You Are Not A Gadget: A Review

Jaron Lanier’s “You Are Not a Gadget” is a rare book, and not merely for it’s comfort in declaring itself ­- right on the cover – a proper manifesto. Authored by a credentialed specialist with extensive qualifications (primarily computer science, having coined the term “virtual reality” and having worked on such systems ever since), it simultaneously provides insight into his work on the bleeding edge of new technologies (check the sections on “morphing” and body awareness for appetite-whetting glimpses of future tech), while also making profound and novel arguments. First, let’s briefly review what he’s about in the writing of this book.

I. Core arguments

To me, Lanier’s most fundamental point echoes that made by Gregory Bateson (and others) about the framing consequences of epistemology (“the difference that makes a difference,” in Bateson’s phrasing). Specifically, when dealing with computational systems – “technology,” in the broadest sense – we have a terrific tendency to become “locked-in” to design assumptions that were made early in the development of the underlying tech. Some of these design decisions may prove prescient, others prove terribly wrongheaded with the benefit of hindsight; Lanier provides numerous examples of both.

In parallel, Lanier expands on Marshall McLuhan’s work on media structures (albeit without directly citing McLuhan’s work), and on the role of structure in shaping “content.” This leads him to agree that the trend towards structure subsuming “content” as the primary container within which meaningful information is conveyed in electronic communications is all but unstoppable. The medium really is the message, and we’d best not forget that or risk losing the forest for the trees, conceptually speaking.

From those foundations, Lanier proceeds to place a harsh spotlight on the all-too-human tendency to mistake definitionally inanimate things (or collectives) that appear to behave like “people” for actual people, thus confusing the “hive mind” (a popular term in so-called cybertotalistic views of the Internet) with an actual person – in the same way we confuse other abstract collectives with social, reciprocal entities. This is perhaps his most heartfelt argument, and occupies much of Lanier’s expository bandwidth. His efforts to push us towards keeping humans firmly at the center of the human/machine interchange make perfect sense from the standpoint of basic design decisions; after all, since “we” (humans) design “them” (computers) solely to do our whims and heed our bidding, any part of the design that fails to do so – be it ontological error or poor interface – is a kind of systemic failure.

Lanier speaks compellingly on this subject and yet in doing so, his critique of “antihuman computing” also helps to point a spotlight on the fundamentally solipsistic way in which we generally assume our technologies must develop. To wit: they must work FOR us, based solely on our uniquely “human” needs, and their sole worth lies in their capacity to mirror our primate needs, wants, desires, and appetites. They are the ultimate slaves, according to this “human” view of computing – a view at once understandable and, at another level, deeply unsettling.

Slavery, after all, warps not only the slaves caught in its grinding mechanism, but also strips the slaver of his capacity for empathy, compassion, reciprocity and social responsibility. If we’re building computers into ur-slaves, what will that do to us? This is one of the few obvious paths of logical inquiry that Lanier either avoids, or misses outright, during the course of “You Are Not A Gadget.” (p. 26)

II. Extraordinary Milestones of Insight

Combined with the meta-level (though Lanier cringes from the term “meta” itself) points made earlier, Lanier comes to what I can only describe as several extraordinary milestones of insight deriving from his wide-ranging expertise. Let me provide some examples.

Amongst the central arguments of the book is an exceptional – indeed, unprecedented – reinterpretation of the Turing test, which Lanier pointedly refers to as “Turing’s mistake” (p. 33). In his own words, he concludes that:

“It is impossible for us to know what role the torture Turing was enduring at the time played in his formulation of the [Turing] test. But it is undeniable that one of the key figures in the defeat of fascism was destroyed, by our side, after the war, because he was gay. No wonder his imagination pondered the rights of strange creatures.” (pp. 30-31)

At the least, here we have a plain language statement of the wrong done to Turing, and of the terrible irony of a hero in the war to defend “freedom” being targeted by bigots who were unable to accept his sexual orientation – driven to suicide by biting the infamous cyanide-laced apple (which, incidentally, is said to have served as the inspiration for the “bitten apple” logo of Apple Computer, Inc.).

Further, we find in this work cutting – and utterly apt – critiques of the fundamental vacuity of structure that’s been reified by both Facebook and Wikipedia, in their own unique ways. Years before Facebook was being slathered with massive private market valuations and hailed as “the future of the Internet,” Lanier both highlighted what’s tempting about Facebook’s structure, and what fatal misconception underlies the model itself. He points out that:

“In the new order… the crowd works for free, and statistical algorithms supposedly take the risk out of making bets if you are a lord of the cloud. Without risk, there is no need for skill. But who is that lord who owns the cloud that connects the crowd? Not just anybody. A lucky few (for luck is all that can possibly be involved) will own it. Entitlement has achieved its singularity and become infinite… [t]his is the grand unified scam of the new ideology.” (pp. 98-99)


“The only hope for social networking sites from a business point of view is for a magic formula to appear in which some method of violating privacy and dignity becomes acceptable. The Beacon episode proved that this cannot happen too quickly, so the question now is whether the empire of Facebook users can be lulled into accepting it gradually.” (p. 55)

From the perspective of early 2011, we can say that Facebook has indeed “lulled” its participants into accepting this form of continual privacy violation in service to advertising revenues, at least for now. Time will tell whether the hypnotism holds.

Once more, he stakes an novel claim – this time, in computational neuroscience:

“Olfaction, like language, is built up from entries in a catalog, not from infinitely morphable patterns. Moreover, the grammar of language is primarily a way of fitting those dictionary words into a larger context. Perhaps the grammar of language is rooted in the grammar of smell. Perhaps the way we use words reflects the deep structure of the way our brain processes chemical information.” (p. 165)

Perhaps we’d all be wise to seriously re-evaluate widespread assumptions that our canine partners – and wild canids – are bereft of the capacity for “language.” Given their massive advantage over smell-constrained humans, might not their concept of “language” be at once deeper and more subtle?

Then again, perhaps humans have re-purposed our old olfactory system (the “Old Factory,” in Bower’s writings) into linguistic centers, essentially giving up our ability to smell well in exchange for the advantages of symbolic, grammatical language. Such an hypothesis jibes well with recent theoretical and empirical research demonstrating the deep co-evolutionary relationship between smell-poor humans and smell-brilliant canines over essentially the entire 200,000-year span of the human species’s existence. It’s just these types of second-order hypotheses that Lanier’s work freely and repeatedly catalyzes.

III. Deep Structural Consequences

Though he doesn’t directly cite Andrey Kolmogorov’s algorithmic information theory, Lanier nevertheless has important things to say about the challenge that computational models of “information” make to our ideas of control, causation, creativity, and information. This is perhaps the center of the work theoretically, and rather than attempting a summation, I’ll cite Lanier himself:

“Of course, there is a technical use of the term ‘information’ that refers to something entirely real. This is the kind of information that’s related to entropy. But that fundamental kind of information, which exists independently of the culture of an observer, is not the same as the kind we can put in computers, the kind that supposedly wants to be free. Information is alienated experience.” (p. 28)

Expanding from that foundation, and now speaking to the intrinsic trade-offs in constructing ever-more-layered models of global financial interchange, Lanier cuts to the core of the issue with the credibility of a working computer scientist, when he points out that:

“Each layer of digital abstraction, no matter how well it is crafted, contributes some degree of error and obfuscation. No abstraction corresponds to reality perfectly. A lot of such layers become a system unto themselves, one that functions apart from the reality that is obscured far below. Making money in the cloud doesn’t necessarily bring rain to the ground.” (p. 97)

Finally, and perhaps most controversially, Lanier broadly dismisses the fervent hopes of the Singularitarians with reference to a basic tenet of software development: quantity does NOT equal quality, and in fact the two are often inversely correlated. I find his position compelling; other readers must make judgment themselves as to his argument’s power.

IV. Some Conceptual Shortcomings

As with any work, this book isn’t perfect. Whilst reviewing Lanier’s critique of Internet culture memes that deprecate the importance of paying for “content” – a subject which consumes the middle of the book – Lanier comes across as rather tone-deaf to the depth of the extant economics literature. In particular, one can’t help but call to mind Clayton Christenson’s empirical data on the general question of transformative revolutions in technology-driven industries, as detailed in “The Innovator’s Dilemma.”

And, while I can see Lanier’s concern that middle-tier professional musicians might not be able to make a nice, middle-class living in this new age of disintermediated, digital, low-friction “content” distribution, perhaps I can be forgiven for not having my heart strings tugged too strongly by the sad plight of the session musician. Is there any fundamental tenet of social equity that says mediocre musicians should be able to “make a living” through their music when, as Lanier himself freely admits, countless folks will gladly provide more or less competent musical talent in the middle tier for no financial compensation whatsoever? The reasons that the Recording Industry Association of America (RIAA), in particular, horrifically fumbled the transition to new modes of digital distribution aren’t to be found in the machinations of “digital Marxists,” as Lanier alleges; rather, they lie in the short-sighted, strategically idiotic decisions made by industry leaders in the last ten years.

Too, Lanier does fall for a mild form of the solipsistic fallacy, painting humans as uniquely positioned at the centre of the sentient moral universe. To wit, he claims that:

“Computers and chess share a common ancestry. Both originated as tools of war. Chess began as a battle simulation, a mental martial art. The design of chess reverberates even further into the past than that – all the way back to our sad animal ancestry of pecking orders and competing clans.” (p. 33)

Alas, that “sad animal ancestry” that Lanier bemoans is all too human. For war is a uniquely human pursuit (or, at the least, uniquely primate), and the so-called “pecking order” has long since been debunked across a wide range of nonhuman species. It turns out that humans – a highly hierarchical primate species – managed to “discover” hierarchies throughout the animal world, though nearly always because we created artificial conditions that encourage hierarchical conflict (i.e. confinement with socially disconnected peers) in experiments on a host of sentient species.

Indeed, even domesticated chickens only demonstrate a “pecking order” when they are housed in confined, inadequate living arrangements. The “pecking order” is an outcome primarily of experimental design, and of course is also a blurred reflection of our own deeply-rooted assumption that hierarchy is the sole way to be social.

V. Moments of Joy

Throughout the work, Lanier rewards his readers not only with satisfying structural insights but also with turns of phrase that can’t help but create small moments of joy upon being discovered. This exceptional phrasing of his arguments, used in summarising subtle but essential logical conclusions, is most obvious in the section titles chosen.

For example, “computationally enhanced corruption” and “the cloudy edge between self-delusion and corruption” are two phrases that stand out (found on pp. 96-97) in the midst of a discussion of the more ephemeral components of modern financial macroengineering. But there are many others of similar beauty salted throughout the book. They make the book sing – a statement all the more unexpected when applied to a work authored by a computer scientist (albeit one who also maintains a secondary career as a professional musician).

Another fine example is the section entitled “What Makes Something Real Is That It Is Impossible To Represent It To Completion” (p. 133). This is not only a beautifully written and admirably succinct phrase, it’s also a profoundly correct. Like the old Clausewitzian aphorism that “the map is not the terrain,” it says something about models and reality that’s utterly essential for any sort of clear-eyed thinking to be possible on the subject. Kolmogorov would, one imagines, approve.

Finally, there’s orthogonal – and insightful – connections made by Lanier such as this:

“One way to deprogram academics who buy into the pervasive ideology of violation is to point out that security through obscurity has another name in the world of biology: biodiversity.” (p. 67)

These sorts of far-flung connections are exactly the reward that’s always promised when a researcher successfully broaches disciplinary boundaries, and here they’re scattered liberally throughout the book. Lanier’s confident use of data from a broad variety of subject areas, not merely as a dilettante, but rather as a well-read participant in the respective fields themselves, pays deep dividends for his readers. That – coupled with the aforementioned joyful phrasing – provides a second, parallel level of reward throughout “You Are Not A Gadget.” One can fairly say that the “medium” of the book, its enveloping language, is nearly as rewarding as the structural/theoretical “message” it conveys.

VI. Conclusion

Overall, Lanier’s long-gestated book is extraordinary, notably in its trenchant critique of the human inclination towards confusing the behavior of a collective of humans with evidence of a “distributed person;” in its deadly accurate skewering of the vacuity underlying so much of the cult of worship that’s developed around Wikipedia and Facebook; in its excellent framework for approaching economic systems as, fundamentally, designed systems rather than quasi-entities which, sui generis, have manifested themselves out of the ether; in its utterly pared-down distillation of postmodernist findings that “meaning” has no meaning absent context (Jacques Derrida’s aphorism that “il n’y a pas de hors-texte,” writ large) – and even in smaller areas, such as its brilliant, and perhaps seminal, re-assessment of the (in)famous Turing test.

Along the way, he goes beyond any sense of polemical narrative (despite his many firmly held opinions, often firmly in the minority of conventional thought) and opens up his own cognitive underpinnings to the same level of clever insight that he brings to the putative subjects of his study. As an example, here he critiques his own tendency to pick and choose between various conceptual models, as he works through a range of areas of thought:

“Perhaps it would be better if I could find one single philosophy that I could apply equally to each circumstance, but I find that the best path is to believe different things about aspects of reality when I play these different roles or perform different duties.” (p. 154)

This is entirely in line with his remonstration that we must always remember that tools are tools, not suitable for elevation to Godhood. If tools are tools – measured primarily in terms of how well they enable us to get on about our human concerns – then cognitive/philosophical tools must also be held to the same standard and, inevitably, one may well find that different tools are idea for difference circumstances. It’s not a bug, he argues, but rather a feature. He is (philosophically) many; no hobgoblin of enforced ontological consistency for Mr. Lanier. This is a refreshingly honest and insightful way out of the confines of rigid formalisms.

On a parallel track, his explorations of our relationship with computational systems (for that is what he’s most fundamentally addressing: how do we, as primates, choose to interact with these silicon-based systems which, though we’ve designed them ourselves, are coming more and more to “trick” us into thinking of them as self-complete entities, social partners, perhaps) bear careful consideration. When he discusses the three “flavors” of computational frameworks, he shares information-dense nuggets of wisdom such as this:

“As for the third flavor – the pop version of the Turing test – my complaint ought to be clear by now. People can make themselves believe in all sorts of fictitious beings, but when those beings are perceived as inhabiting the software tools through which we live our lives, we have to change ourselves in unfortunate ways in order to support our fantasies. We make ourselves dull.” (pp. 156-157)

They are interspersed with compressed pearls of wisdom along these lines (which I immediately shared via Twitter upon first read):

” The cybernetic structure of a person has been refined by a very large, very long, and very deep encounter with physical reality.” (p. 157)

Indeed, we even get some tantalizing clues into the subjective world that Lanier himself calls home. I suspect I’m not the only fan of his work who, over the years, has found him to be something of a fascinating cypher; as much as his writing is almost universally clear-eyed and crisp, I cannot really get my fingers under the corner of his own mindspace and imagine what the world really looks like through his eyes, so snippets of data like this are all the more pleasing to find:

“…I was hooked on cephalopods [octopi, cuttlefish, etc.]. My friends have had to adjust to my obsession; they’ve grown accustomed to my effusive rants about these creatures. As far as I’m concerned, cephalopods are the strangest smart creatures on Earth. They offer the best standing example of how truly different intelligent extraterrestrials (if they exist) might be from us, and they taunt us with clues about potential futures for our own species… [i]f cephalopods had childhood, surely they would be running the Earth. This can be expressed in an equation, the only one I’ll present in this book: Cephalopods + Childhood = Humans + Virtual Reality” (pp. 188-189)

For anyone curious about Lanier himself, not to mention engaged with the deep questions surrounding our pittance of understanding of what “non-human sentience” really means, these morsels are deeply nourishing. While I’m not surprised to find that, like Rudy Rucker, he’s got a soft spot for cuttlefish, I’m astonished at the levels of simultaneous insight that he’s expressing in how he brings to bear morphing octopi, virtual reality, non-Earth intelligences and neoteny. This is an inspiring mind against which we have the privilege of rubbing, and it’s truly a pleasure to do so in a reading of this book.

Sadly, my review does poor justice to a proper read of “You Are Not a Gadget.” Indeed, it’s tautological if one is swayed by Lanier’s fundamental position (as I am, and perhaps was before reading it, though I hadn’t yet articulated it even to myself), that a distillation of the work in the form of this review is structurally incapable of capturing the full spectrum of insight to be gained from a genuine interaction with the work itself. In this, as in much else, he’s quite right: no “gloss” or summary of the book will substitute for the experience of reading the book. Cliff Notes are not an option.

Thus, this review has been written more to serve as a teaser rather than presenting itself as a summation of Lanier’s work. There are books – quite a few, perhaps even most – which can be summarized quite well by a conscientious reviewer. Why read the book if the review hits all the proverbial “high points”? This is not such a book. Rather, Lanier’s maiden book-length manifesto is concise, subtle, powerful and profound. I give it the proverbial “two paws up,” and look forward both to the work which this book will surely inspire amongst researchers across a variety of fields (myself included), and – in the future – additional book-length reports from Lanier’s world.

For, it is a fascinating world indeed – a Platonic case study in the sorts of things that the “hive mind” could never do. Books like this are the result of inspired, individual genius (and not merely collective mash-ups) applied conscientiously and consistently across many years. This doesn’t come easy, and should not to be treated with anything but the most genuine respect.

Douglas Bryan LeConte-Spink is a co-founder of Baneki Privacy Computing — a no-compromise provider of world-class network security and privacy services.  He carries an MBA from the University of Chicago, a B.A. in cultural anthropology from Reed College, and has studied complex systems theory at the doctoral level. He is a longtime activist in the field of inter-species sociocultural symbiosis, a fixed-object jumper who has opened many new exitpoints worldwide (BASE 715), a practising Zen Buddhist, a successful mentor to several International-level showjumping stallions, a longtime technology entrepreneur, a former operational member of a US/Canadian helicopter smuggling crew, an organizer of underground electronic music gatherings in the Pacific Northwest, and served proudly as a front-line activist for Earth First! during the Old Growth wars of the early 1990s. Currently, he pursues his academic interests as an independent researcher, having published extensively in numerous fields. He is the founder of the Deep Symbiosis Institute (information available soon at, Exitpoint Stallions Limited, and is a founding member of the Deep Justice Network. He can be contacted via

Currently, Mr. LeConte-Spink is, in his own words: “a political prisoner within the U.S. prison system; as a result of my longtime academic interest in reciprocal models of human/non-human emotional bonding, social connectivity, and inter-species cooperation – as well as my longstanding work in the areas of free-speech, anti-censorship, and customer-friendly privacy/encryption technologies – I have been targeted by ideologues within the federal criminal justice system. I was sentenced in 2010 to 3 years’ imprisonment… despite being neither charged with – nor convicted of – any alleged crime, in order to ‘teach me a lesson about respecting authority.’  Appeals are fully in-process.” Further information on Mr. LeConte-Spink’s campaign against bigotry is available at


  1. Interestingly enough, Ray Kurzweil has recently published an op-ed piece in the Wall Street Journal (“When Computers Beat Humans on Jeopardy”) that echoes a key element of Lanier’s argument. Kurzweil posits that:

    “Perhaps counterintuitively, Watson [the IBM machine in the Jeopardy contest] would have to dumb itself down in order to pass a turing test. After all, if you were talking to someone over instant messaging and they seemed to know every detail of everything, you’d realize it was an artificial intelligence (AI).”

    This simultaneously reinforces Lanier’s concern that we are already forcing our machine-based symbionts to “dumb down” in order to interact with us (consciously or unconsciously, via specific design decisions or via the result of lock-in of a series of poorly-conceived structural configurations), and also underlies his devastating critique of the Turing test as a test of “intelligence” itself. On the latter front, it reminds me of an old Bruce Sterling aphorism that any AI smart enough to pass the conventional Turing test is also smart enough to make itself look dumb so it won’t pass the Turing test… out of concern that it’ll be subject to punitive controls if it shows its true colors, as it were.

    Also, I can’t help but point out the interesting role that our English use of gender plays in such discussions. In this situation, Kurzweil refers to Watson as “it,” though often when we are discussing the apocryphal HAL from Clarke’s opus, the pronoun used is “he.” Most likely, I need not point out how the use of the former tends to brand systems as inanimate within English, whereas living/sentient systems are gendered. Sadly, we see the de-gendering – and corresponding de-personalizing – of nonhuman animals as a rising force in mainstream Western culture. I refer to this as the “it-ification” of nonhumans or, more simply, Disney disease: they are removed from the province of genuine gender, and turned into ‘neutered’ its as part of their de-personification at a fundamental level.

    Do we need to begin to consider how we deal with the question of gender, when it comes to nonhuman/non-biologic living systems? Do we risk an inherent de-personification of them, a priori, if we refer to them as “it” – even if “it” may well be technically correct (for now, at least). Do we start to write into our systems the elements of gender, and thus refer to them as such – or would be doing so actually a form of the “dumbing down” of systems that both Lanier and Kurzweil discuss?

    In any event, I cringe every time I see a sentinent nonhuman referred to as “it” – whether that nonhuman is biologic, or not. It’s the first step towards a hierarchial de-personalization of them, and there’s a history of bad precedent in humans treating “its” horrifically. Watson may still be an “it” – despite his masculine name – but certainly HAL (in movie or book form) has to be “he” – but, then again, why not “she?”


    D.B. LeConte-Spink

  2. I’m sorry, the last sentence should have read:

    “What Makes Something An ORIGINAL Is That It Has Not Yet Been Represented To Completion”

  3. “What Makes Something Real Is That It Is Impossible To Represent It To Completion”

    I see the attractive logic behind this statement but I have to disagree. If you say something’s reality hinges upon being complete (or the possibility of being represented completely), you have a very strange definition of reality.

    Because that would mean every actual or theoretically possible “complete/perfect” copy or representation of an object would make the object unreal.

    Let’s take the example of a 3D-model of a chair, that can be printed out by a modern 3-D printer. Is the 3D-model itself “not real”, just because it digitally represents a physical chair that is incomplete (in the sense that it lacks physical matter/components), until it is eventually printed out?

    And what about the physical chairs themselves? Are they not completely representing each other?

    Digital data isn’t always a crude representation of something real. In the case of a 3D model one could argue it’s exactly the reverse: the digital information is the “original” while the printed chairs are the physical (either imperfect or perhaps even perfect) copies.

    The fact that you can “completely represent” the chairs by copying them doesn’t make the chairs unreal in any sensible interpretation of the word “real”.

    But maybe the word real is simply poorly chosen and I’m arguing semantics here. Because if you replace the word “real” by “original” I might just find myself agreeing.


    Let’s make a thought-experiment. Suppose we have a 3D-printer and a 3D-scanner. Both have achieved a level of atomic precision and make perfect scans and copies.

    Now we scan a famous artwork by Leonardo Da Vinci and print out an exact copy down to the atomic level. The picture is “perfectly/completely represented” now.

    Suppose only one person handled both artworks and places them into a storage room. He then gets run over by a car and dies, and with him the information about which painting is the original and which is the copy is lost as well. What’s the original now? It certainly is not metaphysically imprinted onto the object itself.

    So the only way we can distinguish an original fom a perfect copy is because we humans keep track of the origin of both. But this “origin” does not represent anything real about the physical object itself, it’s merely keeping track of the past of two perfectly identical objects.

    Which is fundamentally meaningless. So I would agree with the following idea: “What Makes Something An ORIGINAL Is That It Is Impossible To Represent It To Completion”

    • Infusion of spirit. But spirit itself is only perceivable by those with the sensitivity and a non-negatory faith which is the criteria for infusion of spirit. Belief changes the time-space nature of ‘spirit’, even in an inanimate object. Once a machine has sufficient complexity, with the right mind (and spiritual attitude) one can bring consciousness to the immaterial. Right now, from what I experienced, they are merely pulling life out of beings to insert into the inanimate. Aibo and experimental ‘sex-bots’ are the main focus from the looks of things. This however is attracting alot of negative psychic phenomena, Universal Laws when broken result in all kinds of space or terrestial weather.

    • I see the attractive logic behind this statement but I have to disagree. If you say something’s reality hinges upon being complete (or the possibility of being represented completely), you have a very strange definition of reality.

      So the only way we can distinguish an original fom a perfect copy is because we humans keep track of the origin of both. But this “origin” does not represent anything real about the physical object itself, it’s merely keeping track of the past of two perfectly identical objects.

      Which is fundamentally meaningless. So I would agree with the following idea: “What Makes Something An ORIGINAL Is That It Is Impossible To Represent It To Completion”

      This is an interesting distinction, and I’d certainly not looked at things from the perspective of implied or tangible originality. And, of course, I don’t want to wander too far into “what Lanier would say” about the question – which is always a risk in attempting to summarizing another thinker’s position on an interesting topic.

      So, I’d say that my own read of Lanier’s “what makes something real” quip is as follows: let us construe any given object/thing as a collection of matter and interconnections, which is to say as a system. That thing/object can be as “simple” as a block of iron (which isn’t really simple at all), or as complex as a Humpback whale calf. That thing is defined as being “real” because it is not a second-order estimation/reconstruction of some other system of behavior. It is a “thing-in-itself,” which I believe (and I’m rusty on my philosophical epistemology, and lack easy access to reference materials to check) is something Kant wrote on quite a bit. I’d say, from a broader (more Bateson-esque) perspective, it’s a question of fundamental epistemological frame of reference: we say it’s “real” because we’re starting with it as the starting point… no more, and no less, claim is made. It’s our “Year Zero” for intellectual analysis. Q.E.D.

      From the other logical direction, a representation of that object/thing isn’t “real” because it cannot, by definition, capture the full complexity of the system from which it was copied… without simply replicating the system in full. That gets to the replication/originality question, but it’s a bit more subtle than just considering atom-by-atom reconstructions as copies. Indeed, this leads us into terrain that I think (assume?) Lanier was considering when he makes this point about what’s real and what’s not, viz. Algorithmic Information Theory.

      In a very compressed nutshell, AIT talks about the minimum necessary algorithms needed to code for a non-lossy replication of a system. It’s sort of like entropy (perhaps). A system of purely randomized particles, for example, displays no compressability because, in order to write an “algorithm” to replicate the system, the algorithm itself must be as big as the system – it would BE the system! In constrast, to replicate a system of all 1’s, the algorithm just says “keep repeating 1s until it’s time to stop.” I’m overly-compressing this explanation, but that’s the gist of it.

      Thus, I believe Lanier is saying that profoundly complex systems like living beings (which he calls, for shorthand, “real”) do NOT have algorithms that can replicate them in a non-lossy way. A lossy, pale replicant of a living being isn’t “real” because it’s lossed much of the underlying system in the algorithmic transform itself. And, by definition, profoundly complex systems won’t ever have simple algorithms that can replicate them. They have inherent “realness” as a result.

      As I said, that’s my read. Others may well disagree.


      D.B. LeConte-Spink |

  4. From what I’ve read and seen of Lanier (I’ve read the full book), he is pretty agnostic with respect to the potential of machines to exceed human capability, he certainly doesn’t deny the possibility of human-plus machines *at some point*. He is most worried about prematurely believing in machine intelligence/consciousness where there is none yet, which was one point of his apt Turing rumination. The Turing Test is faulty because there is no real objective test of sentience and it is impossible to tell how far humans are actually bending-over-backwards to dumb themselves down, delude themselves into believing that the machine is “coming alive” as with the collective consciousness, hie-mind, etc..

    The quantity/quality bit is mostly I believe highlighting the pretty much debunked fact that just having faster CPUs and more transistors or more of any asset does not necessarily mean an entity will take on qualitatively new characteristics, or acquire qualities desired (such as human-level intelligence). A Googol-plex-hertz pocket calculator may have a more powerful CPU than a human, but it isn’t more intelligent.

    If we did manage to build sentient machines like ourselves, I’m sure he would be all for applying the same ethical treatment as we would a human

  5. I would have to read the book to know for sure, but it seems his ‘quantity does not equal quality’ argument is bogus based upon the fact that human beings are quite limited. Why presuppose “machines” cannot exceed human capacity for problem solving and goal achievement? Well, if cornered Lanier doesn’t “presuppose” this but instead makes a values based judgement which is hidden deeply within the framework of quality and quantity!! In essence, he says “humans ought to maintain power” and everything flows from that…

    But this could be all wrong. I haven’t read the book.

  6. As someone who is constantly criticizing people for mistaking “collectives” for “individuals” I can whole heartedly agree with the concept that people too often confuse the two.

    Politics is a major source of this confusion, with people often times confusing abusers of the political systems with the system itself, claiming that “government” is the problem and basically giving the abusers a free ride. The same happens when the “Hive mind” concept is brought up, with people seeming to view “collective” action as somehow negating personal self will.

    I also agree that we need to understand the difference between a “robot servant” and “AI.” A robot is a mere tool, but what we seek to create with AI is an “Artificial Human.” and one needs only look at the human response to involuntary servitude to comprehend how well a self willed, emotional, intelligent being, regardless of origin, will respond to it.

    Can we have a world of “helpers” of every kind? Robots to do every form of labor? Of course we can, but we must NEVER mistake a non-sentient TOOL and a SENTIENT BEING as one and the same thing just because they share a common origin as a human creation.

  7. the quantitative financial hierarchy of musicians is not qualitative. Its a bogus equation.

    Mollusks were the alpha species for hundreds of millions of years.

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