Cognitive Nanorobots for Pathology Resoulution and Enhancement

One way to think of cognitive nanorobots is as a subset of medical nanorobots, meaning nanorobots for use in the body related to medical purposes, in this case, neural processes. Nanorobots are tiny computing machines at the nanoscale that can perform a variety of operations within the human body and beyond.

In the strictest sense, nanorobots are still conceptual: the Oxford English Dictionary definition of nanorobots (nanobots) is hypothetical very small (nanoscale) self-propelled machines, especially ones that have some degree of autonomy and can reproduce. While this definition that includes autonomy and reproducibility is one for the farther future, in reality there are a number of nanoscale inorganic objects that have already been in use in the body for some time in a variety of medical applications. So far, the activity scope of these nano-objects has been pathology resolution, but the same kinds of techniques and characterization of the underlying biological processes could be explored for enhancement purposes.

The most developed area of nanomedicine is nanoparticle drug delivery (designed particles that disgorge cargo in cellular destinations per simple onboard logic instructions) and other therapeutic techniques, followed by nano-diagnostics, and nano-imaging (like quantum dot imaging) (Boysen 2014). Some of the more recent interesting applications are nanosponge waste soak-up and biomimetic detoxification (Hu 2013), optogenetics (controlling the brain with light) (Klapoetke 2014), and neural dust brain sensors that might be able to read whole sections of brain activity externally (Seo 2013). The current status of the development of neural nanomedicine is well covered in the scientific literature (Provenzale 2010, Kateb 2013, Schulz 2009, Mavroidis 2014, and Boehm 2013).

Thinking in the longer-term, Robert Freitas has designed several classes of medical nanorobots such as respirocytes, clottocytes, vasculoids, and microbivores that could perform a variety of biophysical clean-up, maintenance, and augmentation functions in the body (Freitas 2003). One example of neural nanorobotic clean-up is autonomous diamondoid “defuscin” class nanodevices. These are conceptual nanodevices designed to eliminate the residual lipofuscin waste granules in lysosomes (the ‘trash compactor’ of the cell) that the body cannot fully digest.

References:
Boehm, F. (2013). Nanomedical Device and Systems Design: Challenges, Possibilities, Visions. New York, NY: CRC Press, especially Chapter 17: Nanomedicine in Regenerative Biosystems, Human Augmentation, and Longevity, 654-722.
Boysen, E. (2014). Nanotechnology in Medicine – Nanomedicine. UnderstandingNano.com. Retrieved from http://www.understandingnano.com/medicine.html.
Freitas, R., Jr. (2003). Nanomedicine, Vol. IIA: Biocompatibility. Austin, TX: Landes Bioscience.
Kateb, B. & Heiss, J.D. (Eds). (2013). The Textbook of Nanoneuroscience and Nanoneurosurgery. New York, NY: CRC Press.
Klapoetke, N.C., Murata, Y., Kim, S.S., Pulver, S.R., Birdsey-Benson, A., et al. (2014). Independent Optical Excitation of Distinct Neural Populations. Nature Methods, 11, 338–346.
Mavroidis, C. (2014). Nano-Robotics in Medical Applications: From Science Fiction to Reality, Northeastern University. Retrieved from http://www.albany.edu/selforganization/presentations/2-mavroidis.pdf.
Provenzale, J.M. & Mohs, A.M. (2010). Nanotechnology in Neurology: Current Status and Future Possibilities. US Neurology, 6(1), 12-17.
Seo, D., Carmena, J.M., Rabaey, J.M., Alon, E., Maharbiz, M.M. (2013). Neural Dust: An Ultrasonic, Low Power Solution for Chronic Brain-Machine Interfaces. arXiv, 1307.2196 [q-bio.NC]. Retrieved from http://arxiv.org/abs/1307.2196.
Schulz, M.J., Shanov, V.N., Yun, Y. (Eds.). (2009). Nanomedicine Design of Particles, Sensors, Motors, Implants, Robots, and Devices. New York, NY: Artech House.

Machine Ethics Interfaces

Machine ethics is a term used in different ways. The basic use is in the sense of people attempting to instill some sort of human-centric ethics or morality in the machines we build like robots, self-driving vehicles, and artificial intelligence (Wallach 2010) so that machines do not harm humans either maliciously or unintentionally. This trend may have begun with Asimov’s Three Laws of Robotics. However, there are many different philosophical and other issues with this definition of machine ethics, including the lack of grounds for anthropomorphically assuming that a human ethics would be appropriate for a machine ethics, beyond the context of human-machine interaction.

There is another broader sense of the term machine ethics which means any issue pertaining to machines and ethics, including how a machine ethics could be articulated by observing machine behavior, and (in a Simondonian sense (French philosopher Gilbert Simondon)) how different machine classes might evolve their own ethics as they themselves develop over time.

There is yet a third sense of the term machine ethics - to contemplate human-machine hybrids, specifically how humans augmented with nanocognition machines might trigger the development of new human ethical paradigms, for example an ethics of immanence that is completely unlike traditional ethical paradigms and allows for a greater realization of human capacity.

Machine ethics interfaces then, are interfaces (software modules for communication between users and technologies (machines, devices, software, nanorobots)) with ethical aspects deliberately designed into them. This could mean communication about ethical issues, user selection of ethically-related parameters, ethical issues regarding machine behavior, and ethical dimensions transparently built into the technology (like a kill switch in the case of malfunction). Machine ethics interfaces are the modules within machines that interact with living beings regarding ethical issues, pertaining to the ethics of machine behavior or the ethics of human behavior

Definitions:
Machine Ethics: 1) (conventional) technology designers attempting to incorporate models of human-centric morality into machines like robots, self-driving vehicles, and artificial intelligence to prevent humans from being harmed either maliciously or unintentionally, 2) any issue pertaining to machines and ethics, 3) the possibility of new ethical paradigms arising from human augmentation and human-machine hybrids.

Machine Ethics Interfaces: Interfaces (software modules for communication between users and technologies (machines, devices, software, nanorobots)) with ethical aspects deliberately designed into them. This could mean communication about ethical issues, user selection of ethically-related parameters, and ethical dimensions transparently built into the technology (like a kill switch in the case of malfunction).

Reference: 
Wallach, W. (2010). Moral Machines: Teaching Robots Right from Wrong. Oxford, UK: Oxford University Press.