The implementation of AI applications have already exhibited serious questions related to implications for businesses, government, and society.
A desired action in 2019 regarding AI technology refers to deploying AI throughout organizations which choose their implementation in order to create maximum value, to enhance their business operations, using specific approach that the organizations choose to create value for customers and other beneficiaries.
Some questions have already arisen before starting the use of AI to improve the results of the companies: define the AI strategy including the definition of company data to be AI-ready, how to find the people who know how to use this technology and train the existing employees
It is not unusual to discover different ways to use AI, one referring to how to implement AI and predicting the results that must happen so that the AI implementation can prove successful in your organization.
Define the AI strategy, in the technology itself there is a machine learning component. To achieve the peak performance of this tech, the way to implement it is to let the machine teach itself. There exist some advantages to this approach: for something to resolve, the AI system can find aspects which humans may miss and may not even consider included in the assumptions to solve any problem.
If at first you implement AI and then let it learn, deploy, and give results based on its own learning what are the implications? It means that up to a point you can program it and implicitly make decisions. After that point you allow the AI-driven technology to make decisions on its own based on the patterns it produces and then it displays the results. When you do not program the AI you give power to AI and as often mentioned in the tech literature this stops the human effort and control over the AI-driven activities.
Researchers at the Georgia Institute of Technology, Cornell University and University of Kentucky have collaborated to produce AI which after selecting choices in relation to solve a problem, the AI are programmed to explain the reasons behind making the decisions. The AI device explains in real-time its actions, justifies its moves after they experienced own development and learning using different aspects, various angles of displaying what has been internally produced in the machine.
Although the explanation does not mean predictability, you can choose which AI systems to develop and can implement under your guidance, find out the reasoning behind the AI activities expressed through its explanations/information since only at the time of implementing the AI-driven tools you can factually see their outcome.