BEYOND HIGH TECH: TOWARDS CONSCIOUSNESS TECHNOLOGIES

by Dr. Dean I. Radin

ABSTRACT

Advancements in human-machine interaction technologies reveal a growing trend towards increasingly intimate modes of communion. The trend suggests that a new mode of deep interdependence may soon arise ? technologies of direct mind-machine interaction. Based upon what is presently a little-known and poorly understood laboratory curiosity, new technologies will emerge that directly couple human thought with the accuracy, memory, and calculating speed of computers, and at the same time extend "human qualities" such as intuition and emotion into computers. This paper discusses why we are much closer to developing mind-machine or consciousness technologies than many people realize.

BEYOND HIGH TECHNOLOGY

There is a fast-growing trend in human-computer interaction (HCI) theory and practice: The evolution is away from isolated telephones and computers and towards a more intimate union among people and a host of info/communication technologies. In this paper I propose that this developing interdependence within HCI may soon extend to realms previously imagined only in science fiction. I shall call this "deep interdependence."

Deep interdependence refers to advances in hardware used to couple people and machines. The evolution from keyboards, to pointing devices, eyetrackers, virtual displays, speech and gesture understanding, and even brainwave analyzers, shows that HCI development is continuing to blur the boundaries between humans and machines.

In this paper, I envision a time when we shall witness a profound blurring - a subtle yet direct interaction between mind and the operation of machines. This will be accomplished without deciphering brainwave or other conventional physiological signals, as is currently being explored [1]. Instead (dodging the debate on monism vs. dualism) I mean the "ghost in the machine," that is, machines that respond to and directly interact with human consciousness.

I suggest that these direct interactions between mind and machine are even now associated with rare, spontaneous computer failures. I also suggest that what is currently viewed as annoying or delightful coincidences - depending on whether your machine mysteriously fails or recovers at precisely the right (or wrong) time - will eventually be harnessed into a new technology of direct mind-machine interaction (DMMI).

DMMI technologies offer the promise of solving several problems that are presently intractable in economic or human terms. And, although it may seem unwarranted at this point, I suggest that primitive versions of these DMMI technologies can be built today. Before discussing a few potential DMMI applications, I will first review why I propose what, at first glance, surely seems like unwarranted speculation.

BACKGROUND: WHY DO SYSTEMS FAIL?

Considering the interdependence of human activities and computer-based technologies in virtually all domains of modern life, it has become vitally important to understand why these systems sometimes fail [2,3]. Great strides have been taken in the design of fault-tolerant computers [4], and causes of the great majority of computer system failures can now be traced to either human factors or machine factors. Human factors include poor user interface design, stressful work environments, logical and functional design errors, and software bugs [5]. Machine factors include circuit board failures, power surges, and electromagnetic interference [6-7].

When failure categories fail

However, it is not always possible to assign failures to known categories. While some unexplained failures can undoubtedly be resolved with sufficient detective work, as computer systems become more complex, distributed, and interdependent, assigning the ultimate cause of a failure becomes much more difficult [8-9]. Indeed, non-linear dynamic systems theory indicates that there are severe limits on our ability to predict the future of completely deterministic systems, including computers [10-11]. Even redundant, fault-tolerant computer systems sometimes fail in mysterious ways [12]. Therefore, besides examining the known categories of human and machine factors for possible sources of system failures, it is also productive to explore a less well-understood intermediary: gremlins.

Gremlins?

Some people are renowned for their ability to fix machines. Others are prohibited from even being in proximity to electronic equipment during important demonstrations, for fear that the equipment will fail. Marks and Kammann [12] refer to this phenomenon as the "gremlin effect." In fact, the apparent tendency of things to go wrong at the worst possible time is so prevalent that Murphy's Law is half-seriously regarded as a "first principle" in engineering and scientific circles. Many such superstitions undoubtedly arise as a result of psychological factors such as selective human memory, and some are related to factors such as personality traits associated with high versus low accident involvement or personality mismatches between system designers and end-users [13-15].

However, after sifting through all the odd coincidences and unexplained glitches, a residue of anecdotes and a growing body of laboratory research suggests that the lab lore may arise from something else.

Something else

Among the many anecdotes about unusual human-machine interactions, Gamow describes the "Pauli Effect" as follows:

It is well known that theoretical physicists are quite inept in handling experimental apparatus; in fact, the standing of a theoretical physicist is said to be measurable in terms of his ability to break delicate devices merely by touching them. By this standard, Wolfgang Pauli was a very good theoretical physicist; apparatus would fall, break, shatter or burn when he merely walked into a laboratory. [16]

Other experimenters, such as Edison, were legendary for their ability to get complex laboratory apparatus working with extraordinary speed [17].

Such anecdotes, as well as dozens of others that arise in every technical environment, give life to the nervous laughter associated with Murphy's Law. Can such things be explained? Are they related to what I have called DMMI effects? When I was with AT&T Bell Laboratories in the early 1980's, I decided to explore these questions by putting Murphy's Law to the test.

EMPIRICAL EVIDENCE

A thought experiment

How can we test if human thought (intention, will, wishes) and computer operations are deeply interdependent? Specifically, how can we objectively test whether conscious mental intention interacts with sensitive electronic circuits such as those found in computers?

Consider the following thought experiment: An electronic circuit is devised which produces sequences of random bits, similar to circuits used in electronic gambling games and digital encryption key generators. The source of randomness in the circuit is either electronic noise or radioactive decay, as both provide truly random events.

The device is designed to generate 100 bits when a button is pressed. As each bit is generated, it is matched against an alternating "target" bit, i.e., 0 1 0 1.... (Alternating the target bit eliminates possible first-order biases within the generator from introducing artifacts into the experimental results.) When a generated random bit matches the target bit, a counter increments, and at the end of the 100 bit sequence, a display shows the number of matches, or hits. Chance expectation predicts that the displayed number of hits will be 50 with a standard deviation of 5.

Now you ask a person to do three things: First, simply press the button and wish that the displayed number is greater than 50. This is called a trial. On the second trial, the subject wishes for the number to be less than 50, and on the third trial, the subject just presses the button and thinks about some distracting task as a control. This sort of "tri-polar" protocol is repeated thousands of times with many different subjects, and the outcome is evaluated statistically to see if the cumulative wishes are associated with biases in the electronic device's output.

To avoid misunderstandings, I must emphasize that the person and the machine are not connected in any way, nor is the machine deciphering the subject's brainwaves or physiological responses.

Experimental results

Experiments like those described above had been investigated by a number of previous researchers (mostly physicists), including Helmut Schmidt, Hal Puthoff, Ed May, and Robert Jahn. I launched an independent replication, and eventually conducted a total of 45 such experiments at AT&T Bell Labs between 1980 to 1985, using experimental protocols and electronic devices like those described above [18,19], and using volunteers from work as experimental subjects. Thirteen of these experiments were significant at the p = .05 level, resulting in an exact binomial probability of p = 2.33 ? 10-8. Similarly conducted control series, using the same equipment but under a protocol where no one wished for any given outcome, produced null results.

From 1985 to 1989, while working first at SRI International and later at Princeton University, I had the opportunity to conduct several additional experiments using different sources of randomness and new experimental protocols [20,21]. These experiments also produced statistically significant results, confirming my previous observations. A decade of research demonstrated to my satisfaction that under strictly controlled conditions one could show that mental intention was predictably correlated with the behavior of a machine. In other words, Murphy's Law seemed to be more than mere superstition.

As a set of observations by a single researcher, these results were intriguing (especially to me), but could not count as conclusive in any formal scientific sense. This is not because the experiments were methodologically inadequate, but because the name of the game in science is independent replication and consensus agreement. In addition, in controversial realms where unconscious biases may sway one's judgment, it is advisable to consider the expert opinions of independent scientific review boards. In other words, although I accepted my

own data, I found it difficult to fully acknowledge the implications of those data unless I had a good reason to believe that my results were not an isolated case.

Expert opinion

In searching for the opinions of scientific review boards, I discovered that because of the possible strategic implications of DMMI phenomena, experiments in this realm had been reviewed in depth during the decade of the 1980's by four separate US government-sponsored scientific review boards. These reviews were conducted by the US Congressional Research Service, the US Army Research Institute, the US National Research Council, and the Congressional Office of Technology Assessment [22-27]. All four committees agreed that the evidence for DMMI merited serious attention by the scientific community, and suggested, as the Congressional Research Service put it, the existence of "an interconnectiveness of the human mind with other minds and with matter." [22]

The four committees disagreed about the extent to which these experiments were independently replicable, about potential artifacts and flaws in some experiments, and about the degree to which selective reporting practices may have inflated the overall estimate of success.

A meta-analysis is born

To help resolve the issues raised by the four scientific review boards, a colleague (Roger Nelson) and I conducted a quantitative meta-analysis of these experiments [28]. A meta-analysis is to a body of empirical data as a trial is to a single experiment. That is, a meta-analysis is an integrative review of all experiments that study the same effect or hypothesis. In essence, the analyst combines apples and oranges (different experiments) because she is interested in studying fruit (all experiments testing the same hypothesis). Because a meta-analysis is concerned with the actual outcome of an experiment, rather than simply whether it was reported as significant or nonsignificant, it allows one to quantitatively determine replication rates, to judge the relationship between study outcomes and

experimental quality, and to assess the plausibility that selective reporting might account for the observed end-result [28]. Meta-analyses are now widely accepted in the social, behavior, and medical sciences as valuable quantitative tools for summarizing large bodies of empirical evidence.

The meta-analysis retrieved 152 experimental reports from refereed journal articles, technical reports, dissertations, conference proceedings, and unpublished manuscripts. These reports were written by 68 principal investigators, representing 15 laboratories in 8 countries, who together published a total of 597 experiments, consisting of over one billion "mentally influenced" bits, and 235 control studies, consisting of over two billion bits.

These experiments were quietly conducted beginning in the mid-1950's at US government laboratories, Boeing Laboratories, AT&T Bell Laboratories, MIT, Princeton University, University of Edinburgh, and many other industrial and academic labs [e.g., 30-32]. Most of the experiments were conducted by physicists interested in whether conscious observation might affect quantum states and by psychologists interested in studying the nature of human intention.

The overall results showed that control data conformed to theoretical chance expectation, but the experimental data was highly significant, equivalent to a 15 standard error shift of the mean from chance. This is associated with a probability p < 10-50. In other words, the DMMI effect is not due to chance.

The filedrawer problem

One might object that the overall estimate of the effect may be inflated because of selective reporting practices. It is well known that experiments with null and negative results are not published as often as experiments with successful results, and since a meta-analysis relies on published reports, the overall results may be much smaller if we knew about all of those (potentially) unpublished, non-significant studies. Missing studies are called the "filedrawer problem." There are a variety of ways of assessing the consequences of the filedrawer problem. One way is to calculate a "failsafe" number, which is the estimated number of unretrieved or unpublished studies, averaging a zero effect, which would be needed to shift the overall results down from the observed value to a non-significant value [29]. For DMMI experiments, this turns out to be 54,000 studies.

Other methods of assessing the effect of the filedrawer problem show even larger numbers of "filedrawer" studies [28]. In other words, the filedrawer analysis shows that the observed effect is not plausibly due to selective reporting practices. But maybe the results are due to methodological problems or poor experimental quality?

Experimental quality

To assess experimental quality, a set of sixteen quality criteria were developed. These criteria covered all valid criticisms that had been published about the methodology of DMMI experiments. Each of the 597 experimental studies were reviewed for the presence or absence of these criteria, assigning a "1" if the criterion was present and a "0" if it was absent. The overall quality score was the sum of the individual criterion scores. Thus, a 0 represented poor quality and a 16 represented excellent quality. This is an accepted, conservative way of assessing quality, because it relies on what the investigators actually reported. Investigators who failed to report their studies in full tended to receive lower quality scores.

Contrary to the hypothesis that the effect would disappear as experimental quality improved, this analysis revealed a tendency for better controlled studies to produce slightly larger effects. Thus, the DMMI effect is not due to the filedrawer problem or to any known methodological problems.

Summary of the meta-analysis

The meta-analysis determined that the DMMI effect observed in these experiments was (a) not due to chance, (b) successfully replicated by different experimenters, (c) uncorrelated with potential methodological flaws or artifacts, and (d) not accounted for even if more than 50,000 nonsignificant studies had been overlooked in the process of searching the literature.

A few years later, a colleague and I conducted another meta-analysis, this time looking at DMMI with physical objects (falling dice) as the targets [33]. This study retrieved 148 experiments, reported by 52 investigators over 30 years, involving more than 2 million trials by 2,569 subjects. The results were similar to the prior meta-analysis. This large body of experiments provided persuasive statistical evidence for DMMI on physical objects: The overall effect for experimental data was more than 19 standard errors from chance.

IF IT IS REAL, PUT IT TO WORK

Given the substantial empirical evidence for DMMI effects, I decided to explicitly test the notion that DMMI-mediated effects might be responsible for some computer failures. At this time (1990) I was working at Contel Technology Center (the R&D arm of Contel Corporation, a multi-billion dollar telecommunications company). I designed an experiment that used only off-the-shelf equipment. A commercial random number generator on a chip (manufactured by AT&T Microelectronics) was used as the DMMI "target" to simulate an unstable electrical circuit within a computer [34]. The idea was that erratic circuitry might be susceptible to small DMMI effects [35-36]. Two experiments using the chip were successful in demonstrating DMMI precisely where it was predicted to appear (p = .02 & p = .002, respectively) [37].

The next step was devising a method of putting the effect to work. Taking advantage of a call for applied research on future-oriented communication technologies, my colleagues and I at Contel proposed to build a prototype "thought-switch," then test it in-house to see if we could demonstrate proof-of-principle. The project was approved, and the device was completed and tested in late 1990. The prototype incorporated a new type of DMMI detector, and used some neural network and error-correcting techniques to analyze the results [38-40]. The test involved 10 volunteers selected from Contel Technology Center who were asked to mentally influence the system in strictly prescribed ways. The experiment was successful [41], prompting us to prepare a patent disclosure. Unfortunately, immediately after the prototyping tests were completed, GTE Corp. merged with Contel and the disruption of the merger halted all efforts on this project.

WHERE DO WE GO FROM HERE?

The experiments mentioned here, along with corroborating anecdotal and experimental evidence, support the plausibility that, in principle, some computer failures may be DMMI-mediated. To avoid misunderstandings, "some" is undoubtedly a very small proportion because computer hardware is normally designed to provide high data integrity and operating reliability. However, computers that are specifically designed to work in conjunction with special DMMI detectors raise the possibility of developing a mind-machine technology.

Applications

Because the empirical data indicates that DMMI phenomena are not mediated by electromagnetic fields [42], applications for DMMI machines include (1) an alternative, low-bit-rate signaling path for deep sea or deep space craft (including sending backup control signals to missing satellites, such as the $1 billion Mars Observer); (2) prosthetic devices for paraplegics, such as thought-controlled robotic exoskeletons; and (3) secure entry systems and communication devices based upon person-unique "mind-prints."

Industrial interest

While Western science and technology has more or less dismissed or ignored the DMMI effect as a minor laboratory curiosity, Japanese electronics giants are taking it more seriously, including DMMI R&D efforts at NEC, Uniden, and Matsushita [43].

More recently, an article in R & D Magazine reported that Japan's Ministry of International Trade & Industry (MITI) created a study group drawing together academic, business, and government representatives [44]. The group's name roughly translates as "Sensitivity Business Study Group." One of the topics seriously being studied by the MITI group is DMMI phenomena. And perhaps in response to the growing realization that there is an enormous technological and financial advantage to being the first to harness these phenomena, Sony Corporation recently (late 1992) established two laboratories in Tokyo specifically devoted to exploring ways of creating DMMI applications [45].

A theoretical aside

While discussion of theory is beyond the scope of this paper, it is worth mentioning that some physicists see strong parallels in both the observational and influence-at-a-distance nature of DMMI phenomena with the enigmatic non-local effects predicted by and observed in empirical tests of Bell's Theorem in quantum mechanics [47-50]. However, upon realizing that these phenomena fall somewhere in the cracks between psychology and physics, caution is essential. As physicist Nick Herbert says,

Science's biggest mystery is the nature of consciousness.... About all we know about consciousness is that it has something to do with the head, rather than the foot. [51, p. 249]

CONCLUSIONS

In this paper I proposed that the evolution of human-computer interaction will pass through a stage where we will begin to see direct mind-machine interaction or consciousness technologies. I have presented a summary of the empirical evidence supporting this proposal, and I have reviewed the inklings of serious industrial interest in this potential new technology.

I imagine that some readers will be perplexed and perhaps a little disturbed by this paper. Could this this outlandish proposal truly be credible? Surely something as revolutionary as evidence for genuine mind-machine interaction would be front-page news? One response is to point to a recent cover article in New Scientist [52] and to other references cited in recent mainstream sources [53-55].

Another response is to explain to the reader that retrieving the evidence cited here required careful digging in specialized journals. Few DMMI experiments demonstrate the "big stuff," i.e., spectacular macroscopic effects observable without the use of statistics. Indeed, these experiments rarely produce anything visible to the naked eye. As a result, science journalists have a difficult time conveying why these strange laboratory anomalies are interesting. And very few scientists have spent much time thinking how to put these curiosities to work.

Complementarity

I should also mention that the ideas presented here challenge many mainstream scientists' deeply cherished (and often unconsciously-held) beliefs about the role of the mind in the physical world. Most of us are taught to naturally assume a strict isolation between mind and matter, with absolutely no exceptions. But what these phenomena suggest is that under certain circumstances there are weak statistical violations of what is essentally an "isolation hypothesis." While mind seems separate and isolated most of the time, at other times it seems distributed, non-local, and deeply interpenetrating. Perhaps there is no paradox here, but rather a form of complementarity, as in a photon being both a wave and a particle. What we see depends on what perspective we take.

Given the evidence for DMMI phenomena, combined with the rapid development of sophisticated digital signal processing techniques and artificial neural networks capable of identifying extremely subtle patterns, suddenly the notion of developing technologies that can detect delicate DMMI-type impressions no longer seems so fantastic.

The physicist Sir James Jeans once said, reflecting on the startling implications of quantum mechanics theory,

The concepts which now prove to be fundamental to our understanding of nature ... seem to my mind to be structures of pure thought, .... the universe begins to look more like a great thought than a great machine. [56]

Perhaps the time is approaching when a shift in technological perspective will reveal something quite new: a great "thought/machine."

Not if, but when

It will take some time for scientists, engineers, and HCI specialists to catch up with the relevant literature and with the scientific and theoretical implications of DMMI phenomena. However, I believe that as the studies mentioned here begin to infiltrate the mainstream, it will no longer be a matter of if, but when and in what form DMMI technologies will appear.

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