The "Artificial Mathematician" Objection: Exploring the (Im)possibility of Automating Mathematical Understanding

Reuben Hersh confided to us that, about forty years ago, the late Paul Cohen predicted to him that at some unspecified point in the future, mathematicians would be replaced by computers. Rather than focus on computers replacing mathematicians, however, our aim is to consider the (im)possibility of human mathematicians being joined by “artificial mathematicians” in the proving practice—not just as a method of inquiry but as a fellow inquirer

Pioneers on the air: BBC radio broadcasts on computers and A.I., 1946-56

Between 1946 and 1956, a number of BBC radio broadcasts were made by pioneers in the fields of computing, artificial intelligence and cybernetics. Although no sound recordings of the broadcasts survive, transcripts are held at the BBC's Written Archives Centre at Caversham in the UK. This paper is based on a study of these transcripts, which have received little attention from historians. The paper surveys the range of computer-related broadcasts during 1946–1956 and discusses some recurring themes from the broadcasts, especially the relationship of 'artificial intelligence' to human intelligence. Additionally, it discusses the context of the broadcasts, both in relation to the BBC and to contemporary awareness of computers

Previously undiscovered neurons of the Bogong moth brain: 3D-reconstruction and registration

The Australian Bogong moths are thought to have the ability to sense the earth’s magnetic field. This ability has to be reflected in the animal’s neural architecture. Hence reconstruction of three brain neurons was carried out, though these respond to visual stimulation instead of magnetic. These reconstructions were compared to that of other known specie’s visual responsive neurons to provide a basis for future investigation into the Bogong moth’s magnetic processing. The neurons were reconstructed with the Amira5.3 program to give 3D representations of their morphology. From this it was concluded that two of the neurons lack homologous ones in other species, these two being previously undiscovered. Implying a possible deviance in how the Bogong moth processes visual information.Brain architecture can give information about your worldly position Imagine yourself suddenly lost inside a thick green forest and you have no idea of how you got there. You are starting to get hungry, you want to go home, but where is home? As if that wasn’t enough the sun is slowly setting over the majestic trees lines, twilight falls and then, then it’s almost impossible to see the world in front of you. Sounds hard huh? These are the conditions that the Australian Bogong moth migrates under and this for a distance 100 of mils. Members of this small insect species are born in the northern part of Australia and migrate to the south, where they sleep through the summer months only to return to their breeding grounds once they awaken. Here in the north they mate and then they die, passing on the mantle to the next generation. The only way these insects can know where they are going is through having some sensory input telling them which direction they’re facing, like their eyes. Because the Bogongs are active during the night most reliable stimuli from the sun, that can give an insect an understanding of where to go, are missing. The only really reliable stimulus left is the ability to sense the earth’s magnetic field. This works in a manner similar to that of a compass, it is like the Bogongs have an internal compass in their head guiding them to their destination. For this internal compass to work there need to be some mechanics behind it, in the case of animals this is most often the brain. The brain can be seen as a big tangled mess of millions of wires connecting different brain areas to one another. Depending on how these connections between wires look an individual might have different abilities, like the internal compass. There needs to be a reflection of this and other abilities in this insect’s brain. Bellow three of these different brain cells, these wires, have been reconstructed in 3D. The cells are shown in different colors, with a few brain areas being transparently grey. These cells collect information from vastly different brain areas and transmit it other different areas. All are involved in processing slightly different kinds of information. They all responded to visual information, not magnetic. However knowing their function is an important step in determining how the internal magnetic compass functions. If one understands how the different cells within a brain wire together it is possible to make synthetic systems that can process information in a similar manner. That is, making computers and robots that can use the earth’s magnetic field and know what direction it’s facing. So in the future, when you are standing in the forest all alone, without a functional GPS on your phone, you might be able to take it out of your pocket. And even without you knowing your position your phone will be able to sense the earth’s magnetic field and determine which way your home is. You’ll be home and dry all thanks to this little insect’s brain. Supervisor: Stanley Heinze Degree Project MOBK01, 15 credits, 2015 Department of Biology, Lund Universit

Artificial Intelligence in the Context of Human Consciousness

Artificial intelligence (AI) can be defined as the ability of a machine to learn and make decisions based on acquired information. AI’s development has incited rampant public speculation regarding the singularity theory: a futuristic phase in which intelligent machines are capable of creating increasingly intelligent systems. Its implications, combined with the close relationship between humanity and their machines, make achieving understanding both natural and artificial intelligence imperative. Researchers are continuing to discover natural processes responsible for essential human skills like decision-making, understanding language, and performing multiple processes simultaneously. Artificial intelligence attempts to simulate these functions through techniques like artificial neural networks, Markov Decision Processes, Human Language Technology, and Multi-Agent Systems, which rely upon a combination of mathematical models and hardware

Minds, Brains and Programs

This article can be viewed as an attempt to explore the consequences of two propositions. (1) Intentionality in human beings (and animals) is a product of causal features of the brain I assume this is an empirical fact about the actual causal relations between mental processes and brains It says simply that certain brain processes are sufficient for intentionality. (2) Instantiating a computer program is never by itself a sufficient condition of intentionality The main argument of this paper is directed at establishing this claim The form of the argument is to show how a human agent could instantiate the program and still not have the relevant intentionality. These two propositions have the following consequences (3) The explanation of how the brain produces intentionality cannot be that it does it by instantiating a computer program. This is a strict logical consequence of 1 and 2. (4) Any mechanism capable of producing intentionality must have causal powers equal to those of the brain. This is meant to be a trivial consequence of 1. (5) Any attempt literally to create intentionality artificially (strong AI) could not succeed just by designing programs but would have to duplicate the causal powers of the human brain. This follows from 2 and 4

Challenging the Computational Metaphor: Implications for How We Think

This paper explores the role of the traditional computational metaphor in our thinking as computer scientists, its influence on epistemological styles, and its implications for our understanding of cognition. It proposes to replace the conventional metaphor--a sequence of steps--with the notion of a community of interacting entities, and examines the ramifications of such a shift on these various ways in which we think

From Biological to Synthetic Neurorobotics Approaches to Understanding the Structure Essential to Consciousness (Part 3)

This third paper locates the synthetic neurorobotics research reviewed in the second paper in terms of themes introduced in the first paper. It begins with biological non-reductionism as understood by Searle. It emphasizes the role of synthetic neurorobotics studies in accessing the dynamic structure essential to consciousness with a focus on system criticality and self, develops a distinction between simulated and formal consciousness based on this emphasis, reviews Tani and colleagues' work in light of this distinction, and ends by forecasting the increasing importance of synthetic neurorobotics studies for cognitive science and philosophy of mind going forward, finally in regards to most- and myth-consciousness