The Role of Imagination in Social Scientific Discovery: Why Machine Discoverers Will Need Imagination Algorithms

When philosophers discuss the possibility of machines making scientific discoveries, they typically focus on discoveries in physics, biology, chemistry and mathematics. Observing the rapid increase of computer-use in science, however, it becomes natural to ask whether there are any scientific domains out of reach for machine discovery. For example, could machines also make discoveries in qualitative social science? Is there something about humans that makes us uniquely suited to studying humans? Is there something about machines that would bar them from such activity? A close look at the methodology of interpretive social science reveals several abilities necessary to make a social scientific discovery, and one capacity necessary to possess any of them is imagination. For machines to make discoveries in social science, therefore, they must possess imagination algorithms

The computer revolution in science: steps towards the realization of computer-supported discovery environments

The tools that scientists use in their search processes together form so-called discovery environments. The promise of artificial intelligence and other branches of computer science is to radically transform conventional discovery environments by equipping scientists with a range of powerful computer tools including large-scale, shared knowledge bases and discovery programs. We will describe the future computer-supported discovery environments that may result, and illustrate by means of a realistic scenario how scientists come to new discoveries in these environments. In order to make the step from the current generation of discovery tools to computer-supported discovery environments like the one presented in the scenario, developers should realize that such environments are large-scale sociotechnical systems. They should not just focus on isolated computer programs, but also pay attention to the question how these programs will be used and maintained by scientists in research practices. In order to help developers of discovery programs in achieving the integration of their tools in discovery environments, we will formulate a set of guidelines that developers could follow

Evocative computing – creating meaningful lasting experiences in connecting with the past

We present an approach – evocative computing – that demonstrates how ‘at hand’ technologies can be ‘picked up’ and used by people to create meaningful and lasting experiences, through connecting and interacting with the past. The approach is instantiated here through a suite of interactive technologies configured for an indoor-outdoor setting that enables groups to explore, discover and research the history and background of a public cemetery. We report on a two-part study where different groups visited the cemetery and interacted with the digital tools and resources. During their activities serendipitous uses of the technology led to connections being made between personal memo-ries and ongoing activities. Furthermore, these experiences were found to be long-lasting; a follow-up study, one year later, showed them to be highly memorable, and in some cases leading participants to take up new directions in their work. We discuss the value of evocative computing for enriching user experiences and engagement with heritage practices

On Birthing Dancing Stars: The Need for Bounded Chaos in Information Interaction

While computers causing chaos is acommon social trope, nearly the entirety of the history of computing is dedicated to generating order. Typical interactive information retrieval tasks ask computers to support the traversal and exploration of large, complex information spaces. The implicit assumption is that they are to support users in simplifying the complexity (i.e. in creating order from chaos). But for some types of task, particularly those that involve the creative application or synthesis of knowledge or the creation of new knowledge, this assumption may be incorrect. It is increasingly evident that perfect order—and the systems we create with it—support highly-structured information tasks well, but provide poor support for less-structured tasks.We need digital information environments that help create a little more chaos from order to spark creative thinking and knowledge creation. This paper argues for the need for information systems that offerwhat we term ‘bounded chaos’, and offers research directions that may support the creation of such interface

What Can Artificial Intelligence Do for Scientific Realism?

The paper proposes a synthesis between human scientists and artificial representation learning models as a way of augmenting epistemic warrants of realist theories against various anti-realist attempts. Towards this end, the paper fleshes out unconceived alternatives not as a critique of scientific realism but rather a reinforcement, as it rejects the retrospective interpretations of scientific progress, which brought about the problem of alternatives in the first place. By utilising adversarial machine learning, the synthesis explores possibility spaces of available evidence for unconceived alternatives providing modal knowledge of what is possible therein. As a result, the epistemic warrant of synthesised realist theories should emerge bolstered as the underdetermination by available evidence gets reduced. While shifting the realist commitment away from theoretical artefacts towards modalities of the possibility spaces, the synthesis comes out as a kind of perspectival modelling

Does Evolution Explain Human Nature?

Compiles short essays by twelve scientists and scholars on how well the theory of evolution explains human nature. Separate link includes video of a panel discussion with three scientists

Reasonable Inferences From Quantum Mechanics: A Response to “Quantum Misuse in Psychic Literature”

This invited article is a response to the paper “Quantum Misuse in Psychic Literature,” by Jack A. Mroczkowski and Alexis P. Malozemoff, published in this issue of the Journal of Near-Death Studies. Whereas I sympathize with Mroczkowski’s and Malozemoff’s cause and goals, and I recognize the problem they attempted to tackle, I argue that their criticisms often overshot the mark and end up adding to the confusion. I address nine specific technical points that Mroczkowski and Malozemoff accused popular writers in the fields of health care and parapsychology of misunderstanding and misrepresenting. I argue that, by and large—and contrary to Mroczkowski’s and Malozemoff’s claims—the statements made by these writers are often reasonable and generally consistent with the current state of play in foundations of quantum mechanics