[HN Gopher] Our field isn't quite "artificial intelligence" - it...
___________________________________________________________________
Our field isn't quite "artificial intelligence" - it's "cognitive
automation"
Author : vo2maxer
Score : 182 points
Date : 2020-01-07 12:43 UTC (10 hours ago)
(HTM) web link (twitter.com)
(TXT) w3m dump (twitter.com)
| YeGoblynQueenne wrote:
| >> Our field isn't quite "artificial intelligence"
|
| True, but so what? We call it AI and that's that, really. We've
| been calling it that for 70 years now and it's never been a
| problem.
|
| And let's be absolutely clear that it's not the _name_ that's
| confusing the public but the way that industry luminaries promise
| autonomous cars and robotic maids in the next -3 years, or the
| way that the technology press -the _technology_ press- can 't get
| its shit together to figure out the difference between "machine
| learning", "deep learning" and "AI" as fields of research and as
| category labels. Of _course_ the lay public is going to be
| confused if people who are paid to elucidate complex concepts
| make a mess of it.
| 6gvONxR4sf7o wrote:
| Probably most of the things being marketed as AI have been
| around and called statistics for a long time, and it's never
| been a problem.
| joe_the_user wrote:
| > " _True, but so what? We call it AI and that 's that, really.
| We've been calling it that for 70 years now and it's never been
| a problem._"
|
| That isn't even ... _true_. AI became "machine learning" in
| the late 90s/early 2000s and that change happened because the
| chorus of criticism of "artificial intelligence" had become
| extremely loud and a less ambitious term served as a refuge.
| YeGoblynQueenne wrote:
| AI was renamed into many things in the '80s and '90s, for
| example "Intelligent Systems" or "Adaptive Systems" etc, and
| that indeed was done to dissociate research from the bad rep
| that had accrued for AI. But "machine learning" has been the
| name of a sub-field of AI since the 1950's and it's never
| stood for the whole, at least not in conferences, papers or
| any kind of activity of the field.
|
| For example- two of the (still) major conferences in the
| field are AAAI and IJCAI: the conference of the "Association
| for the Advancement of Artificial Intelligence" and the
| "International Joint Conferences of Artificial Intelligence".
| Neither of those is in any way, shape or form a conference
| for machine learning only and neither uses machine learning a
| byname for AI. By contrast, machine learning has its own
| journal(s actually) and there are specific conferences
| dedicated to machine learning and deep learning (NeurIPs and
| ICLR).
|
| Additionally, there are many sub-fields of AI that are not
| machine learning, in name or function: intelligent agents,
| classical planning, reasoning, knowledge engineering etc etc.
|
| The only confusion between "AI" and "machine learning" exists
| in the minds of tech journalists and the people who get their
| AI news exclusively from the tech press.
|
| P.S. As a side note, the name for what the tech press is
| doing, referring to the field of AI as "machine learning", is
| "synecdoche": naming the whole by the name of the part.
| sgt101 wrote:
| No.
|
| Some people started saying things like that, more in about
| 2013, but all the time many people have been working on
| topics like MAS, answer sets, causal logic and other stuff.
|
| At that time the big trend was actually rebranding maimed
| logical inference as The Semantic Web.
| [deleted]
| jariel wrote:
| I don't really agree, and think the misnomer should be applied in
| the opposite direction: AI should be called 'adaptive algorithms'
| and it should be just another tool the box of CS people.
|
| We're not doing anything that we were not before.
|
| There is no new paradigm shift. There is no AI. There's just a
| slightly new approach to solving problems. That's it. There's
| somer really nice improvements in computer vision ... and a few
| other things ...
|
| ... but all this talk of 'intelligence' etc. should be brushed
| aside, it's misleading to everyone.
|
| There will be no 'general AI' with our current approaches for a
| whole variety of reasons.
|
| I'm embarrassed at how so many intelligent colleagues drink the
| kool-aid on this.
|
| Take classical ML: it was hyped for a while, now it's not as
| exciting as 'Deep Learning'. Well, in few years, I think that DL
| will be there as well: just a tool in the toolbox.
| LoSboccacc wrote:
| not even, it's multivariate regression analysis optimization
| anticensor wrote:
| It is automated (not _automatic_ ) cognition using multivariate
| regression techniques, after all, there is something to
| automate.
| airstrike wrote:
| I think many take issue with the use of the word "cognition"
| in that definition.
| sebastianconcpt wrote:
| Brilliant observation.
|
| And it's even harder than this.
|
| The problem is not that we have a problem. The problem is that we
| have problems. So the solution is not finding a solution to a
| problem. The solution is finding a metasolution that is valid
| across time and tribes. Bam! the challenge of being an
| intelligent being in this universe. No way we can automate that.
| Only mimic a portion of it and call it intelligence doesn't make
| it really intelligent.
| carapace wrote:
| FWIW, check out the Godel machine:
|
| https://en.wikipedia.org/wiki/G%C3%B6del_machine
|
| http://people.idsia.ch/~juergen/goedelmachine.html
|
| > No way we can automate that.
|
| It's a very very interesting question. Personally I believe
| that "automaton" is _almost_ the opposite of "being". But
| that's just me, not science or other authority. Certainly,
| somewhere between virus and human _something_ comes into being
| (no pun intended.) I don 't know of any non-metaphysical
| argument that we couldn't find some _other_ way to create non-
| biological general AI.
|
| I think we could genetically engineer human DNA to create
| wetware G"A"I but I put the "artificial" in quotes to indicate
| that I'm not saying whether that would count as AI or not. I
| know of a few efforts to create "Daleks" out of human brain
| organoids, but I don't think anyone has gone beyond the
| speculative/hype stage with it so far.
| eanzenberg wrote:
| Call it whatever you want, I don't care. It's working and
| improving year over year.
| mcculley wrote:
| I have been wondering why we don't use the term "synthetic
| intelligence": https://enki.org/2019/08/18/artificial-
| intelligence-is-a-dum...
| UncleOxidant wrote:
| That just replaces the first word with what is essentially a
| synonym. It's the second word "intelligence" that's the issue.
| mcculley wrote:
| "artificial" and "synthetic" aren't exactly synonyms in my
| mind. If I synthesize glucose, there is nothing artificial
| about it. It just didn't come from a process developed by
| evolution. Conversely, artificial leather is nothing like
| real leather.
|
| I'll have to think about that some more.
| kevin_thibedeau wrote:
| The root artifice has a broader meaning than "fake".
| Synthesizing something is an application of artifice.
| TheRealPomax wrote:
| But again, it's the "intelligence" part that's the
| misnomer. Except for John Carmack, no one's trying to
| invent general intelligence. Every single bit of work is
| merely automating tasks that _when performed by humans_
| requires intelligence... except that too is a misnomer
| because as humans we literally can 't do anything, no
| matter how mundane, without it "requiring intelligence".
| ratsmack wrote:
| I like this comment:
|
| >At the end of the day, "AI" is just glorified statistics
| (running on increasingly powerful computers).
| godelski wrote:
| I think it is also important to remember that intelligence isn't
| clearly defined. It seems a lot of people interpret it in
| different ways and the definition is closer to pornography (I
| know it when I see it).
|
| I often see two camps, one that defines intelligence to be more
| human like. Limiting it to really cetaceans and hominids. Maybe
| including ravens. The other group gives too vague of a
| definition.
|
| Personally, I do not see a problem with having lots of bins. I
| don't think many disagree that intelligence is a continuum. So
| why restrict it to very high level bins? Because that's the
| vernacular usage? I for one vote for the many bin and continuum
| approach. In this I think you could say that ML has some
| extremely low level form of intelligence, but I would generally
| say lower level than that of an ant. In that respect, a multi
| agent system with the intelligence surpassing that of ants I
| believe would be extremely impressive.
| proc0 wrote:
| Well said. The definition of intelligence is bastardized for
| virtually all current AI applications. They are glorified
| statistical heuristics / stochastic descent as has been mentioned
| before. The key to approaching actual intelligence as we know it,
| will be a system that can dynamically model its environment and
| actors in it, since even insects are able to do this to some
| extent.
| qwerty456127 wrote:
| I'd rather call it cognition imitation if you insist to associate
| it with cognition or intelligence. In fact it's just brute-force
| statistics.
| savanaly wrote:
| Are we so sure human cognition isn't this too?
| dr_dshiv wrote:
| One thing I find strange is how much we emphasize the artificial
| nature of the intelligence. AI and automation always occurs in
| the context of human processes. Nothing is truly autonomous, so
| why design it as if human involvement is a failure? We can easily
| design artifacts to enhance human intelligence or team
| intelligence. Why the focus on the machine part and not the
| overall system that functionally accomplishes the desired work?
| joe_the_user wrote:
| > _One thing I find strange is how much we emphasize the
| artificial nature of the intelligence._
|
| We really don't know what intelligence (sans qualifications)
| is. AI has been a term for effort emulate what we roughly think
| of as "intelligent" behavior. It's far from successful so far
| and the lack of a "theory of intelligence" is probably part of
| that. But it's pretty clear what "AI" researchers and systems
| are doing now is far from intelligence.
|
| > _AI and automation always occurs in the context of human
| processes. Nothing is truly autonomous, so why design it as if
| human involvement is a failure?_
|
| This argument makes as much sense as "we'll never exceed the
| speed of light, why act like faster transportation matters". An
| automated factory still requires some maintenance but it's
| creation certainly is significant.
|
| > _We can easily design artifacts to enhance human intelligence
| or team intelligence. Why the focus on the machine part and not
| the overall system that functionally accomplishes the desired
| work?_
|
| Both approaches matter and since there's really nothing keeping
| people from doing both of these, people pursue each separately.
| Moreover, I'd say AI research could do well to cross-pollinate
| with human-computer interaction theory.
|
| But overall, you seem to just not understand why automation
| matters - automation has brought vast productivity in a variety
| of fields. It may or may not be possible other further fields
| but if it is, it will transform the world equivalently.
| carapace wrote:
| "Intelligence Amplification" (IA) is a thing:
| https://en.wikipedia.org/wiki/Intelligence_amplification
|
| FWIW, I think that AI offers to _offload_ thinking (whether it
| delivers or not is another thing) while IA appeals to people
| who want to improve their own intelligence. Maybe I 'm too
| cynical, but the former seems more popular than the latter.
| cjauvin wrote:
| Following the recent "AI Debate" between Yoshua Bengio and Gary
| Marcus [0], there was a lot of discussion about the exact
| definition (or redefinition even, as some argued) of some labels
| like "deep learning" and "symbol" (what do we mean exactly by
| these?), I find that it is quite relevant to this discussion.
|
| [0] https://www.youtube.com/watch?v=EeqwFjqFvJA
| [deleted]
| choonway wrote:
| Nope. It's just pattern recognition.
| sgt101 wrote:
| What is? I assume you mean machine learning? Ok... What about
| one shot learning like lake and tabembauns bpl? What about
| optimal resource allocation in auctions? Is this recognising
| patterns in event spaces larger than the number of atoms in the
| universe?
| amrrs wrote:
| Francois Chollet's discussion with Lex Fridman (first half) is an
| interesting one on AGI - Video - https://youtu.be/Bo8MY4JpiXE
| dsr_ wrote:
| All programming is, is the reification of decision making.
| shmerl wrote:
| I think a better term you are contrasting it with is artificial
| mind, not artificial intelligence.
| liamcardenas wrote:
| In my opinion, even calling it "cognitive" is too generous.
|
| What makes it "cognitive" instead of just "normal" automation?
| Because it's dealing with information rather than the physical
| world?
|
| I think a better term is statistical or digital automation.
| GuB-42 wrote:
| From the Merriam-Webster dictionary.
|
| Definition of cognitive 1 : of, relating to, being, or involving
| conscious intellectual activity (such as thinking, reasoning, or
| remembering) 2 : based on or capable of being reduced to
| empirical factual knowledge
|
| Using "cognitive" instead of "intelligence" puts the emphasis on
| data processing rather that adaptability, which may be a bit more
| in line with how things are done today. However, it doesn't
| addresses the core of the debate. The usual "[technology] isn't
| [AI/cognitive automation] because it can't do [thing humans do],
| it is just [thing computers do]". Both terms relate to
| consciousness, and are generally considered fundamentally human
| qualities.
|
| I think there is simply no way out of that debate. Maybe use a
| term that it sounds completely unrelated to human activity, maybe
| something like "Big Data Statistical Matching".
| knolan wrote:
| It's curve fitting.
| gfodor wrote:
| It seems unclear if your brain is also curve fitting. Time will
| tell hopefully.
| 0xdeadbeefbabe wrote:
| it's automation
|
| Edit: artificial automation
|
| Edit: computer science
|
| Edit: pseudo science?
| jokoon wrote:
| Intelligence doesn't have a lot of scientific ground either. It's
| pretty hard to define what intelligence is, or at least have a
| scientific definition that is precise enough. The Turing Test is
| only a measure, it doesn't help to reach a definition.
|
| Practical research will always hit a ceiling if scientists cannot
| try to define what they're looking for.
|
| Even machine learning is not a good definition. There are other
| attemps, like "sophisticated statistics" or "statistical
| prediction".
|
| Kudos for this tweet.
| hprotagonist wrote:
| As usual, the monks know what the laity doesn't, and aren't
| particularly afraid to talk about it. Also as usual, there's
| still a yawning gap between what domain experts are up to and
| what non-domain experts think they're up to.
|
| That this is true in AI is not surprising; humility comes from
| knowing that my domain expertise in some fields (and thus a
| clearer picture of 'what's really going on') is guaranteed to be
| crippled in other fields. Knowing that by being in some knowledge
| in-groups requires me to also be in some knowledge out-groups is
| the beginnings of a sane approach to the world.
| Invictus0 wrote:
| The author is just correcting a misnomer. It is not really
| accurate to say that machine learning is intelligent at all, so
| why label it as such? It's confusing for everyone and leads to
| great misunderstandings.
| pmelendez wrote:
| I don't think there are many definitions of machine learning
| that claim the models to be intelligent. Most of them limit
| the term to models that can be built from data.
|
| Learning is a skill that not necessarily comes with an
| "intelligent" label attached to it.
| kkwak wrote:
| Have we even defined 'intelligent' might mean? As in, we
| had the Turing test as a bar and we are close to that
| already. What is intelligence then, last I checked, there
| wasn't a definitive answer do it. We'll need it so that we
| can label AI as I properly - or maybe we don't care so
| much... If it's close enough...
| hprotagonist wrote:
| there are several hundred competing definitions of
| "intelligence". No consensus, as they say, has been
| reached.
| aSplash0fDerp wrote:
| Once we start seeing cheaply made, imported yes/no
| engines (masquerading as AI or knowledge) flooding the
| market, the definition of intelligence will be lost on
| marketing anyways (unlimited data, superfood, etc)
| PeterisP wrote:
| Machine learning is a particular narrow result of studying
| the wider field of artificial intelligence. Just as expert
| systems, or rdf knowledge representation, or first order
| logic reasoners, or planning systems - none of them are
| 'intelligent' but all of them are research results coming
| from (and being studing in) the discipline of studying how
| intelligence works and how can something like it be
| approached artificially.
|
| There's lots in the field of AI that is _not_ 'cognitive
| automation' - many currently popular things and use cases
| are, but that's not correcting a misnomer, that's a separate
| term for a separate (and more narrow) thing - even if that
| narrower thing constitutes the most relevant and most useful
| part of current AI research.
|
| A classic definition of intelligence (Legg&Hutter) is
| "Intelligence measures an agent's ability to achieve goals in
| a wide range of environments". That's a worthwhile goal to
| study even if (obviously) our artificial sytems are not yet
| even close to human level according to that criteria; and
| while it is roughly in the same direction as 'cognitive
| automation', it's less limited and not entirely the same.
|
| For example, 'cognitive automation' pretty much assumes a
| fixed task to execute/automate, and excludes all the nuances
| of agentive behavior and motivation, but these are important
| subtopics in the field of AI.
|
| But I am willing to concede that very many people _are_
| explicitly working only on the subfield of 'cognitive
| automation' and that it would be clearer if these people (but
| not all AI researchers) explicitly said so.
| joe_the_user wrote:
| > _Machine learning is a particular narrow result of
| studying the wider field of artificial intelligence._
|
| I beg to differ, at least as far as terms go now. Neural
| networks lived in the "field" of machine learning along
| with Kernel machines and miscellaneous prediction systems
| circa the early 2000s. Neural network today are known as AI
| because ... why? Basically, the histories I've read and
| remember say that the only difference is now neural
| networks are successful enough they don't have to hide
| behind a more "narrow" term - or alternately, the hype
| train now prefers a more ambitious term. I mean, the
| Machine Learning reddit is one go-to place for actual
| researchers to discussion neural nets. Everyone now talks
| about these as AI because the terms have essentially
| merged.
|
| > _A classic definition of intelligence (Legg &Hutter) is
| "Intelligence measures an agent's ability to achieve goals
| in a wide range of environments"._
|
| Machine learning mostly became AI through neural nets
| looking really good - but none of that involve them become
| more oriented to goals, is anything, less so. It was far
| more - high dimensional curve can actually get you a whole
| lot and when you do well, you can call it AI.
| PeterisP wrote:
| What do you mean by "today are known as AI" and "became
| AI" ?
|
| Neural networks have always been part of AI, machine
| learning has always been a subfield of AI, all these
| things are terms within the field of AI since the day
| they were invented, there never was a single day in
| history when those things had not been part of AI field.
|
| Neural networks were part of AI field also back when
| neural nets were _not_ looking really good - e.g. the
| 1969 Minsky 's book "Perceptrons", which was a
| description of neural networks of the time and a big
| critique about their limitations - that was an AI
| publication by an AI researcher on AI topics.
|
| Your implication that an algorithm needs to do well so
| that "you can call it AI" is ridiculous and false. First,
| _no_ algorithm should be called AI, AI is a term that
| refers to a scientific field of study, not particular
| instances of software or particular classes of
| algorithms. Second, the field of AI describes (and has
| invented) lots and lots of trivial algorithms that
| approximate some particular aspect of intelligent-like
| behavior.
|
| Lots of things that now have branched into separate
| fields were developed during AI research in e.g. 1950s -
| e.g. all decision making studies (including things that
| are not ubiquitous such as minmax algorithm in game
| theory), planning and scheduling algorithms, etc all are
| subfields of AI. Study of knowledge representation is a
| subfield of AI; Probabilistic reasoning such as Kalman
| filters is part of AI; automated logic reasoning
| algorithms are one more narrow subfield of AI, etc.
| ozim wrote:
| I think what parent poster means was that for people who
| don't know better "neural networks === AI". For people
| who now a bit more, there is bunch of other stuff than
| just neural networks, and neural networks are not some
| god sent solution for AI.
| corporateslave5 wrote:
| The thing with differentiating machine learning and AI, is
| that nothing in AI world works except machine learning.
| It's just a bunch of old theories and ideas, none of which
| have panned out
| cgriswald wrote:
| > so why label it as such?
|
| Great misunderstandings are often profitable for those who
| understand.
| Accujack wrote:
| Or put more simply... marketing.
|
| Every new discovery ever, people wanting to exploit it have
| done anything necessary to use people's honest interest in
| new technology and good feeling about human progress to get
| money or power.
| aSplash0fDerp wrote:
| > Also as usual, there's still a yawning gap between what
| domain experts are up to
|
| The best homophone for AI is "beyond be yawned".
|
| Comparitive analysis against refined/biased datasets with
| Kiptronics (knowledge is power electronics/devices) is going to
| change the world, but spectacular fodder is to be expected.
| nickpinkston wrote:
| I see a lot of AI engineers who seem concerned with this
| particular issue, which I never really understand.
|
| Is it because of a perception that most regular people are likely
| overestimating the speed of which AI is going to overtake human
| intelligence? Or more about corp management wanting miracles that
| aren't possible?
|
| Why does this matter and always seem to be talked about?
| UncleOxidant wrote:
| Because there's a history of overhyping ML/AI (whatever you
| want to call it) leading to AI winters. Winter in this case
| being kind of like a recession in economic terms - most
| research funding dries up, etc. We essentially had one of those
| winters from the late 80s until about a dozen years ago. A lot
| of laymen now think of AI as being "magic" that can do anything
| and that's not a good thing when the reality turns out to be
| different.
|
| At this point I don't think we'll see an AI winter as deep as
| some of the previous ones. But we could certainly see an AI
| Fall.
| 0xdeadbeefbabe wrote:
| The name is overhyped and pretentious by itself, and history
| bears this out. Who cares if it's an AI fall or winter if
| it's an AI stupid, because of all the credulous students.
|
| Edit: Russel and Norvig's book is good though
| http://aima.cs.berkeley.edu/
| YeGoblynQueenne wrote:
| >> Because there's a history of overhyping ML/AI (whatever
| you want to call it) leading to AI winters.
|
| Note that past AI winters have not occurred because of
| overhyping _machine learning_. They occurred because of
| overhyping of _symbolic AI_ that had nothing to do with
| machine learning. For example, the last AI winter at the end
| of the '80s happened because of the overhyping of expert
| systems- which of course are not machine learning systems.
|
| Machine learning is not all, not even most, of AI,
| historically. It's the dominant trend right now, but it was
| not the dominant trend in the past. The dominant trend until
| the 1980's was symbolic reasoning.
| radarsat1 wrote:
| But symbolic reasoning mostly worked, did it not? However,
| its Achilles heel was that for it to be useful, it's
| necessary to distill a lot of domain knowledge into a
| format that can be processed by an expert system. That
| means, writing 10s upon thousands of rows of "if then then
| that".
|
| Machine learning is different in that it is more amenable
| to distilling those rules from the data automatically. It
| is successful where symbolic reasoning failed because it
| can go from the raw data. A good portion of machine
| learning research is in new ways to preprocess and format
| data into a structure that can be further consumed by
| linear algebra, which turns out to be a lot easier and
| practical than figure out a huge database of sensible first
| order predicate logic statements.
|
| If ML techniques can be used to feed symbolic systems, the
| latter would show promise again, which is already happening
| in recent trends in causal inference and graph networks.
| The marriage of these two fields is inevitable, and has
| already started.
| UncleOxidant wrote:
| There was a neural net popularity surge in the late 80s,
| early 90s. Of course, the hardware wasn't there yet to be
| able to deliver on the promises. I was in a Goodwill book
| section about a year ago and there were a couple of NN
| books from that era on sale for $3, one titled "Apprentices
| of Wonder: Inside the Neural Network Revolution" from 1990
| and the other was for programmers and included C code for a
| NN to predict the stock market from 1989. Anyway, that all
| had died out by about '92 or '93 and NNs were a pretty dead
| academic topic until about 2005 or so when they figured out
| that GPUs could be used to accelerate them.
| twblalock wrote:
| It seems analogous to Searle's "Chinese Room" argument:
| automated responses to predefined stimuli isn't the same as
| "intelligence" or "understanding".
|
| The OP suggests modern AI is a fancy way of teaching systems to
| effectively hardcode or automate their behavior themselves.
|
| I'm not sure why that matters, as long as the results are what
| we aim for. It's not like most AI researchers are trying to
| create sentient artificial life-forms.
| taurath wrote:
| Interestingly though, at the population level it can seem a
| lot closer.
| mattkrause wrote:
| It matters because the hard-coded behavior is brittle and
| often doesn't do exactly what we want (or think).
|
| For example, GPT-2 has been ascribed nearly magical powers:
| it's a knowledge base, it can play chess, it does calculus,
| it's a dessert topping AND a floor wax!
|
| When you look closer, however, it doesn't do any of those
| things particularly well. It can regurgitate something that
| looks like a true fact--or its negation with equal
| probability. It doesn't quite know the rules of chess. It
| needs a solver to check that the solution to an integral is,
| in fact, a solution.
| whatshisface wrote:
| All of those caveats apply to human intelligence, but to a
| lesser degree. Kids can play chess without exactly knowing
| the rules, and come on, everybody needs to check their
| integrals.
| TallGuyShort wrote:
| Personally, when a lay person asks what I do, I like telling
| people I work on "Artificial Intelligence software" because
| it's the most accurate term that doesn't (a) get an immediate
| request to implement their app idea for them and (b) require
| explaining what machine learning / deep learning is.
|
| But beyond that I hate the term within the industry because I
| think artificial intelligence gets equated with a Jarvis-like
| general AI that will talk to you like a superhuman servant. I
| get the desire to better define the current state of the art.
| But for most people, I agree it's going to seem like pedantry.
| radarsat1 wrote:
| > artificial intelligence gets equated with a Jarvis-like
| general AI that will talk to you like a superhuman servant
|
| to be fair, for a lot of researchers, that _is_ the ultimate
| end goal, even for those who admit we are not even close to
| it. I for one first got interested in AI from an 80 's movie,
| can't remember which, with a character who talked to his
| computer, which talked back. Since those early years, I
| haven't spent even one second _working_ on actual AGI, seeing
| the plethora of subgoals needed to get there, but..
| _thinking_ about it.. plenty. that dream is a driving force
| behind more ML /AI researchers than maybe you think.
| Particularly in the RL community I would guess.
| laichzeit0 wrote:
| There's already a term you can use. "Statistical learning".
| There's even a well known important book with that title:
| Elements of Statistical Learning.
| TallGuyShort wrote:
| There are books well known in the field with "machine
| learning" in the title. I don't think that's any clearer to
| a lay person.
| wayoutthere wrote:
| It's because this kind of hype inevitably leads to a trough of
| disillusionment -- the methods we collectively call "AI" today
| are never going to lead to a general-purpose artificial
| intelligence. People are disappointed we don't have self-
| driving cars yet, but it's not clear whether that problem
| domain is constrained enough for deep neural networks to solve.
|
| What we have developed are ways to automate complex tasks
| within a constrained input domain that can be easily
| quantified. It seems like magic, which leads people to say that
| it's "AI" but in reality it's just a complex automation built
| through reinforcement techniques that leverage some clever math
| tricks. Throw an unexpected input or new set of circumstances
| at the model and you get interesting results.
|
| It's not a sense that people are overestimating the speed with
| which AI is going to overtake human intelligence -- it's that
| the techniques we're using today that we call "AI" are not
| capable of doing anything of the sort.
| hunter-gatherer wrote:
| This. Working in big Corp and Government I have seen how far
| this disillusionment can take an organization down the wrong
| road. Learning how to articulate complex technical /
| scientific topics to bureaucracy, I am learning, is a very
| valuable and needed skill amongst engineers.
| wayoutthere wrote:
| It's a fine line you have to walk. They usually are looking
| for a person who will tell them what they want to hear, so
| it's usually a matter of starting with "the art of the
| possible" (aka a bunch of bullshit they heard on NPR) and
| working them over to something more realistic.
|
| I've found it helps if you can frame it in the context of
| the other options (i.e. agree with where they want to go
| and present multiple ways to get there) they're more
| receptive. Leaders know about these hype cycles too, but
| they often have to play along for political reasons and
| they'll be thankful if you work with them rather than
| against them.
| liamcardenas wrote:
| Andrew Yang is a serious contender for the US presidency whose
| entire platform rests on assumptions about AI. He wants to
| fundamentally reshape welfare in the country and implement an
| entirely new tax. Thinking clearly about AI is therefore very
| important, as it is having real and substantial political
| implications.
| chillacy wrote:
| I remember him a year ago saying stuff that wasn't
| particularly mainstream, like warning about fast food
| cashiers being replaced by kiosks, malls closing due to
| competition with Amazon, call center workers being automated,
| etc.
|
| These are all things that are coming, I have peers working on
| some of them, but they aren't particularly mainstream, even
| though the most accessible jobs in the economy fall under
| those categories.
| chrshawkes wrote:
| Luckily he won't be elected and shouldn't if he really thinks
| AI (in its current form) will solve these problems.
| jimbokun wrote:
| He doesn't think it will solve them, he thinks it is going
| to cause them, and that we need to be ready with solutions.
|
| Take Universal Basic Income. He is predicting far more jobs
| are going to be automated in the near future than most
| people expect, and something like UBI will be needed to
| keep the people out of work from starving or rioting.
| deesep wrote:
| When machines transcend beyond their programmed limitations to
| shape their environment in their own image, then they become
| truly intelligent.
| ForrestN wrote:
| Why would a non-human intelligence necessarily have a drive to
| "shape their environment?" Maybe a non-human intelligence would
| discover the inevitable end of the habitable universe and opt
| to just do nothing?
| whatshisface wrote:
| Nobody's going to pay for AWS hours for a lazy robot. They'll
| keep changing it does something. The human drive, which is
| not essentially rational, will give birth to the machine
| drive, which won't be rational either.
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