI’s consequences for human capital, via its impacts on education, workplace productivity, and health.
AI needs data to keep on improving, but the supply is vulnerable to disruption. There is an imbalance of benefits between the companies who monetize data and the rest of society who produces it, which needs addressing.
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