On point #1, Maybe we can expound on the meaning of "judgement". By the dictionary it's "an opinion or conclusion", but in common parlance we might interpret a judgement as "a belief that we desire others to agree with.". An even more cynical take would be "a belief we expect to be accepted by others on grounds of appeal to authority, i.e an expert or judge". We might even establish a chain of social value, from greatest to least:
1) Correct Judgement 2) Correct Opinion 3) Incorrect Judgement 4) Incorrect Opinion Where correctness is based on social acceptance, and judgement vs opinion is based on the source's expertise in the subject matter. Social value being a measurement of long term durability and benefit to building upon. For instance, one might have a "Correct Judgement" that the "concept of laws" has long term durability, and there are societal benefits from building on (instantiating) laws. Conversely, the "incorrect opinion" that some laws are meant to be broken may not have long term durability, and a negative social benefit if done. On point #2, I think only activist AI Ethicists are fighting for control over the grounds of the decisions (because they see the danger if no one champions the social good); I believe you are right that a majority of AI developers are not concerning themselves with the grounds, beyond subtly allowing their own bias. (Not pointing fingers, in most AI approaches I believe escaping your own groups' biases is impossible) AIKR taken to heart on point #3. Agreed on the premise of point #4, and I'll inject that an AGI developer ought to know that a judgement is an opinion within a space-time-context frame. I've continued work on something I'm calling Facet Theory, which is independent of the one by Guttman on wikipedia by the same name. The goal is to model contiguous space-time-context frames of understanding as something called a facet, which have interesting properties where two or more facets meet along an edge. For instance where two similar, but incompatible paradigms (groups of opinions) meet, e.g. Newtonian and Relativistic physics. In that example I like to visualize those as two facets on a 3D diamond. They are both reasonable approximations of understanding for their own particular space, time, and context. They may both be useful models of understanding how the world works (even at the same time in history). One may reign supreme for centuries, and just because a more accurate, "better" understanding is discovered in the future does not mean that it is totally replaced. "Context" in "space-time-context" is a catch-all for other dimensions of understanding, such as: * Socio-Cultural (body language in a certain social or cultural situation) * Information Source (The news being dire, but from a certain news channel) * Related Context (The food being good, related to a particular lunch event; A building having a good aesthetic, within the concept of Brutalist architecture) * etc. In this way the AGI may not only survive cognitive dissonance, but thrive in it by cognicizing at levels above the compartmentalized facets it encounters. Something that is related to (my) Facet Theory but not quite the same is Prototype theory, where our esteemed Antonio Lieto gets a mention: https://en.wikipedia.org/wiki/Prototype_theory I suppose a prototype of a concept would exist at the centroid of one of my facets. What we think of as subjective judgements are just opinions whose variance is greatest on the contextual scale (i.e. by person, place) and second greatest variance by time (your favorite music might change over your lifetime) However your objective judgements can be modeled as opinions with less variance over context, space and time, but still subject to instances where it does not hold true. "This apple" refers to an apple in a particular space and time, but in the context of an entity moving close to c, the apple may not be red. It also may not be red in the context of a colorblind persons' context, as distinguishable from green. Self referential statements such as "I think therefore I am", or axiomatic systems like mathematics absolve themselves from many dimensions and therefore seem profound to us because they are without counterexample across time, space, or context. Fleeting statements such as "my head itches right now" seem least profound simply because of the number of dimensional constraints on the facet. NARS has some great parts, and part of my substrate is based on what NARS can achieve. However there are a great many things which, once incorporated into NARS, allow a more human-compatible understanding to take place. For instance, instead of only frequency and confidence of an experience, also incorporating a learned confidence of the data source, when it was learned, etc. You may imagine a human case where you have to believe your brother who has old information, or a dubious politician. An AGI will be put in analogous situations, and a conscious system also consumes the reflection of its own past decisions, not only the reputation of external data sources. For the last part of point #4, saying "follow the money" may sound cynical but it's rarely wrong. Modern AI developers (especially Weak AI) will likely build systems to maximize stakeholders return, whatever the judgements. I don't have it all figured out, but this past year of sabbatical has been a tremendous help. Instead of trying to cram my own opinions into the AGI, it needs to be able to interpret reality on its own, and learn to reflect on its own judgements like a child. From an AI Safety perspective I've embarked on what I call Pathology First Development, which is basically generating failure modes of being that are analogous with human neuropathologies and psychopathologies. The motivation is that if pathological behavior patterns can be simulated and recognized, an AGI could be taught to avoid behaviors that lead to these patterns. Daniel Jue On Fri, May 20, 2022 at 1:48 AM Mike Archbold <[email protected]> wrote: > MOTIVATIONS > > Is the following fair? > > * There seems to be a prevailing, tacit climate of opinion in AI that > a judgment is correct primarily if it is 1) equivalent to prior > human-caused judgments (supervised) or 2) due to rewards. > > *Thus there seems to be no need for developers to concern themselves > with the grounds of the decision; ie., WHY *this* specific judgment? > (just point to the data and precedent) > > *But the problem is the combinatorial explosion: in a real world > settings often novel variations occur, each nuance bearing a thousand > little preferences, values, probabilities that have not specifically > been trained for. > > *So it seems like an AGI developer ought to know what a judgment is, > and to design accordingly. For example, we can think of purely > objective judgments ("this apple is red") or more subjective judgments > ("I think blues is superior to jazz, but not in the future"). > Presently it seems like modern AI regards both as valid if the answer > fits some pattern. > > ~~~~~~~~~~ > > By the way I know NARS holds "judgment" as one of its major > components, need to re-examine) > > Mike A -- Daniel Jue Cognami LLC 240-515-7802 www.cognami.ai ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/Ta80108e594369c8d-Mad81bfffaf67150e9cd80477 Delivery options: https://agi.topicbox.com/groups/agi/subscription
