Today I have the pleasure of attending the Posthuman
Resilience in Major Emergencies (PRiME) networking event organised by the OU,
UK. This is definitely a timely event as it launches a constructive idea
exchange with regard to what we need to think about to enable societies to be
resilient in case of major emergencies (natural and human disasters affecting
small to big regions). The main aim of the workshop is to bring together
researchers and stakeholders from a variety of fields within the future
technologies area.
The workshop focuses on emergency situations, particularly
in major events and disasters, which in today’s connected world require
sophisticated responses involving extraordinarily close collaboration between
humans and technologies. The concept of resilience has been identified as
encapsulating a highly desirable characteristic of both humans and technologies
in these settings. Although resilience has been the subject of extensive
research in various academic and technical domains, it needs to be thoroughly re-examined
in relation to the prospect of a post-human future, e.g. in 50 to 100 years, in
which human capacities may be manipulated and radically enhanced. If you are
interested in this challenge and have relevant ideas or expertise, you are
invited to join us in our upcoming workshop where the concept of resilience
will be a core aspect.
A posthuman approach to resilience might analyse networks of
which humans are only a part, or assemblages composed entirely of non-humans.
It may involve applying abstract concepts of resilience to humans and nonhumans
alike; or "pluralizing" the concept to acknowledge different ways in
which things or subjects can exhibit resilience. It may explore the
contribution of nonhuman actors to forms of stability traditionally viewed in
human terms, or seek greater recognition of diverse interests in being
resilient.
The day is filled mostly by 30 min keynotes on posthumanism,
resilience, human-machine interaction, communication, and robot technology.
Some first thoughts picked up while liveblogging:
Resilience some info (came in a bit after start of first
keynote, train travel).
From Mars exploration, space technologies, self-riding
rovers and cars. No external location info.
Use AL mapping area and computer vision & cameras. Mapping
the world in 3D, mapping where the rover is, and than plan.
Energy is limited: solar power in combination with battery.
Autonomous sensors will use battery power, the more watt’s used, the less
energy for moving around. Sometimes cheap sensors can be used, but sometimes
(e.g. challenges met) more expensive sensors need to be used. So what I tried
is modeling the terrain and looking at which type of sensors can be used. Where
the software is going to calculate which sensors can be used in terms of energy
investment. Anyway mapping the way as it is explored. In a GPS void environment
some mapping and exploration can be one, with additional energy saved. But mapping
has it limits as the exact photograph taken will provide detailed information,
but as soon as the video angle is different, different information will be
given. So, how can different pictures ensure accurate information, build from
different sensors. The mars technology is now used in tunnels, surveying
tunnels and mapping them. VR, AR tech coming from the 3D models sent out from
the tunnels, decreasing the risk for humans. But a major challenge is the data
coming out of these 3D models. Too much information to calculate. Deep learning
is an option, fueled by theoretical information, and lots of gaming industry
feedback. Steep and rapid change, every 6 months giant leaps forward. Using AI
to augment, improve and replace human actors. Current state of the art is
changing so rapidly, that it exceeds information coming out (papers, tech…). Up
to 2010 error rates were high, with deep learning, the errors have come down,
and very complex images the machines are classifying better than human beings
are doing; this can be used for any visual analysis at the moment and be used
to looking for information of interest.
Autonomous robotic for surveillance, that way minimize risk
for humans and visualise or provide detailed information, plus dealing with
problem of lots of data.
Another big problem is the human-machine interaction, as the technology (now) does not understand the human communication. The interface to communicate with human/machine.
(inge: makes me think off a lot of internet of things problems revolving on energy versus tech action. )
