The measurement of sensory intensity has had a long history, attracting the attention of investigators from many disciplines including physiology, psychology, physics, mathematics, philosophy, and even chemistry. While there has been a continuing doubt by some that sensation has the properties necessary for measurement, experiments designed to obtain estimates of sensory intensity have found that a general rule applies: Equal stimulus ratios produce equal sensory ratios. Theories concerning the basis for this simple psychophysical rule are discussed, with emphasis given to (...) the physical correlate theory, which considers judgments of subjective magnitudes to be based upon estimates of physical dimensions that vary regularly with changes in degree of stimulation. For the most thoroughly investigated sensory scales, brightness and loudness, the physical correlate is considered to be distance. Our “tacit knowledge” of the sensory effects of changing distance plays an essential role in matching motor activities to environmental conditions and in ensuring accurate perceptual evaluations through brightness and loudness constancies. In psychophysical experiments, subjects apparently use this same tacit knowledge when required to estimate relative subjective magnitudes. The evidence related to the physical correlate theory is summarized, and it is concluded that, while under appropriate conditions we demonstrate considerable skill in evaluating environmental relationships, we are quite unable to estimate the neurophysiological nature or quantity of sensory response. A psychophysics devoted to studying conditions required for accuracy and conditions producing errors in the perception of environmental relationships would seem to be more valuable than one devoted to subjective magnitudes. (shrink)

Psychological and philosophical studies have extended J. J. Gibson’s notion of affordances. Affordances are possibilities for bodily action presented to us by the objects of our perception. Recent work has argued that we should extend the actions afforded by perception to mental action. I argue that we can extend the notion of affordance itself. What I call ‘Introspective Affordances’ are possibilities for mental action presented to us by introspectively accessible states. While there are some prima facie worries concerning the non-perceptual (...) nature of introspection, I will argue that our internal mental lives share enough commonalities with experiences in our environment to warrant this extension. I will demonstrate the value of introspective affordances by showing how they allow us to explain an underexplored aspect of thought insertion. (shrink)

The book’s core argument is that an artificial intelligence that could equal or exceed human intelligence—sometimes called artificial general intelligence (AGI)—is for mathematical reasons impossible. It offers two specific reasons for this claim: Human intelligence is a capability of a complex dynamic system—the human brain and central nervous system. Systems of this sort cannot be modelled mathematically in a way that allows them to operate inside a computer. In supporting their claim, the authors, Jobst Landgrebe and Barry Smith, marshal evidence (...) from mathematics, physics, computer science, philosophy, linguistics, and biology, setting up their book around three central questions: What are the essential marks of human intelligence? What is it that researchers try to do when they attempt to achieve "artificial intelligence" (AI)? And why, after more than 50 years, are our most common interactions with AI, for example with our bank’s computers, still so unsatisfactory? Landgrebe and Smith show how a widespread fear about AI’s potential to bring about radical changes in the nature of human beings and in the human social order is founded on an error. There is still, as they demonstrate in a final chapter, a great deal that AI can achieve which will benefit humanity. But these benefits will be achieved without the aid of systems that are more powerful than humans, which are as impossible as AI systems that are intrinsically "evil" or able to "will" a takeover of human society. (shrink)

Psychophysical scaling models of the form R = f, with R the response and I some intensity of an attribute, all assume that people judge the amounts of an attribute. With simple biases excepted, most also assume that judgments are independent of space, time, and features of the situation other than the one being judged. Many data support these ideas: Magnitude estimations of brightness increase with luminance. Nevertheless, I argue that the general model is wrong. The stabilized retinal image literature (...) shows that nothing is seen if light does not change over time. The classification literature shows that dimensions often combine to produce emergent properties that cannot be described by the elements in the stimulus. These and other effects cannot be adjusted for by simply adding variables to the general model because some factors do not combine linearly. The proposed alternative is that people initially judge the entire stimulus – the object in terms of its environment. This agrees with the constancy literature that shows that objects and their attributes are identified through their relations to other aspects of the scene. That the environment determines judgments is masked in scaling studies where the standard procedure is to hold context constant. In a typical brightness study the essential stimulus might be the intensity of the light or a difference between the light and the background. The two are perfectly confounded. This issue is examined in the case of audition. Judgments of the loudness of a tone depend on how much that tone differs from the previous tone in both pitch and loudness. To judge loudness people first seem to process the stimulus object in terms of differences between it and other aspects in the situation; only then do they assess the feature of interest. Psychophysical judgments will therefore be better interpreted by theories of attention that are based in biology or psychology than those that are based in classical physics. (shrink)

Central to contemporary cognitive science is the notion that mental processes involve computations defined over internal representations. This view stands in sharp contrast to the to visual perception and cognition, whose most prominent proponent has been J.J. Gibson. In the direct theory, perception does not involve computations of any sort; it is the result of the direct pickup of available information. The publication of Gibson's recent book (Gibson 1979) offers an opportunity to examine his approach, and, more generally, to contrast (...) the theory of direct perception with the computational/representational view. In the first part of the present article (Sections 2direct perceptioncase study”: the problem of perceiving the three-dimensional shape of moving objects is examined. This problem, which has been extensively studied within the immediate perception framework, serves to illustrate some of the inherent shortcomings of that approach. Finally, in Section 5, an attempt is made to place the theory of direct perception in perspective by embedding it in a more comprehensive framework. (shrink)