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

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

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

Measuring impact of academic research in computer and information science on society

Academic research in computer & information science (CIS) has contributed immensely to all aspects of society. As academic research today is substantially supported by various government sources, recent political changes have created ambivalence amongst academics about the future of research funding. With uncertainty looming, it is important to develop a framework to extract and measure the information relating to impact of CIS research on society to justify public funding, and demonstrate the actual contribution and impact of CIS research outside academia. A new method combining discourse analysis and text mining of a collection of over 1000 pages of impact case study documents written in free-text format for the Research Excellence Framework (REF) 2014 was developed in order to identify the most commonly used categories or headings for reporting impact of CIS research by UK Universities (UKU). According to the research reported in REF2014, UKU acquired 83 patents in various areas of CIS, created 64 spin-offs, generated £857.5 million in different financial forms, created substantial employment, reached over 6 billion users worldwide and has helped save over £1 billion Pounds due to improved processes etc. to various sectors internationally, between 2008 and 2013

Open problems in artificial life

This article lists fourteen open problems in artificial life, each of which is a grand challenge requiring a major advance on a fundamental issue for its solution. Each problem is briefly explained, and, where deemed helpful, some promising paths to its solution are indicated

Lessons from a Restricted Turing Test

We report on the recent Loebner prize competition inspired by Turing's test of intelligent behavior. The presentation covers the structure of the competition and the outcome of its first instantiation in an actual event, and an analysis of the purpose, design, and appropriateness of such a competition. We argue that the competition has no clear purpose, that its design prevents any useful outcome, and that such a competition is inappropriate given the current level of technology. We then speculate as to suitable alternatives to the Loebner prize.Comment: 20 page