algorithmic aversion
What It Means
Algorithmic aversion is when people automatically distrust or reject AI-driven decisions, even when the algorithm performs better than humans. Users often prefer human judgment over algorithmic recommendations, regardless of actual performance data. This bias leads people to abandon or avoid AI systems after seeing them make mistakes, while being more forgiving of equivalent human errors.
Why Chief AI Officers Care
This bias directly undermines AI adoption and ROI across the organization, as employees and customers resist using AI tools that could improve efficiency and outcomes. It creates significant change management challenges when rolling out AI systems, requiring additional training and communication strategies. The aversion can lead to shadow workarounds where people bypass AI systems, reducing data quality and creating compliance gaps.
Real-World Example
A hospital implements an AI system that accurately diagnoses skin cancer 95% of the time versus dermatologists' 87% accuracy rate. However, after the AI misses one case, doctors lose confidence and revert to manual diagnosis, citing the need for 'human judgment' despite the AI's superior overall performance record.
Common Confusion
People often confuse algorithmic aversion with legitimate concerns about AI bias or accuracy. The key difference is that algorithmic aversion persists even when the AI demonstrably outperforms humans and operates fairly.
Industry-Specific Applications
See how this term applies to healthcare, finance, manufacturing, government, tech, and insurance.
Healthcare: In healthcare, algorithmic aversion manifests when clinicians and patients reject AI diagnostic tools or treatment recom...
Finance: In finance, algorithmic aversion manifests when clients reject robo-advisor recommendations or algorithmic trading strat...
Premium content locked
Includes:
- 6 industry-specific applications
- Relevant regulations by sector
- Real compliance scenarios
- Implementation guidance
Technical Definitions
NISTNational Institute of Standards and Technology
"biased assessment of an algorithm which manifests in negative behaviours and attitudes towards the algorithm compared to a human agent."Source: Ekaterina_et_al_2020
Discuss This Term with Your AI Assistant
Ask how "algorithmic aversion" applies to your specific use case and regulatory context.
Start Free Trial