From a technological standpoint, accountability is all about ensuring that those responsible for creating and executing Artificial Intelligence (AI) systems better recognize and grasp the potential footprint of such systems. It implies that clear lines of responsibility must be evident and maintained for the innovation and execution of AI technology, alongside imperative safeguards in location to progressively handle to negative impacts it might rouse. In order to successfully operationalize accountability, certain methods such as audits and independent monitoring may need to be utilized. By recognizing accountabilities regularly, any other harmful consequences that may emerge can be quickly attended to while the innovation of AI projects advances optimally.
