The Mechanical Turk, Part 2: Lying Liar Filled With Promise

Returning to the Mechanical Turk (as agent of deception). As the use of LLMs spreads and winnows its way into more and more forms of the ways we talk to each other, the series of questions we must develop the habit of asking is less centered in the “Is this a human?” arena.

Every technological advance brings an EXPANSION of complexity.

This process is an accretion - existing modes of complexity are not displaced by new ones, they form the base layer of a new structure. The telegraph compelled us to become able to carry out rapid exchanges with unseen people far away, the telephone required that such exchanges be conducted verbally in real time, etc. It’s by now well understood that we’ve moved, in the present age of data and information, into a largely symbolic economy—one where meaning and value are increasingly constructed through representations, abstractions, and interpretations rather than tangible goods or direct transactions - the condition of being a “buyer” has come to more fully encompass being a “reader,” our role is as much “interpreter” as it is “recipient.”

The real world still exists (for the moment, anyway,) but more and more we must occupy a kind of liminal space between actual and abstraction. This ascendent place of symbols in the exchanges between us - in the form of brands, data visualizations, algorithms, etc. - means they carry great (and growing) weight in our decision making. These symbols - abstractions - can mask the underlying uncertainties and biases present in their creators - actual people in the actual world; with the result that the abstraction can eclipse the actual. The reason, therefore, that Lector cave (“READER beware,” and it’s Latin, so “cah-vay,” not not long “a” “cave”) comes to have such importance is that each interpretive act is necessarily the result of multiple forms of deciphering comprised of the meaning and relevance of abstracted symbols, the intentions and competence of the sender.

This Accretion of Complexity principle demands, therefore, that the lens through which we view everything grows more critical. An Attention Economy does not mean simply that our attention has been commodified - though obviously it has - it means that we as participants in an Attention Economy must necessarily grow more discerning in where we permit that attention to be directed.

Imagine the Mechanical Turk but with a cabinet made of glass - we’d be able to see the human operator wedged inside. The nature of the Turk would be unalterably changed, the purpose driving it (i.e. to deceive the viewer) eliminated entirely. Or imagine that the components of the Turk are disarticulated - if his pieces are unbundled from one another, we can immediately separate those carrying out some function (what we’re here calling the actual) from those intended to misdirect or misrepresent (the veneer of abstraction that performs no work/serves no purpose).

Applying a similar thought experiment to LLMs today means parsing A) the intent of human actors who provide the inciting inputs (actual), B) the resulting textual output (abstracted/symbolic) and squaring all that with C) what we’ve determined to be true/accurate/pertinent (a hybrid of the actual and abstracted). Lector cave thereby becomes not simply a caution about checking the veracity and validity of all the textual stuff that comes our way, but a kind of Prime Directive for how we must navigate the whole of this hybridized actual-plus-abstracted world in which we are all operating.

If we think of the Turk in relation to LLMs, the opacity problem is comparable but is not identical - it’s important to keep sight of the fact that for LLMs, the nature, character, and source of the opacity differs from that of the Turk: where the Turk was born to deceive, an LLM is not. LLMs can be wrong, they can be mistaken, but left to perform the tasks we set for them, they will not provide outputs with any intent to deceive. Deceit by design is (so far, anyway,) the province of people. In its “natural” state, an LLM system is devoid of any capacity for moral lapse or ill intent - it’s only the people steering it that can introduce such elements.

The LLM can be wrongheaded, it can be shortsighted or misguided, but it is not a liar.

We are, though, or can be - we alone have that capacity. So Lector cave comes to occupy a crucial and central role in how we engage with the information bombarding us each day. At the core of a concept like “media literacy” in fact, there must be this ongoing, updating, constantly revised estimation of both content and intent. Proficiency with the tools in question can go a long way to sharpening this capacity for estimation - a solid understanding of what LLMs can and cannot do, how they function, and the precise manners in which they may be deployed in service of deceptive intent.

A core aspect of the ZeroWidth approach, the heart and backbone of the ZeroWidth Workbench, is to give the LLM-Turk a cabinet of glass, so to speak, or - even further, to dismantle the Turk, to remake our relationship with LLMs. To unpack the monolith into comprehensible constituent parts, modules that will perform the tasks we set it in ways that are transparent, ways that render the product of LLMs a bit more human. By pulling the veil away from the workings of Turk, we make the structures inside and underlying the Turk to direct his efforts in truthful fashion.

In the coming weeks and months, ZeroWidth will demonstrate how its products and services seek to be a principled and conscientious presence in the field of LLM use. We’ll do that in part by outlining ways that the prevailing thinking about LLMs gets it wrong or misses the mark. We wish to become a resource in helping to plot the course this technology takes, and a leader in developing sound thinking around it. Here’s hoping you’ll tag along.

Next, our final part of this series: The Mechanical Turk, Part 3: Lying Liar Filled With Power