Welcome to the second issue of Volume 2 of the Journal of Disability Research (JDR). The aim of JDR is clearly focused on developing innovation and insight that will enhance the lives of those living with disabilities, in whatever form this may take. When we originally set up the journal, we keenly anticipated submissions from a wide variety of sources. It is therefore interesting to observe that, mirroring the rise of artificial intelligence (AI) as both a talking point in much of our modern discourse and as a tool of practical application for humanity, we see so many of these papers harnessing the power of AI to address important applications that can support and enhance the daily living for those living with disabilities, ranging from sign language to autism.
While many aspects of modern AI draw inspiration from natural phenomena, whether it is the perceptron mimicking the function of the neuron as the basic building block of much of our deep learning technology or human-in-the-loop training, otherwise known to humanity simply as “school,” there is clearly much to learn from humans and other natural structures and behaviours. It is therefore gratifying to see so many of our authors drawing on processes that draw their inspiration from the natural world, whether it be avian-inspired behaviours for decision-making, insects or aquatic behaviours, to arbitrarily mention some examples. The examples in the following pages demonstrate that the development of the AI apprentice still has much to learn from its human master and the natural world in which it finds itself deployed. I look forward to seeing and learning about these exciting and ever-growing developments as they unfold over the coming years.
Finally, I would like to acknowledge the efforts and excellent work of our contributor authors, the diligent work of our review panel and the vital and excellent organisational work of our back-room team at ScienceOpen. All have been key in the development of this second edition, and to all of whom I say: thank you; your efforts are appreciated.
Kevin Wells, e-mail: k.wells@123456surrey.ac.uk
ORCID: https://orcid.org/0000-0002-4658-8060
September 2023
Centre for Vision, Speech & Signal Processing
University of Surrey