There has recently been a significant desire across industries and sectors to exploit Artificial Intelligence (AI) especially to drive the automation of human tasks and gain new insights from sensory information (data). AI can be used for “advisory-roles” (e.g. augmenting human decision-making) or “critical-roles” where the AI output could directly or indirectly impact life, society, environment, livelihood and at scale. AI such as typical neural networks are unable to sufficiently explain or reason about how they derived decisions. These uncertainties are brought about by the black-box nature of such paradigms and further exacerbate potential risks across industries. However, our AI technology is ideal for safety/business-critical applications and is able to provide reasoning and explanations behind critical-decision-making - resulting in a positive impact on trust, safety, security, ethics and performance.
Technology Features, Specifications and Advantages
Regulations, standards, best practices are not impediments for businesses. They help them deliver a less failure-prone service to their customers, reinforcing trust and protecting assets (e.g. cyber security to protect data – a business’ vital asset). However, the growing complexity of modern technology and services is making traditional methods inadequate for demonstrating and becoming compliant.
Our technology involves AI that is able to perform critical-decision-making and machine learning whilst being able to sufficiently explain its reasoning and behaviour in human understandable natural language. Our AI is also able to understand and show compliance of monitored systems with regulations, best practice, ethical frameworks, safety, security and performance requirements in real-time fashion (e.g. are self-driving vehicles insurable and compliant to regulations?). This technology can be applied to a wide range of applications including FinTech, Smart Cities, Transportation and Healthcare.
Our technology can be used for assurance of image and object recognition (e.g. perception of self-driving vehicles), Insurance (e.g. is your service still compliant with regulations?), Legal and Auditing (e.g. if a self-driving vehicle is involved in an accident who is to blame?), Control and Scheduling (e.g fuel optimisation or mechanical control of autonomous vehicles) and FinTech (e.g, is the service sufficiently cyber-secure and ethical?). Our technology is applicable cross-industry and cross-sector.
As an example, HSBC spent over US$2.2 billion to show compliance to regulations in 2015. This is set to increase with additional regulations (e.g. GDPR) and the probability of failures in compliance increases with the modern complexity of IT infrastructure and operations. The assured application of our AI can significantly reduce the probability of compliance and assurance failures whilst drastically reducing required resources.