The production and use of technologies as an extension of the human condition has helped us not only to dominate our natural environment, but to know ourselves better as a biological species. Therefore research in Artificial Intelligence is a fertile field to generate new forms of scientific knowledge, as well as for the production of innovative artifacts that serve as an epistemic extension for augmenting human intellect.
The intellectual roots of AI, and the concept of intelligent machines, may be found in Greek mythology. For example Hephaestus -the god of metalworking, craftsmen, sculptors- manufactured mechanical servants, and in the 4th century B.C. Aristotle invented syllogistic logic, the first formal deductive reasoning system. Intelligent artifacts appear in literature since then, with real (and fraudulent) mechanical devices actually demonstrated to behave with some degree of intelligence.
After modern computers became available, following World War II, it has become possible to create programs that perform difficult intellectual tasks. From these programs, general tools are constructed which have applications in a wide variety of everday problems. Artificial Intelligence was founded as an academic discipline in 1956, and in the years since has experienced several waves of optimism, followed by disappointment and the loss of funding. For most of its history, AI research has been divided into subfields that often fail to communicate with each other.
In 1965 philosopher Hubert Dreyfus was hired by RAND Corporation where he wrote “Alchemy and AI” a paper ridiculizing Artificial Intelligence and this new field ́s researchers by comparing it ́s theoretical foundation with mythology by predicting that there were limits beyond which AI would not progress. Dreyfus -whose critique was based on the insights of modern continental philosophers- argued that human intelligence and expertise depend primarily on unconscious instincts rather than conscious symbolic manipulation, and that these unconscious skills could never be captured in formal rules.
In the twenty-first century AI techniques, especially Deep Learning, have experienced a resurgence following concurrent advances in computer power, large amounts of data, and theoretical understanding; and Artificial Intelligence or Cognitive Computing have become an essential part of the technology industry. University of California computer scientists Stuart Russell and Google’s director of research, Peter Norvig, put this field into four broad categories:
- machines that think like humans
- machines that act like humans
- machines that think rationally
- machines that act rationally.
As computer scientist and entrepreneur Jerry Kaplan states in his book “Artificial Intelligence: What Everyone Needs to Know” that as for today “little more than speculation and illusions unites the real work of AI with the mysterious works of the human mind: in practice, it is an engineering discipline whose relationship with biological organisms is mostly metaphorical and inspirational”. On the other hand pioneer scientist Margaret Boden explains in her new book “AI: it ́s nature and future” the applications of Artificial Intelligence lie all around us; in our homes, schools and offices, in our cinemas, in art galleries and – not least – on the Internet. The results of Artificial Intelligence have been invaluable to biologists, psychologists, and linguists in helping to understand the processes of memory, learning, and language from a fresh angle. As a concept, Artificial Intelligence has fuelled and sharpened the philosophical debates concerning the nature of the mind, intelligence, and the uniqueness of human beings.
“The intellectual activity that produces material artifacts is no different fundamentally from the one that prescribes remedies for a sick patient or the one that devises a new sales plan for a company or a social welfare policy for a state”, Herbert A. Simon, “Sciences of the Artificial” (1968).
As Computer Simulation methods (like Artificial Intelligence) have gained importance in more and more scientific disciplines, the issue of their trustworthiness for generating new knowledge has grown, especially when simulations are expected to be counted as epistemic peers with experiments and traditional analytic theoretical methods. According to R.W. McHaney the fields of Artificial Intelligence and Computer Simulation are two different classes of tools used to tackle similar problems. The merger of these two technologies appears to be an inevitable and exciting part of computer simulation’s near future.
Paul Humphreys and Mark Bedau have argued that philosophers interested in the topic of emergence can learn a great deal by looking at computer simulation. And since the publication in 1922 of “The Emergent Theory of Mind” by G.T.W. Patrick this topic has been recurring in the explanation of the mind processess and how our mind arises from biological matter. It should be clear by now that AI research has a lot to contribute to the study of cognitive procesess and little in common with Alchemy, that philosophical and protoscientific tradition which higher goal was the creation of an elixir of immortality.
The old story of AI is about human brains working against silicon brains. Therefore videogame developer and teacher Nicky Case firmly states that we should not fear artificial Intelligence because the new story of AI will be about human brains working with silicon brains. As Douglas Engelbart reasoned some time ago the state of our current technology controls our ability to manipulate information, and that fact in turn will control our ability to develop new, improved technologies. Augmenting Human Intellect therefore will increase “the capability of a man to approach a complex problem situation, to gain comprehension to suit his particular needs, and to derive solutions to problems”.
According to architect and designer Neri Oxman engineering produces utility that is used by designers. Designers produce changes in behavior that are perceived by artists. Art produces new perceptions of the world, thereby granting access to new information in and about it, and inspiring new scientific inquiry. Oxman argues that if “nature” is described as “anything that supports life,” and if life “cannot be sustained without culture,” the two belief systems collapse into singularity. In this singularity, Nature claims the infrastructure of civilization and, equally so, culture now enables the design of Nature herself.
Anyway, if we truly want to design machines that exhibit intelligent and/or creative outcomes -or at least that function as an enhancement of our own capacity for knowledge and originality- a divergent state of mind will be needed. And many times artistic processes are really helpful specially if we learn to distance ourselves from a romantic and idealized view of human condition and creativity, because there is not hidden “magic” in the cognitive processes behind the creation and design of new ideas and objects.
*(Picture: pexels.com & Isaac Newton was also an alchemist).