Smart Data, Unfair Outcomes: How AI is Reshaping Insurance – and Not for the Better

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Introduction

In the age of algorithms, the insurance industry has undergone a quiet but radical transformation. Once grounded in the statistical science of shared risk, insurers are increasingly turning to artificial intelligence (AI) and big data to make highly individualised decisions about coverage and cost. What is sold as personalisation is, in truth, a sophisticated method of discrimination-one that penalises people not based on actual events, but on what an algorithm predicts might happen[1][2][3].

At the same time, many governments-particularly those influenced by populist and neoliberal ideologies-are stepping back from their responsibility to provide public services. Citizens are being nudged towards sourcing their own support through private means, leading to a dangerous convergence: hyper-individualised risk assessment meets a shrinking safety net, leaving consumers increasingly vulnerable[4][5].

1. From General Statistics to Personal Surveillance

Traditionally, insurance risk was assessed using general statistical models-age brackets, regional data, and historical trends. These actuarial methods relied on pooled risk across similar demographics, providing a transparent model built on the principle of shared vulnerability.
Today’s AI-driven models, however, operate on real-time surveillance and micro-profiling. Insurers now draw data from fitness trackers, smart phones, social media activity, purchasing habits, and even browser history[2][6].
Instead of grouping people into risk categories, they assign scores to individuals based on complex and opaque algorithms. This shift may seem efficient, but it dramatically alters the ethical foundation of insurance[1][2][6].

2. A One-Sided Benefit.

Insurers claim that AI allows them to offer fairer, more customised premiums. In reality, it gives them powerful tools for cherry-picking customers. Those deemed low-risk may be offered marginally cheaper deals, while everyone else faces increased premiums or outright refusal[3][2].

3. Discrimination Disguised as Data

The move towards AI-based profiling entrenches existing inequalities. Data points often act as proxies for race, income, health status, and disability. For example, someone living in a poorer neighbourhood, buying discounted food, or browsing content related to mental health might be flagged as high risk-despite never having made a claim[7][2].

This is not merely unfair-it is deeply discriminatory. Worse still, algorithmic decisions are difficult to challenge, as they are proprietary and shielded under commercial confidentiality[7][2]. Research has shown that “proxy discrimination” occurs when insurers use neutral traits that correlate with protected groups, resulting in higher premiums for minorities or disadvantaged populations[7].

4. The Bigger Picture: Retreat of the State

These developments are not occurring in a vacuum. Over the past few decades, many Western governments-including the UK-have pursued an agenda of shrinking public services and promoting personal responsibility. Health care, pensions, disability support, and even unemployment benefits have been steadily privatised or devolved to underfunded local authorities[4][5].

This ideological shift creates a dependency on private insurance markets. But when those markets are driven by opaque algorithms and unchecked AI, citizens are left unprotected. The public good is replaced by private profit, and essential services become inaccessible to those who need them most[5][4].

5. Toward a Fairer Model

Insurance should be about pooling risk and supporting those in need. Instead, it is becoming a mechanism for reinforcing privilege and punishing the vulnerable. Without stronger regulation, increased transparency, and digital rights protections, this trend will only accelerate[7][2].

Governments must not only regulate the use of AI in insurance, but also reaffirm their responsibility to provide universal access to essential services. Data must not become destiny. We need a digital infrastructure that serves the public, not just the powerful[7][5].

Conclusion

The rise of AI in insurance marks a turning point-not just in how risk is calculated, but in how society defines fairness. If left unchallenged, these technologies will continue to benefit insurers at the cost of consumer rights and social cohesion[1][2][7]

Insurance was once a tool for collective security. It must not become a system of selective exclusion. To prevent this, we must demand transparency, advocate for digital justice, and push back against the erosion of our public institutions[7][5].

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