The “human-machine interaction”
Concept is widely discussed in academic circles nowadays. Broadly speaking, the term refers to the wide range of cases, in which people utilize various technological devices to fulfill “tasks too dangerous, too expensive, too onerous or too boring for human beings” (Sagan 377). The areas of knowledge, in which sophisticated mechanisms are employed, range from astronautics to medicine and from genetics to social care or psychology. The scholars whose articles have been reviewed before writing the present research paper (Sagan, Turkle, Kurzweil, and Joy) provide many examples of such an interesting collaboration.
The class of advanced machines operated by men for scientific and commercial purposes includes computers and robots, either self-controlled or remotely controlled. It is commonly believed that the former type of devices “has its intelligence within it” (Sagan 377), whereas the latter is linked to the outer source of intelligence. The question of whether intelligence in machines is brought into them by humans or developed as inherent in a course of technological evolution forms the core of a hot discussion.
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This metaphor came from Greek mythology to describe situations on the brink of collapse and despair. (Pandora was the first woman created by gods who gave her a jar full of all the world’s evils. She was believed to let these evils out of her box and close the lid when humans’ patience was almost exhausted. ) The scholar argued that by granting machines the gift of intelligence a human being endangers his own privileged position in the natural world and releases the mechanisms he is not able to control yet.
The present research will attempt to demonstrate how human species manage to communicate with robots (i. e. machines) to learn more about the functioning of natural systems. The argument about human-machine interaction being a positive process is supported by the enriched concept of evolution. Even kindergarten children know that all organisms possessing genes inherit certain traits that change over time as these species accommodate to the changing environments. At the age of machines coming to people’s aid in many fields out knowledge of evolution is rapidly enriched.
Kurzweil defined the expanded concept of evolution in the following words: Evolution moves towards greater complexity, elegance, intelligence, beauty, creativity, and love. … While evolution never reaches an infinite level, it advances exponentially, certainly moving in that direction. Technological evolution … moves us inexorably closer to becoming like God. And the freeing of our thinking from the severe limitations of our biological form may be regarded as an essential spiritual quest.
(391) The researcher prophesized that finally “the earth’s technology-creating species will merge with its own computational technology” (ibid. ), and this would be the ultimate goal of evolution in the world of artificial intelligence. However, it seems more appropriate to speak not about simply the “merge” but about more complex patterns of human-machine cooperation such as adaptivity. The thesis is explained on the example of the newest field of research – biomimetic robotics.
Utilizing biological matrices this science aims at designing mechanisms that would be able to communicate with the environments as flexibly as people without causing harm to the latter. The paper consists of three parts. The first section will review the main points of discussion about human-machine interaction in many realms of knowledge with the emphasis on biology. The second section will overview the goals of the new adaptive robotics. Besides it will analyze in depth the two of many its directions: the creation of walking robots and robots capable of sensory-motor coordination or control.
The conclusion section will summarize the principles of evolutionary robotics as the realm of important human-machine interaction following biological models. To return to the topic of human-machine interaction in general, intelligent mechanisms are used nowadays everywhere. People and mechanisms are often described in one and the same terms of memory, speed, task-solving and decision-making.