Building a conscious robot is a grand scientific and technological challenge. Debates about the possibility of conscious robots and the related positive outcomes and hazards for human beings are today no more confined to philosophical circles. Robot consciousness is a research field aimed to a unified view of approaches as cognitive robotics, epigenetic and affective robotics, situated and embodied robotics, developmental robotics, anticipatory systems, biomimetic robotics. Scholars agree that a conscious robot would completely change the current views on technology: it would not be an “intelligent companion” but a complete novel kind of artifact. Notably, many neuroscientists involved in the study of consciousness do not exclude this possibility. Moreover, facing the problem of consciousness in robots may be a major move on the study of consciousness in humans and animals.
The Frontiers Research Topic on consciousness in humanoid robots concerns the theoretical studies, the models and the case studies of consciousness in humanoid robots. Topics related to this argument are: – the needs of a body for robot consciousness; – robot self-consciousness; – the capability of a robot to reason about itself, its body and skills; – the episodic memory in a robot, i.e., the ability to take into account its operational life; – design strategies versus developmental approaches in assessing consciousness in a robot; – robot architectures candidates for consciousness; – symbolic versus neural networks representations in robot consciousness; – consciousness, theory of mind and emotions in a humanoid robot; – measurements and assessments of consciousness and self-consciousness in a robot; – ethical and trust issues in a conscious humanoid robot.
In his new book, Range: Why Generalists Triumph in a Specialized World,David J. Epstein investigates the significant advantages of generalized cognitive skills for success in a complex world. We’ve heard and read many praises for narrow expertise in both humans and AIs (Watson, Alpha Go, etc.). In both humans and AIs, however, narrow+deep expertise does not translate to adaptiveness when reality presents novel challenges, as it does constantly.
As you ingest this highly readable, non-technical book, please add your observations to the comments below.
If you are familiar with complex systems theorist Dr. Stuart Kauffman’s ideas you know he covers a broad range of disciplines and concepts, many in considerable depth, and with a keen eye for isomorphic and integrative principles. If you peruse some of his writings and other communications, please share with us how you see Kauffman’s ideas informing our focal interests: brain, mind, intelligence (organic and inorganic), and self-aware consciousness.
Do you find Kauffman’s ideas well supported by empirical research? Which are more scientific and which, if any, more philosophical? What intrigues, provokes, or inspires you? Do any of his perspectives or claims help you better orient or understand your own interests in our focal topics?
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Team Human by Douglas Rushkoff investigates the impacts of current and emerging technologies and digital culture on individuals and groups and seeks ways to evade or extract ourselves from their corrosive effects.
After you read the book, please post your thoughts as comments to this post or, if you prefer, as new posts. There are interviews and other resources about the book online. Feel free to recommend in the comments those you find meaningful. Also, the audiobook is available through the Albuquerque Public Library but may have a long wait queue (I’m aiming for a record number of ‘q’s in this sentence).
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We propose ‘multi-level evolution’, a bottom-up automatic process that designs robots across multiple levels and niches them to tasks and environmental conditions. Multi-level evolution concurrently explores constituent molecular and material building blocks, as well as their possible assemblies into specialized morphological and sensorimotor configurations. Multi-level evolution provides a route to fully harness a recent explosion in available candidate materials and ongoing advances in rapid manufacturing processes.
From this piece located at the publications page of the International Computer Science Institute. “Mathematical models help describe reality, but only by ignoring its inherent integrity.” Computers work on binary logic and the world is full of ‘noise.’ Hence computers, and mathematical models for that matter, can only approximate reality by eliminating that noise.
“Can a bunch of bits represent reality exactly, in a way that can be controlled and predicted indefinitely? The answer is no, because nature is inherently chaotic, while a bunch of bits representing a program can never be so, by definition.”
Which leads us to ask: “Are our mathematical models just a desperate, failed attempt to de-noise an otherwise very confusing, extremely blurred reality?”
So yes, math and computers are quite useful as long as we keep the above in mind instead of assuming they reveal reality as it is. And as long as we also search for that noisy humanity in the spaces between binary logic, which will never be revealed by math or computers alone.
Mark suggested this book as a future group reading and discussion and I agree. Rushkoff provides a very brief summary of his new book on the topic in the TED talk below. It starts with tech billionaires main concern being: Where do I build my bunker at the end of the world? So what happened to the idyllic utopias we thought tech was working toward, a collaborative commons of humanity? The tech boom became all about betting on stocks and getting as much money as possible for me, myself and I while repressing what makes us human. The motto became: “Human beings are the problem and technology is the solution.” Rushkoff is not very kind to the transhumanist notion of AI replacing humanity either, a consequence of that motto. He advises that we embed human values into the tech so that it serves us rather than the reverse.
Psychologist Robert Epstein, the former editor of Psychology Today, challenges anyone to show the brain processing information or data. The IP metaphor, he says, is so deeply embedded in thinking about thinking it prevents us from learning how the brain really works. Epstein also takes on popular luminaries including Ray Kurzweil and Henry Markram, seeing both exemplifying the extremes of wrongness we get into with the IP metaphor and the notion mental experience could persist outside the organic body.
Underlying our tech vision is a gnostic belief system of leaving the body behind, as it is an inferior biological system thwarting our evolution. Hence all the goals of downloading our supposed consciousness into a machine. It’s an anti-human and anti-environment religion that has no concern for either, imagining that tech is our ultimate savior.
And ironic enough, it’s a belief system that teamed up with the US human potential movement at Esalen. What started as an embodied based human potential program, with practices geared at integrating our minds with our bodies and the environment, got sidetracked by this glorious evolution beyond all that messy material and biological stuff.
And then there’s the devil’s bargain of this religion with our social media, like Facebook and Google, who use tech merely as a means of manipulating us for their own capitalistic purposes. Apparently it has been accepted that there is no alternative to capitalism, since the latter also assumes that humanity is strictly utilitarian and self-interested, the latter also being just mere algorithmic computations determined by an equally algorithmic ‘natural’ selection. Since tech can do all that better then what’s all the fuss?