9,725 research outputs found
Algorithm and Human Creativity: Threats or Opportunity? A Literature Review
We explore the move from a mechanical vision of Artificial Intelligence (AI) to a systemic
vision of Intelligence Augmentation (IA) (Barile et al., 2018, 2019, 2020, 2021;
Navarrini, 2020; Chiriatti, 2019). AI assumes the role of empowered intelligence (IA)
as it is capable of expressing a capacity for modeling integration of experiences, knowledge
and emotions in conditions of strong uncertainty (Barile et al., 2021; Hagel,
2021). But in a world where the nature of machine learning is changing so rapidly,
does technology empower or annihilate creativity? The aim of the paper is to draw
attention to the impact that disruptive technology has on human creative processes.
How might progress in AI affect Human Creativity (HC)?We propose a literature review
to better understand both trends and gaps
Cyborgs as Frontline Service Employees: A Research Agenda
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Purpose
This paper identifies and explores potential applications of cyborgian technologies within service contexts and how service providers may leverage the integration of cyborgian service actors into their service proposition. In doing so, the paper proposes a new category of âmeldedâ frontline service employees (FLEs), where advanced technologies become embodied within human actors. The paper presents potential opportunities and challenges that may arise through cyborg technological advancements and proposes a future research agenda related to these.
Design/methodology
This study draws on literature in the fields of services management, Artificial Intelligence [AI], robotics, Intelligence Augmentation [IA] and Human Intelligence [HIs] to conceptualise potential cyborgian applications.
Findings
The paper examines how cyborg bio- and psychophysical characteristics may significantly differentiate the nature of service interactions from traditional âunenhancedâ service interactions. In doing so, we propose âmeldingâ as a conceptual category of technological impact on FLEs. This category reflects the embodiment of emergent technologies not previously captured within existing literature on cyborgs. We examine how traditional roles of FLEs will be potentially impacted by the integration of emergent cyborg technologies, such as neural interfaces and implants, into service contexts before outlining future research directions related to these, specifically highlighting the range of ethical considerations.
Originality/Value
Service interactions with cyborg FLEs represent a new context for examining the potential impact of cyborgs. This paper explores how technological advancements will alter the individual capacities of humans to enable such employees to intuitively and empathetically create solutions to complex service challenges. In doing so, we augment the extant literature on cyborgs, such as the body hacking movement. The paper also outlines a research agenda to address the potential consequences of cyborgian integration
ARIGAN: Synthetic Arabidopsis Plants using Generative Adversarial Network
In recent years, there has been an increasing interest in image-based plant
phenotyping, applying state-of-the-art machine learning approaches to tackle
challenging problems, such as leaf segmentation (a multi-instance problem) and
counting. Most of these algorithms need labelled data to learn a model for the
task at hand. Despite the recent release of a few plant phenotyping datasets,
large annotated plant image datasets for the purpose of training deep learning
algorithms are lacking. One common approach to alleviate the lack of training
data is dataset augmentation. Herein, we propose an alternative solution to
dataset augmentation for plant phenotyping, creating artificial images of
plants using generative neural networks. We propose the Arabidopsis Rosette
Image Generator (through) Adversarial Network: a deep convolutional network
that is able to generate synthetic rosette-shaped plants, inspired by DCGAN (a
recent adversarial network model using convolutional layers). Specifically, we
trained the network using A1, A2, and A4 of the CVPPP 2017 LCC dataset,
containing Arabidopsis Thaliana plants. We show that our model is able to
generate realistic 128x128 colour images of plants. We train our network
conditioning on leaf count, such that it is possible to generate plants with a
given number of leaves suitable, among others, for training regression based
models. We propose a new Ax dataset of artificial plants images, obtained by
our ARIGAN. We evaluate this new dataset using a state-of-the-art leaf counting
algorithm, showing that the testing error is reduced when Ax is used as part of
the training data.Comment: 8 pages, 6 figures, 1 table, ICCV CVPPP Workshop 201
AI Extenders: The Ethical and Societal Implications of Humans Cognitively Extended by AI
Humans and AI systems are usually portrayed as separate sys- tems that we need to align in values and goals. However, there is a great deal of AI technology found in non-autonomous systems that are used as cognitive tools by humans. Under the extended mind thesis, the functional contributions of these tools become as essential to our cognition as our brains. But AI can take cognitive extension towards totally new capabil- ities, posing new philosophical, ethical and technical chal- lenges. To analyse these challenges better, we define and place AI extenders in a continuum between fully-externalized systems, loosely coupled with humans, and fully-internalized processes, with operations ultimately performed by the brain, making the tool redundant. We dissect the landscape of cog- nitive capabilities that can foreseeably be extended by AI and examine their ethical implications. We suggest that cognitive extenders using AI be treated as distinct from other cognitive enhancers by all relevant stakeholders, including developers, policy makers, and human users
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Verbal analogy problem sets: An inventory of testing materials.
Analogical reasoning is an active topic of investigation across education, artificial intelligence (AI), cognitive psychology, and related fields. In all fields of inquiry, explicit analogy problems provide useful tools for investigating the mechanisms underlying analogical reasoning. Such sets have been developed by researchers working in the fields of educational testing, AI, and cognitive psychology. However, these analogy tests have not been systematically made accessible across all the relevant fields. The present paper aims to remedy this situation by presenting a working inventory of verbal analogy problem sets, intended to capture and organize sets from diverse sources
Augmented reality meeting table: a novel multi-user interface for architectural design
Immersive virtual environments have received widespread attention as providing possible replacements for the media and systems that designers traditionally use, as well as, more generally, in providing support for collaborative work. Relatively little attention has been given to date however to the problem of how to merge immersive virtual environments into real world work settings, and so to add to the media at the disposal of the designer and the design team, rather than to replace it. In this paper we report on a research project in which optical see-through augmented reality displays have been developed together with prototype decision support software for architectural and urban design. We suggest that a critical characteristic of multi user augmented reality is its ability to generate visualisations from a first person perspective in which the scale of rendition of the design model follows many of the conventions that designers are used to. Different scales of model appear to allow designers to focus on different aspects of the design under consideration. Augmenting the scene with simulations of pedestrian movement appears to assist both in scale recognition, and in moving from a first person to a third person understanding of the design. This research project is funded by the European Commission IST program (IST-2000-28559)
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