Abstract
Initially, when we thought of doing this article, the first author (JC) felt distain. I (JC) must admit that I am not much of a prognosticator. Skinner (1990) argued that we do not the future but we know the past. We attempt to discriminate relevant variables in the present from the past and respond to them. For example, if the reader has an interest in robotics, neural networks (e.g., Thrun, & Mitchell, 1993), and operant conditioning (e.g., Thrun & Schwartz, 1995) models of behavioral development. The world has aging populations. Often this population experiences problems with mobility. Today, this problem is handled by giving them scooters. Scooters have a problem in that once you start using them, the mobility rarely returns and they are not very flexible as to the places that you can go. In the movie Forrest Gump, Forrest had bracers for his legs made from metal to help him walk. Given this set of learning experiences, one can easily suggest envision solving the problem of older people walking as the creation of a device like Forrest's braces only with an operant neural network based chip. When the person is younger (say early 50s), they are made a set of braces. They are instructed to wear the braces for a week or so. Through this wearing, the person's muscles train the chip as to the person's movement range and muscle reactions. The chip is stored for year and when the person is experiencing problems in mobility (maybe 80 or 90 years old), the bracers are taken from the closet, the chip placed back in, and put on the person in effect creating an exoskeleton. This will instantly help the person to walk but it is farm more helpful then that- it can help the person to regain the strength to be independent again. The device can be designed so that each day of consecutive wearing, it gradually transfer .02% of the workload back to the existing muscle structures of the person who is the wearer. Thus, in a year or so, it gradually rebuilds the muscle to walk without the device. The above sounds like a plan, maybe or maybe not. Lots of environmental variables might render the device worthless. For example, biological research on stem cells might develop to the point of recreating muscle tissue rapidly regenerating the lost muscle. Another possible break to the plan would be that since scooter technology already exists, it has many people working on its improvement as a technology to increase mobility, as opposed to our suggested exoskeleton. Finally, some unforeseen advance in some other field could change the landscape even further relegating our work to worthless. Like with the above an ever shifting environment and stimuli emerge, rarely can we make predictions with 100% certainty. The same can be said to be true for licensing. Is it a breath of new air for behavior analysts or a threat and bringer of doom? What we can predict is the community's reaction. When a vague stimuli emerges, signal detection theorists (Greene & Swets, 1966; Swets, 1992) tell us, response can be organized into the following classification system (Table 1) So we can ask if the stimulus of licensing is good for the profession. Since it is a vague stimulus our responses will fall into one of the four boxes (Table 1). Yet, our responses are also behavior under operant control and prone to local contingencies that effect the statement. For example, we believe licensing to be good for several reasons (1) it will establish behavior analysis as a profession in a given state. Once it is a profession (a) parents or advocate groups can ask local Universities Why don't you have such a program? and thus create pressure on Universities to develop and staff behavior analytic programs. (b) More university programs will mean more faculty positions and granter number of research grants are researchers argue things like well thousands of clinicians are using stimulus control techniques in work with their clients but the process of stimulus control is not researched. …
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