This thematic area measures steps countries have taken to enhance AI safety by integrating principles of accuracy and reliability into the design, development, use and deployment of AI technologies
Safety can be generally defined as the condition of being protected from or unlikely to cause danger, risk, or injury.
Accuracy can be defined as ‘the quality or state of being precise and correct’. If something is accurate, it is exact, meaning that it is not an approximation or estimation, and that its result is free from error or defect.
Reliability can be defined as ‘the quality of being trustworthy or of performing consistently well’.
Country and regional scores
Bright spots
Relevance
The emergence of AI driven technologies across various facets of life raises new questions around the safety of these tools and concerns about whether the decisions and outcomes of these tools can be trusted. Global movements have pushed for efforts to enhance AI safety, primarily by emphasising the importance of strict standards when it comes to the accuracy and reliability of AI systems as a way to mitigate harm and reduce risks to individuals, communities and societies that are looking to leverage the power of AI. Because AI technologies emanate from systems and contexts that are subject to human error, unconscious bias, and intersecting forms of inequality, the challenge and importance of building trustworthy AI systems and tools is both urgent and necessary.
Country rankings by Safety, accuracy and reliability
*In the table above, data was collected for Chinese Taipei (commonly referred to as Taiwan) and the West Bank, which is under the administration of the Palestinian Authority. No data collection took place in Gaza. We recognize that these are, at the time of writing, disputed jurisdictions.
