Data may be just a raw material. But Artificial Intelligence (AI) has breathed new life into how that raw material is being used to add value for businesses on the basis of algorithmic processing. The absence of human agency in this process means the trust we would typically place in a person we have interviewed, hired and built up a relationship with is now placed in machines, algorithms and data quality. No surprises, then, that AI is considered guilty until proven innocent when it comes to convincing those that need to rely on decisions made by AI .
The advantages of data and AI-driven solutions, improving accuracy, performance, resiliency and real-time adaptation, are plain to see for most tech-based businesses. However, even if your business is not directly reliant on AI at present, chances are some neural networks will be working in the background of your peripheral activity. Alternatively, AI may well become part of your future value proposition – or is already directly impacting the work of service providers and partners. All the more reason to understand what it means to create responsible and trustworthy AI .
Trust is one of the most defining factors in all kind of interactions. Proposing that machines humans are interacting with should be trusted, is a claim that should not be taken lightly.
We share a growing reliance on them to perform crucial tasks, and that means learning to trust systems based on AI is not something businesses can bypass in the long run.