Bayes in the age of intelligent machines

The success of methods based on artificial neural networks in creating intelligent machines seems like it might pose a challenge to explanations of human cognition in terms of Bayesian inference. We argue that this is not the case, and that in fact these systems offer new opportunities for Bayesian modeling. Specifically, we argue that Bayesian models of cognition and artificial neural networks lie at different levels of analysis and are complementary modeling approaches, together offering a way to understand human cognition that spans these levels. We also argue that the same perspective can be applied to intelligent machines, where a Bayesian approach may be uniquely valuable in understanding the behavior of large, opaque artificial neural networks that are trained on proprietary data

Industrial Applications: New Solutions for the New Era

This book reprints articles from the Special Issue "Industrial Applications: New Solutions for the New Age" published online in the open-access journal Machines (ISSN 2075-1702). This book consists of twelve published articles. This special edition belongs to the "Mechatronic and Intelligent Machines" section

The coming jobs boom in the age of intelligent machines

We're pessimistic when we focus on the world that we know now, not thinking that processes are being reorganised, writes Ben Prin

Workshop: Work in the Age of Intelligent Machines

This all-day workshop aims to promote convergence among its participants on research related to working with intelligent machines. We define intelligent machines as both material (e.g., robots) and immaterial (e.g., algorithms) computing technologies that can be characterized by autonomy, the ability to learn, and the ability to interact with other systems and with humans. The workshop has three goals: identifying specific research problems around work and intelligent machines, developing a common language base that can facilitate interdisciplinary collaboration among researchers, and identifying information and cyber-infrastructure needs to support convergent research. Workshop activities will facilitate interdisciplinary dialogue and strive to generate high-impact research ideas to advance each of these goals.NSF 17-45463Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138939/1/Erickson et al. 2018.pdfDescription of Erickson et al. 2018.pdf : Main articl

Creative Machines

Technology has shifted humans from their highly calculated ‘older’ traditions of orthogonal thinking…to a more developed machine-age where we can now benefit from utilising machines and their assets to assist in repetitive design tasks in a more precise and automated manner. Through the interoperation of computer systems, we are in a beneficial position to be able to lead machines and Ai to think critically using our data in an intelligent way. So that humans can benefit from the innovations and technological creations derived by our own kind. Architects and designers must find new ways of constructing significance from data to benefit our future existence on earth - assisted by ‘Creative Machines’. Developing the intersection of innovative design with cutting-edge technologies will enable humans to respond effectively towards existing globalclimate-challenges beyond our own native capacities

Transhumanism Between Human Enhancement and Technological Innovation

Transhumanism introduces from its very beginning a paradigm shift about concepts like human nature, progress and human future. An overview of its ideology reveals a strong belief in the idea of human enhancement through technologically means. The theory of technological singularity, which is more or less a radicalisation of the transhumanist discourse, foresees a radical evolutionary change through artificial intelligence. The boundaries between intelligent machines and human beings will be blurred. The consequence is the upcoming of a post-biological and posthuman future when intelligent technology becomes autonomous and constantly self-improving. Considering these predictions, I will investigate here the way in which the idea of human enhancement modifies our understanding of technological innovation. I will argue that such change goes in at least two directions. On the one hand, innovation is seen as something that will inevitably lead towards intelligent machines and human enhancement. On the other hand, there is a direction such as “Singularity University,” where innovation is called to pragmatically solving human challenges. Yet there is a unifying spirit which holds together the two directions and I think it is the same transhumanist idea

Universal Intelligence: A Definition of Machine Intelligence

A fundamental problem in artificial intelligence is that nobody really knows what intelligence is. The problem is especially acute when we need to consider artificial systems which are significantly different to humans. In this paper we approach this problem in the following way: We take a number of well known informal definitions of human intelligence that have been given by experts, and extract their essential features. These are then mathematically formalised to produce a general measure of intelligence for arbitrary machines. We believe that this equation formally captures the concept of machine intelligence in the broadest reasonable sense. We then show how this formal definition is related to the theory of universal optimal learning agents. Finally, we survey the many other tests and definitions of intelligence that have been proposed for machines.Comment: 50 gentle page

Man and Machine: Questions of Risk, Trust and Accountability in Today's AI Technology

Artificial Intelligence began as a field probing some of the most fundamental questions of science - the nature of intelligence and the design of intelligent artifacts. But it has grown into a discipline that is deeply entwined with commerce and society. Today's AI technology, such as expert systems and intelligent assistants, pose some difficult questions of risk, trust and accountability. In this paper, we present these concerns, examining them in the context of historical developments that have shaped the nature and direction of AI research. We also suggest the exploration and further development of two paradigms, human intelligence-machine cooperation, and a sociological view of intelligence, which might help address some of these concerns.Comment: Preprin