Diana Bang's ETEC 531 e-portfolio

The connectionist model of design contends that the brain operates from the bottom up rather than the top down approach and has been utilized in recent artificial intelligence research. A simplified version of this model is that thought is considered to develop though associative and low-level series of connections. For example, brain neurons are stimulated by the impressions given to them by the body’s sense organs. These impressions and responses then develop patterns in the brain’s neural pathways. When some networks are strengthened we achieve learning and at another level patterns form into conscious thoughts. Also, though time these patterns will continue to change. In relation to AI research, they’ve developed neural nets (i.e. web of neurons) which try to copy the parallel processing capabilities of the human brain. Minsky and Papert (1988) refer to these copies as the fundamental parts of “percepetrons” (as cited in Murphie & Potts, 2003). Thus, if this is indeed the way the human brain functions then the implications for AI research is that consciousness will develop with the proper connection between low-level components and the appropriate environment to learn. Ultimately, then the focus of AI should not be about trying to create a replica of the human brain as creating consciousness in machines is a matter making the “right” connections. What are the implications of achieving machine consciousness? Is it vision of a doomsday Terminator-like scenario or akin to WALL-E?