• Finance : By evaluating market data and executing transactions at fast speeds , it is expected to achieve risk avoidance , such as fraud identification and risk assessment , as well as optimise investment strategies .
• Manufacturing : Data utilisation is expected to greatly improve productivity . In addition to optimising supply chain / logistics and resource allocation , the use of data can be considered in the area of predictive maintenance , which has been overlooked by humans in the past , enabling data-based analysis to predict equipment failures and achieve leaner production schedules .
It is no exaggeration to say that AI ethics and explainable AI will be most central to the future development of AI and machine learning technologies . Discrimination and bias , in terms of ethics , and transparency , in terms of responsible AI , are particularly important . It is necessary to clarify where the responsibility lies with regard to accountability for AI decisionmaking , and it is essential to work hard to develop guidelines and regulations that are tailored to individual situations , as has been discussed with many other countries and companies .
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