Abstract
“Cognitive Computing” has become somewhat of a rallying call in the technology world, with the promise of new smart services offered by industry giants like IBM and Microsoft. The associated technological advances in Artificial Intelligence (AI) have thrown into the public sphere some old questions about the relationship between machine computation and human intelligence. Much of the industry and media hype suggests that many traditional challenges have been overcome. On the contrary, our simple examples from language processing demonstrate that present day cognitive computing still struggles with fundamental, long-standing problems in AI. An alternative interpretation of cognitive computing is presented, following Licklider’s lead in adopting “man-computer symbiosis” as a metaphor for designing software systems that enhance human cognitive performance. A survey of existing proposals on this view suggests a distinction between weak and strong versions of symbiosis. We propose a Strong Cognitive Symbiosis, which dictates an interdependence rather than simply cooperation between human and machine functioning, and introduce new software systems, which were designed for cognitive symbiosis. We conclude that strong symbiosis presents a viable new perspective for the design of cognitive computing systems.
Highlights
The Gartner Hype Cycle for Smart Machines, 2017, names Cognitive Computing as a technology on the “Peak of Inflated Expectations” [1]
We propose a Strong Cognitive Symbiosis, which dictates an interdependence rather than cooperation between human and machine functioning, and introduce new software systems, which were designed for cognitive symbiosis
Predictive statistical models based on vast quantities of data are all there is to natural language cognition
Summary
The Gartner Hype Cycle for Smart Machines, 2017, names Cognitive Computing as a technology on the “Peak of Inflated Expectations” [1]. IBM’s public promotional materials claim that “cognitive computers can process natural language and unstructured data and learn by experience, much in the same way humans do” [4] This kind of extravagant language brings to mind the term ‘strong AI’, which describes systems that process information “in the same way humans do”. Licklider felt that the emergence of something like strong AI was not imminent, and there would be an interim period of “between 10 and 500 years” in which humans and computers would exist in a symbiotic relationship that would “bring computing machines effectively into the processes of thinking” He argued that for many years, computer programs would not be able to mimic human thought processes, but instead work with humans as “dissimilar organisms living together in intimate association”, enhancing the weaker parts of human cognition.
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