Neuroethics

, Volume 2, Issue 3, pp 137–149 | Cite as

Brain to Computer Communication: Ethical Perspectives on Interaction Models

Original Paper

Abstract

Brain Computer Interfaces (BCIs) enable one to control peripheral ICT and robotic devices by processing brain activity on-line. The potential usefulness of BCI systems, initially demonstrated in rehabilitation medicine, is now being explored in education, entertainment, intensive workflow monitoring, security, and training. Ethical issues arising in connection with these investigations are triaged taking into account technological imminence and pervasiveness of BCI technologies. By focussing on imminent technological developments, ethical reflection is informatively grounded into realistic protocols of brain-to-computer communication. In particular, it is argued that human-machine adaptation and shared control distinctively shape autonomy and responsibility issues in current BCI interaction environments. Novel personhood issues are identified and analyzed too. These notably concern (i) the “sub-personal” use of human beings in BCI-enabled cooperative problem solving, and (ii) the pro-active protection of personal identity which BCI rehabilitation therapies may afford, in the light of so-called motor theories of thinking, for the benefit of patients affected by severe motor disabilities.

Keywords

Brain-computer interfaces BCI communication protocol Autonomy Responsibility Personal identity persistence Human-machine cooperative problem solving Sub-personal psychology 

Notes

Acknowledgments

I wish to thank an anonymous reviewer, Giuseppe Trautteur, Federica Lucivero, and Giovanni Boniolo for helpful and stimulating comments. I benefited from discussions on BCI systems and ethics with Febo Cincotti, Edoardo Datteri, José del R. Millán, Donatella Mattia, Stefano Rodotà, and Matteo Santoro.

References

  1. 1.
    Birbaumer, N., N. Ghanayim, T. Hinterberger, B. Kotchoubey, A. Kuebler, J. Perelmouter, E. Taub, and H. Flor. 1999. A spelling device for the paralyzed. Nature 398:297–298.CrossRefGoogle Scholar
  2. 2.
    Hochberg, L.R., M.D. Serruya, G.M. Friehs, J.A. Mukand, M. Saleh, A.H. Caplan, A. Branner, D. Chen, R.D. Penn, and J.P. Donoghue. 2006. Neuronal ensemble control of prosthetic devices by a human with tetraplegia. Nature 442:164–171.CrossRefGoogle Scholar
  3. 3.
    Birbaumer, N. 2006a. Breaking the silence: Brain-computer interfaces for communication and motor control. Psychophysiology 43:517–532.CrossRefGoogle Scholar
  4. 4.
    Wolpaw, J.R., N. Birbaumer, D.J. McFarland, G. Purtscheller, and T.M. Vaughan. 2002. Brain-computer interfaces for communication and control. Clinical Neurophysiology 113:767–791.CrossRefGoogle Scholar
  5. 5.
    Millán, J. del R., F. Renkens, J. Mouriño, and W. Gerstner. 2004. Brain-actuated interaction. Artificial Intelligence 159:241–259.CrossRefGoogle Scholar
  6. 6.
    Galán, F., M. Nuttin, E. Lew, P.W. Ferrez, G. Vanacker, J. Philips, and J. del. R. Millán. 2008. A brain-actuated wheelchair: Asynchronous and non-invasive brain-computer interfaces for continuous control of robots. Clinical Neurophysiology 119:2159–2169.CrossRefGoogle Scholar
  7. 7.
    Friedman, D., R. Leeb, L. Dikovsky, M. Reiner, G. Pfurtscheller, and M. Slater. 2007. Controlling a virtual body by thought in a highly immersive virtual environment, in GRAPP 2007, Barcelona, Spain, 83–90.Google Scholar
  8. 8.
    Nijholt, A., D. Tan, A. Brendan, J. del R. Millán, B. Graimann. 2008. Brain-computer interfaces for HCI and games, in Proceedings of CHI08, ACM, pp. 3225–3228.Google Scholar
  9. 9.
    Gerson, A.D., L.C. Parra, and P. Sajda. 2006. Cortically coupled computer vision for rapid image search. IEEE Transactions on Neural Systems and Rehabilitation Engineering 14(2):174–179.CrossRefGoogle Scholar
  10. 10.
    Yahud, S., and N.A. Abu Osman. 2007. Prosthetic hand for the brain-computer interface system. IFMBE Proceedings 15:643–646. Springer, Berlin.CrossRefGoogle Scholar
  11. 11.
    Fenton, A., and S. Alpert. 2008. Extending our view on using BCIs for locked-in syndrome. Neuroethics 1:119–132.CrossRefGoogle Scholar
  12. 12.
    Birbaumer, N. 2006b. Brain-computer interface research: Coming of age. Clinical Neurophysiology 117:479–483.CrossRefGoogle Scholar
  13. 13.
    Buxton, R.B. 2002 An introduction to functional magnetic resonance imaging: Principles and techniques. Cambridge UP.Google Scholar
  14. 14.
    Linderman, M. D., G. Santhanam, C.T. Kemere, V. Gilja, S. O’Driscoll, B.M. Yu, A. Afshar, S.I. Ryu, K.V. Shenoy, T.H. Meng. 2008. Signal Processing Challenges for Neural Prosthetes. A Review of State-of-Art Systems, IEEE Signal Processing Magazine 18.Google Scholar
  15. 15.
    Millán, J. del R. 2004. On the Need for On-line Learning in Brain-Computer Interfaces. International Joint Conference on Neural Networks.Google Scholar
  16. 16.
    Vapnik, V. 2000. The nature of statistical learning theory. 2nd ed. New York: Springer.Google Scholar
  17. 17.
    Reath, A. 1999. Autonomy, ethical. In Routledge encyclopedia of philosophy, ed. E. Craig. London: Routledge.Google Scholar
  18. 18.
    MacKay, D. 2003. Information theory, inference, and learning algorithms. Cambridge UP.Google Scholar
  19. 19.
    Arkin, R. 1998. Behavior-based robotics. Cambridge: MIT.Google Scholar
  20. 20.
    Nehmzow, U. 2006. Scientific methods in mobile robotics. London: Springer.Google Scholar
  21. 21.
    Matthias, A. 2004. The responsibility gap: Ascribing responsibility for the actions of learning automata. Ethics and Information Technology 6:175–183.CrossRefGoogle Scholar
  22. 22.
    Miall, R.C., and D.M. Wolpert. 1996. Forward models for physiological motor control. Neural Networks 9:1265–1279.CrossRefGoogle Scholar
  23. 23.
    Kawato, M. 1999. Internal models for motor control and trajectory planning. Current Opinion in Neurobiology 9:718–727.CrossRefGoogle Scholar
  24. 24.
    Bufalari, S., F. Cincotti, F. Babiloni, L. Giuliani, M.G. Marciani, and D. Mattia. 2007. EEG patterns during motor imagery based volitional control of a brain computer interface. International Journal of Electromagnetism 9:214–219.Google Scholar
  25. 25.
    Dennett, D. 1969. Content and consciousness. London: Routledge & Kegan Paul.Google Scholar
  26. 26.
    Hornsby, J. 2000. Personal and Sub-Personal: A Defence of Dennett’s Original Distinction. In New Essays on Psychological Explanation, Special Issue of Philosophical Explorations, eds. M. Elton, and J. Bermudez, 6–24.Google Scholar
  27. 27.
    Kanizsa, G. 1955. Margini quasi-percettivi in campi con stimolazione omogenea. Rivista di Psicologia 49:7–30.Google Scholar
  28. 28.
    Philiastides, M.G., and P. Sajda. 2006. Temporal characterization of the neural correlates of perceptual decision making in the human brain. Cerebral Cortex 16:509–518.CrossRefGoogle Scholar
  29. 29.
    Owen, A.M., M.R. Coleman, M. Boly, M.H. Davis, S. Laureys, and J.D. Pickard. 2006. Detecting awareness in the vegetative state. Science 313:1402.CrossRefGoogle Scholar
  30. 30.
    Kant, I. 1983. Grounding for the Metaphysics of Morals. In Kants Ethical Philosophy, ed. J.W. Ellington. Indianapolis: Hackett.Google Scholar
  31. 31.
    Millán, J. del R. 2007. Tapping the mind or resonating minds? In European visions for the knowledge age, a quest for new horizon in the information society, ed. P.T. Kidd, 125–132. Macclesfield: Cheshire Henbury.Google Scholar
  32. 32.
    Farah, M.J. 2002. Emerging ethical issues in neuroscience. Nature Neuroscience 5:1123–1129.CrossRefGoogle Scholar
  33. 33.
    Nordmann, A. 2007. If and then: A critique of speculative nanoethics. Nanoethics 1:31–46.CrossRefGoogle Scholar
  34. 34.
    Warwick, K. 2003. Cyborg morals, cyborg values, cyborg ethics. Ethics and Information Technology 5:131–137.CrossRefGoogle Scholar
  35. 35.
    Tamburrini, G. 2006. Artificial intelligence and Popper’s solution to the problem of induction. In Karl Popper: A centenary assessment. Metaphysics and epistemology, vol. 2, eds. I. Jarvie, K. Milford, and D. Miller, 265–284. London: Ashgate.Google Scholar
  36. 36.
    Santoro, M., D. Marino, and G. Tamburrini. 2008. Robots interacting with humans. From epistemic risk to responsibility. Artificial Intelligence and Society 22:301–314.Google Scholar
  37. 37.
    Christman, J. 2003. Autonomy in moral and political philosophy. Stanford encyclopedia of philosophy, http://plato.stanford.edu/entries/autonomy-moral/
  38. 38.
    Hansson, S.O. 2007. The ethics of enabling technology. Cambridge Quarterly of Healthcare Ethics 16:257–267.CrossRefGoogle Scholar
  39. 39.
    Merkel, R., G. Boer, J. Fegert, T. Galert, D. Hartmann, B. Nuttin, and S. Rosahl. 2007. Intervening in the Brain. Changing psyche and society. Berlin: Springer.Google Scholar
  40. 40.
    Lucivero, F., and G. Tamburrini. 2008. Ethical monitoring of brain-machine interfaces, A note on personal identity and autonomy. AI and Society 22:449–460.CrossRefGoogle Scholar
  41. 41.
    Reynolds, C., and R.W.Picard. 2004. Affective sensors, privacy, and ethical contracts. Proceedings of CHI04, ACM, 1103–1106.Google Scholar
  42. 42.
    Freud, S. 1933. New introductory lectures on psycho-analysis. The standard edition of the complete psychological works of Sigmund Freud, vol. 22, 1–182. London: Hoghart.Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  1. 1.Dipartimento di Scienze fisicheUniversità di Napoli Federico IINapoliItaly

Personalised recommendations