Machine-Learning Machines Possibilities and Capabilities of Authentic Learning

Do Machine-Learning Machines Learn?
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Do Machine-Learning Machines Learn?
Contrary to Bringsjord’s argument that machine-learning machines cannot learn, the ability of systems to learn from data, identify patterns, and make decisions with minimal human intervention encompasses real learning. Therefore, machine-learning machines undergo real learning. Machine learning is a product of innovative technology that has significantly improved many industrial, such as manufacturing and operation of machineries, and professional processes, such as supervision and holding meetings. It is a form of artificial intelligence that uses statistical techniques to create intelligent computer systems capable of learning from the available databases. Computer systems collect all the consumer information during the machine learning process and create patterns from the data. The process is usually programmed, and hence it is adjusted to suit the specific conditions needed. The algorithms adapt to data with time, allowing the system to develop behaviors that were not programmed in advance.
Despite explicit information about the actual learning process of the machines, some researchers, including Selmer Bringsjord, have argued that real learning is impossible in the machine-learning process. First, Bringsjord defines real learning as an intuitive process characterized by an understanding of the available facts. In his reasoning, he contends that even machines that have human-level intelligence are not close to having a human’s ability to understand the procedures involved in a process. Bringsjord associated the ability to understand the human potential to undertake operationalization, which involves combining ideas with data and using wit to solve problems. Wit entails responding to penetrating questions and providing the necessary proof that the answers are correct. This discussion centers on the fear that machines will replace humans at one point.
First, Bringsjord erred in asserting that machines cannot develop intuition. There are already intuition machines specializing in deep learning and the visual domain, such as the Adaptive Learning via Intuitive/Interactive, Collaborative and Emotional Systems (ALICE) tool (Claudiu, 2011). The creators of this concept of intuition developed the idea from Google’s DeepMind research that involved a supercomputer that applied an artificial intelligence device called AlphaGo. This device derives its name from its prowess in playing the ancient game of Go, in which it ended up outshining even the best human players in the world. Following the success of AlphaGo, the creators built a successor called AlphaGo Zero, which outshined AlphaGo. This new device has shown the potential of machines to use intuitive thinking, som...