Human-Machine Symbiosis


Human-machine symbiosis can be traced back to Licklider who in 1960 envisaged a situation where machines could work side by side with humans. Licklider’s vision was that humans and machines could be coupled together and work interactively. He stated the following:

Man-computer symbiosis is an expected development in cooperative interaction between men and electronic computers. It will involve very close coupling between the human and the electronic members of the partnership. The main aims are 1) to let computers facilitate formulative thinking as they now facilitate the solution of formulated problems, and 2) to enable men and computers to cooperate in making decisions and controlling complex situations without inflexible dependence on predetermined programs. In the anticipated symbiotic partnership, men will set the goals, formulate the hypotheses, determine the criteria, and perform the evaluations… Preliminary analyses indicate that the symbiotic partnership will perform intellectual operations much more effectively than man alone can perform them. (Licklider, 1960, p. 1).

The premise of this idea was that human intellect could be augmented and as a result human beings would be able to perform more challenging tasks beyond the limitations placed on them. In considering the aspect of augmenting human intellect even further, Engelbart and English (1968) came up with an augmentation system in the form of a computer-based multiconsole interactive display system. This is generally believed to have been the debut of the mouse, human-computer interaction, interactive computing, hypermedia, video teleconferencing[1], all mediums that have helped humans work and communicate much more effectively and interactively (Friedewald 2005).

Putting this into context, human-machine symbiosis can be understood as a technology that as Roy (2004) accords has the ability to be able to enhance and improve the human potential where human capacities are restricted. Therefore, such technologies will as Roy asserts “complement rather than replace human abilities” (2004, p. 1). He further views such interaction or interdependence of human and machine as an extension of the other, i.e. the technological machine as an extension of the human. Such symbiosis can be seen through wearable technologies, as suggested by Starner et al (1997), through assistive technologies such as discussed by Lay et al (2001) or through neural implants as explored by Saniotis (2009).

When considering Licklider’s visionary idea in the present day, it would appear that his vision has to some degree become a reality. For instance, technology has permeated modern society to an extent where it can be argued that users have become dependent and perhaps reliant to a large extent on technology. This may be in any number of ways and include the way they access information, conduct business as well as the way in which communication is conducted. However, as Foster (2007) suggests, although humans can now perform more complex computations much more than during Licklider’s time, there is still much work that needs to be undertaken with regard to human-machine symbiosis.

Hence, the continued growth and development of the technology to this day. Some of the developments are outlined in the application examples and areas given below:

Application Areas/Examples

This section outlines some examples and application areas of human-machine symbiosis. Research shows diverse application areas of the technology. For purposes of this exercise, five application examples are outlined:

i. Human-Machine Symbiosis in Medical Science

Human-machine symbiosis is being applied in medical science as a way to improve quality of life. The technology may be used to better the quality of life of people who may otherwise be disadvantaged due to for instance a physical disability. Research into this area can be seen in several examples such as in work being carried out by the Human Machine Symbiosis Lab and by other research work in programs such as the MIT 10x research program.

The Human Machine Symbiosis Lab[2] associated with Arizona State University is designing, developing and evaluating new human machine interfaces that can be applied in haptic user interfaces which is a field of R&D that relates to the sense of touch. The lab aims to incorporate psychophysics, biomechanics and neurology in its development of smart and effective haptic interfaces and devices. The initial target groups are the blind and patients suffering from Alzheimer’s disease. The intention is to stimulate and enhance the haptic memories of such group of patients. This is being done through surgical simulations. Another research project that has looked at human-machine symbiosis for medical science is the MIT’s 10x[3] research program whose objective was to magnify human abilities. The research program looked at a cross-section of application areas including aspects of memory in order to enhance and expand human cognitive abilities. The MIT 10x program has focused its research on physical disability by looking at bionic and robotics technologies which may be used as an extension of physically disabled body (Roy, 2004).

In addition to the above, other examples that may fall under this category are implants. Admittedly implants are not necessarily a new phenomenon particularly in the medical field when one considers the development of heart pacemaker’s in the 1960s or cochlear and cortical implants for the hearing and visually impaired respectively (EU, 2005). However, the continuing technological research advancements in brain or neural implants render this technology as emerging. Brain implants may be used for the treatment of memory loss, paralysis or similar other neural related condition.he brain implant is implanted in the brain where the device transmits signals to and from the brain (Stieglitz & Meyer, 2006).

ii. Human-Machine Symbiosis in Brain Computer Interfaces

This has some overlaps with neuroelectronics, particularly when one considers brain computer interface (BCI) or brain-computer symbiosis as captured by Schalk (2008). Aspects of this as covered in the neuroelectronics metavignette include the following:

BCIs, sometimes called brain-machine interfaces (BMIs), are an emerging neurotechnology that translates brain activity into command signals for external devices. Research on BCIs began in the 1970s at the University of California Los Angeles (UCLA). Researchers at UCLA also coined the term brain-computer interface. A BCI establishes a direct communication pathway between the brain and the device to be controlled. They are mainly being developed for medical reasons, because there is a societal demand for technologies which help to restore functions of humans with central nervous system (CNS) disabilities (Berger, 2007). Patients for whom a BCI would be useful usually have disabilities in motor function or communication. This could be (partly) restored by using a BCI to steer a motorized wheelchair, prosthesis, or by selecting letters on a computer screen with a cursor. Invasive or non-invasive electrodes are used to detect brain activity, which is subsequently translated by a signal processing unit into command signals for the external device. The most common BCI responds to specific patterns detected in spatiotemporal EEGs measured non-invasively from the scalp. Spatiotemporal EEGs can be controlled by imagining specific movements (Gasson & Warwick, 2007).

iii. Human-Machine Symbiosis in Human-Systems Integration for Optimal Decision Making.

The application example is highlighted in the database[4] and is according to the database entry potentially most suitable for people working in dynamic and complex environments such as air traffic controllers and nurses in busy hospitals. The technology and in this case the human systems intergration system can then be used to support decision making in such dynamic and complex environments. Human-systems integration considers personnel, training, system safety, health hazards and other human-centric issues in the design of the technologies the targeted audience will use. Cognitive and Organisational Systems Engineering (COSE), a Project at NICTA, is finding ways to model human-systems integration to support optimal decision-making in these sorts of environments, through the system development life-cycle. Innovative integrated processes and tools will be developed, initially to support people’s cognitive work in health and air traffic management environments, but later extended to other domains. The goal of the COSE project[5} is to develop better techniques and tools for evaluating the integration between people, the ICT systems that they use, and the environments in which they work.

iv. Human-Machine Symbiosis in Industry

Human-machine symbiosis offers an opportunity for effective and improved operations in industry through smart and intelligent applications. Lepratti (2006) has stated the following "An intelligent use of human knowledge and skills coupled with the qualities of robotic systems (such as flexibility, high speed and precision) lead to profitable synergetic effects. Hence, humans and robots should be seen as complementary elements. Robotic systems employed in manufacturing will assist the work of humans supporting—not replacing—them in carrying out various tasks through an intelligent interaction” (p.654).

v. Human-Machine Symbiosis in Entertainment

The technology is applicable in entertainment through for example interactive gaming (Tseng et al, 2006) or dance as demonstrated by Nahrstedt et al. (2007) in their discussion of tele-immersive environments. Another example that may be considered here are game worlds (such as Second Life) in which users have the ability to transcend the physical in virtual reality. The use of such technology provides a sense of reality as well as interaction between human and machine

Time Line

This is an ongoing development

Definition and Defining Features

Symbiosis is defined as:

A close, prolonged association between two or more different organisms of different species that may, but does not necessarily, benefit each member[6].

The above definition suggests that humans and machines can work together and interact to mutual benefit. However, this may not always be the case as such mutuality can mean that one agent benefits more than the other or indeed that the agents do not actually benefit from each other at all and instead bring potential harm. It is due to the latter that ethical issues may arise and therefore the need to understand the associated risks becomes important. These of course will be covered in the critical issues area. Looking at this definition of symbiosis, the implication is that the interaction between man and machine can have both a positive and negative effect. The positive effect is evident in how the machines improve and enhance human life while the negative aspects lie in the problems that the technology brings to its intended users.

Defining Features


One of the major defining characteristic of human-machine symbiosis is that of interaction. For humans and machines to mutually work together and be effective in for instance brain-computer interaction and/or in performing other highly challenging activities, interactivity is central to the technology.

Augmentation: In cases where the technology is used to improve and enhance memory and vision, the main defining feature is augmentation. As Greef et al (2007) argue in relation to augmented cognition, the aim is “the creation of adaptive human-machine collaboration that continually optmisises performance of the human-machine system” (p.1). By so doing, the assertion of Greef and colleagues is that such collaboration can overcome man’s limitations in human-machine processing.

Sensory perception to aide cognitive abilities: Interaction between the brain and the technology is possible with sensory perceptions. This allows technologies like robots to be cognizant of and execute a user’s needs. Kurzweil (2000) has written of how in the future neural implants will provide a range of sensory perceptions and sensations when the implants interact with virtual environments.

Relations to other Technologies

From the examples given above as well from some of the defining features looked at, it is clear that human-machine symbiosis is realed to, and overlaps with other technologies. These technologies include neuroelectronics, particularly when brain-computer interface technology is taken into consideration. There is an additional relationship between robotics and human-machine symbiosis as gathered from discussions on human-robot interaction (Lepratti, 2006) and (Lay et al, 2001) where robots are expected to play a significant part in industry as well as in medical science. In additional, another relationship can be seen in Artificial Intelligence which has many links with robotics. Lastly, human-machine symbiosis can also be said to be related to augmented reality. An example of this relation can be seen in Starner et al (1999, 1997).

Critical Issues

While acknowledging that new technologies in direct human-brain interaction may offer opportunities to have little to no invasive procedures, Schalk (2008) has stated that invasive procedures are likely to remain one of the critical issues in brain-computer symbiosis. In addition, safety and dependability have been identified as one of the issues when human-robot interaction is considered (De Santis & Siciliano, 2008).


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De Santis, A & Siciliano, B. (2008) Issues for Human-Robot Cooperation in Manufacturing Systems. Retrieved on 20 May, 2010, from

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European Union (2005) Aspects of ICT Implants in the Human Body. Opinion of the European Group on Ethics in Science and New Technologies to the European Commission. Retrieved on 25th May 2010, from

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Friedewald, M. (2005). The Continuous Construction of the Computer User: Visions and User Models in the History of Human-Computer Interaction. In Buurman, G.M. (ed.), Total Interaction: Theory and Practice of a New Paradigm: Basel/Berlin, pp. 26–41

Gasson, M. & Warwick, K. (2007). D12.1 Study On Emerging AmI Technologies. FIDIS – Future of Identity in the Information Society. [Scientific Report]

Greef, T., Dongen, K., Grootjen, M. & Lindenberg, J. (2007). Augmenting Cognition: Reviewing the Symbiotic Relation Between Man and Machine. In Foundations of Augmented Cognition. Springer Berlin / Heidelberg

Kurzweil, R. (2000). The age of spiritual machines: When computers exceed human intelligence. New York: Penguin.

Lay, K. et al. (2001). MORPHA: Communication and interaction with intelligent, anthropomorphic robot assistants. In Tagungsband Statustage Leitprojekte Mensch-Technik-Interaktion in der Wissensgesellschaft, Oktober 2001, Saarbrücken, Germany

Lepratti, R. (2006). Advanced & Human-Machine System for intelligent manufaturing: Some Issues for Employing Ontologies for Natural Language Processing. In Journal of Intelligent Manufacturing,Vol. 17, No. 6, 2006

Licklider, J. C.R. (1960) Man-Computer Symbiosis. In IRE Transactions on Human Factors in Electronics, Vol. HFE-1, p. 4-11. Retrieved on 10 May 2010, from

Nahrstedt, K. et al. (2007). Symbiosis of Tele-Immersive Environments with Creative Choreography. Retrieved on 21 May 2010 from

Roy, D. (2004) 10x: Human-machine symbiosis. BT Technology Journal, Vol. 22, No. 4, October 2004. Retrieved on 17 May 2010 from

Saniotis, A. (2009) Present and Future Developments in Cognitive Enhancement Technologies. In Journal of Futures Studies, Vol. 14, No. 1, p. 27–38. Retrieved on 22 May 2010 from,

Schalk, G. (2008) Brain-Computer Symbiosis. Retrieved on 18 May 2010, from

Starner, T. et al. (1997). Augmented reality through wearable computing. Presence, Special Issue on Augmented Reality. Vol. 6, No. 4, (1997

Starner, T. et al. (1999). Everyday-use Wearable Computers. In International Symposium on Wearable Computers, 1999.

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Tseng, K. et al (2006). Vision-Based Finger Guessing Game in Human Machine Interaction. In IEEE International Conference on Robotics and Biomimetics, 2006


[4] This is an ETICA database created to develop a list of technologies from difference sources which include government and scientific sources. It encompasses application examples, artefacts, technologies and the various sources that data has been derived from.