The future of AI in insurance

My view

It's summer 2023, and the insurance industry finds itself in the midst of an emerging topic – Generative AI. It strikes me that AI is now taking center stage, provoking philosophical reflections on what truly differentiates human from machine intelligence. 

The excitement – some might call it hype – surrounding AI is understandable. ChatGPT has provided a good example of the potential capabilities of Generative AI to us all making its impact tangible. However, along with its clear promise, AI has also revealed its weaknesses. This interplay of promise paired with challenges will likely continue moving forward, as this technology evolves.

What I find crucial: the future of AI hinges on the individuals who are developing and using it. It's us humans who must ensure that AI creates value for society, without negative side effects. This truth remains relevant for the current situation, as well as all future scenarios involving AI. Ultimately, AI will only be as good as those people who develop and utilise and the quality of the underlying training data.

Unchanging core purpose

Despite the transformative potential of AI in the re/insurance industry, one constant remains: people's need for risk transfer and mitigation solutions. AI may enable new solutions and business models, but it cannot alter the core mission of our industry. Hopefully, AI will help in closing the protection gap more efficiently.

Part 2 of our series delved into the immense opportunities AI holds for the insurance industry. Currently, the industry is in the early stages of adopting AI, primarily employing narrow AI for specific purposes like automating parts of the underwriting processes without decision making. 

Many large insurance companies are experimenting with large language models (LLMs) such as GPT, though they are not yet fully deploying them. These models can have a significant impact on the re/insurance industry, not only by automating processes, but also by automating tasks such as code generation and analytics.  

I find it very exciting that the rapidly developing abilities to process unstructured data (see graphic below) is opening our eyes to new solutions that will help us to serve our customers better. With enhanced data analytics and predictive capabilities, it will become easier to combine insurance coverage with risk mitigation. More and more AI use cases are emerging in the industry, one recent example is our partnership with CompScience for improved worker safety. 

Shaping the future of AI now

The future of ethical and beneficial AI depends on actions taken today. Full enterprise maturity requires addressing various risks associated with LLMs and Generative AI. 

Swiss Re's latest edition of Sonar, our annual publication that tackles new emerging risks of often existential significance, explores risks of Generative AI relevant for the insurance industry. For example, Generative AI has unresolved intellectual property issues regarding training, its outcome and the creation of "plausible” content. The same goes for data privacy. The collection of the large data sets with the intent of producing something new from that material raises questions around rights to the underlying data, and also concerns about data quality and biases. 

In order to guarantee that AI fulfills its future potential, it is important to actively shape the technology now. As an industry, we have an obligation to drive the development of ethical AI that benefits society, ensuring it aligns with our values and needs. 

As we navigate the immense promise of AI, it is crucial to recognise the pivotal role humans play in harnessing its power so that future generations can benefit from AI applications. 

With AI technology still really only in its infancy, we have an opportunity to forge a path in which AI enhances our work while preserving our core purpose in the ever-evolving world of insurance. 

Antonio Grasso's view

As we move further into the era of generative artificial intelligence (AI), it's important to remember that AI is, at its core, a reflection and amplification of our human thinking. While this sophisticated technology is capable of creating content that appears original, it is fundamentally an echo of our input. It is not an independent entity but a tool we have developed to transform our thoughts, knowledge, and creativity into new forms at a scale and speed far beyond our capabilities.

Navigating the Ethical Landscape of generative AI

Within this premise, essential questions arise around generative AI, encompassing data ownership, quality, potential bias, and misuse. Far from being purely technological, these challenges serve as a mirror that reflects our ongoing societal and ethical struggles. Therefore, our approach to addressing these concerns requires advanced technical solutions and deep introspection about our collective values and guiding principles.

The Illusion of Synthetic Thought

As we navigate this ethical landscape, we encounter the notion of synthetic reasoning, which is often attributed to AI. It's important to understand that what may appear to be synthetic thinking is actually a reconfigured version of our human reasoning, shaped by the training data we provide. AI doesn't create knowledge; it reshapes and remixes the human knowledge it's trained on. It's our thoughts, amplified and modified by algorithmic patterns.

Harnessing the Immense Power of generative AI

Recognising this reshaping of our thinking underlines the transformative power of generative AI, which is as broad as deep. This technology has the potential to revolutionise efficiency, drive innovation and streamline processes across numerous sectors. To fully realise these benefits, however, we must thoughtfully guide the development and application of generative AI, maintaining a comprehensive understanding of its potential and limitations to ensure its responsible, strategic use.

Balancing Risks and Opportunities

While it's true that generative AI poses significant challenges, I firmly think that the potential benefits far outweigh the risks, as I believe that the gains in productivity, creative problem solving, and resource management that can be derived from AI can drive societal progress and economic growth on an unprecedented scale.

Moreover, by recognising AI as a digital extension of our thought processes, we allay fears of AI as an independent entity, allowing us to maintain control over this technology and align its development with our collective ethical and societal norms. Finally, generative AI has the potential to democratise access to information, services, and resources, enabling widespread access to services once limited by human capacity.

As creators and stewards of AI, we are responsible for ensuring that this digital manifestation of our knowledge benefits the collective. In doing so, we shift the narrative toward the limitless potential of generative AI and away from the predominantly fear-driven perspectives. This belief underpins my conviction that the benefits of integrating generative AI into our society far outweigh the risks.