Emotion Science Keeps Getting More Complicated. Can AI Keep Up?

https://howwegettonext.com/emotion-science-keeps-getting-more-complicated-can-ai-keep-up-442c19133085

by imartin2k • 8 years ago

58 24 8 years ago

Xcelerate4• 8 years ago

Psychology needs to start moving away from trying to categorize things into these arbitrary fuzzy human buckets ("emotions") and toward being able to predict things. If someone is diagnosed with "X", the most pressing question is now: how is this diagnosis useful to that person or society? Is the person trying to change from the state they are in to a different state? If so, does knowing they are "X" or feeling "Y" help with this goal? I would argue that for the past few centuries, no, this process hasn't helped very much.

For instance, consider the DSM description of borderline personality disorder:

"BPD is a pervasive pattern of instability in interpersonal relationships, self-image, and emotion, as well as marked impulsivity beginning by early adulthood and present in a variety of contexts, as indicated by five (or more) of the following:

- Frantic efforts to avoid real or imagined abandonment

- A pattern of unstable and intense interpersonal relationships characterized by extremes between idealization and devaluation (also known as "splitting")

- Chronic feelings of emptiness

- [...]"

You get the point. You have to meet five or more of the listed criteria. Not four or more. Not six or more. But five or more. There's a lot of ad hoc, informally specified, subjective criteria that probably have no reproducibility if ten different psychologists were all told to independently specify which of the above criteria a given patient satisfies. See the recently published update on the reproducibility crisis: https://www.the-scientist.com/news-opinion/half-the-time--ps....

In general, psychology doesn't seem to be based on many of the lessons acquired in the physical sciences over a very long period of time, and there doesn't seem to be much math involved. Open a textbook on quantum field theory and open a textbook on psychology, and notice the main difference between the two. Data on people is scarce, often biased, improperly sampled, and study results are frequently cherry-picked to promote some sort of predetermined narrative about how the human mind works. The human brain is one of the most complex objects in the known universe, and pretending that we have a modicum of understanding about this object is the type of overconfidence and hubris that will lead to centuries of inadequate mental help for people that need it.

What's the solution? Start collecting data and start trying to quantitatively predict things. I have no doubt that machine learning will fail to predict human behavior, but I also have no doubt that it will fail much less drastically than the current approach. Outcomes need to be strictly measured. In this case, I don't think we are as interested in "explanatory" science as we are "predictive" science; i.e., we don't care as much about why the blackbox model works as long as it improves people's lives. Consider for instance the current system of categorizing personalities: the "Big Five" system (OCEAN). Why is this still a thing? Any sort of primitive GBDT would almost certainly perform better than this, so it's a mystery to me why these crude systems are still being used in the mental health industry in 2018.

trevyn• 8 years ago

OCEAN is useful in predicting human behavior because there are certain common constellations of human behavior and disposition, and the meanings of the dimensions are easily understood by today’s humans. There certainly exists a more efficient representation, but machine-learned dimensions often don’t have easy analogues to existing human words.

Agreed that the DSM is kind of silly in that it draws arbitrary boundaries, but again, it’s pointing at common constellations of characteristics that are absolutely statistically predictive of behavior.

The underlying problem is that we are only just beginning to be able to formally represent complex behaviors in terms of underlying neural activity, and until we can do this fully and properly, there are still useful analyses that can be performed, they’re just “fuzzier”.

winchling2• 8 years ago

Start collecting data and start trying to quantitatively predict things

One can't start collecting data until one knows what to measure and why. We normally start with problems.

Psychologists have made little progress, as far as I can tell, because they unwittingly chose a hard problem: how does a general problem-solver work? They've actually been trying to solve AGI but without the tools of computer science.

The human brain is one of the most complex objects in the known universe

Otter hardware seems good enough:

https://www.youtube.com/watch?v=zGTzclrsujA

Xcelerate4• 8 years ago

We normally start with problems.

I never said we didn't. Why would anyone collect data without knowing the problem that it will be used for? That's implicit. I don't need to directly state the obvious.

Otter hardware seems good enough

Ok, here's a technical description of what I meant by "complex object": an object whose output is in theory capable of being represented by a universal Turing machine that is significantly shorter in length than the output itself but is still longer than the output of other objects that humanity has interacted with and is capable of observing. I think you'd be hard pressed to argue that the Kolmogorov complexity of an otter's brain is greater than that of a human's.

huahaiy2• 8 years ago

You may not realize, OCEAN is precisely the outcome of approach you seems to suggest. It’s called psychometrics. If you open a textbook on that subject, you will feel at home if you are a statistitian. If you believe anything else can perform better, you are welcome to try. I predict you will be humbled in the process.

Xcelerate4• 8 years ago

I've perused the literature on the subject (but have not conducted any research of my own). The deficiencies of the five-factor model are well known; I don't think that's a particularly controversial statement among the researchers in the field. See, e.g., this publication in the American Journal of Psychiatry with 283 citations:

https://ajp.psychiatryonline.org/doi/abs/10.1176/ajp.161.10....

This is a much better model, but going from research to clinical practice seems to be a very slow process.

jpfed• 8 years ago

Just FYI, calling the Big 5 a system for categorizing personalities would be like calling the coordinate plane a system for categorizing positions.

BenMorganIO5• 8 years ago

A lot of your post is wrong. By just reading the initial bit, emotions aren't fuzzy. Ekman's work and many others were very based on quantifying them rather than qualitatively identifying them. You should look up the work is done for clinical psychology with emotion recognition and the muscle system for measuring facial movements. You'll see it wasn't so fuzzy as one may think. It's very precise.

In general, psychology doesn't seem to be based on many of the lessons acquired in the physical sciences over a very long period of time, and there doesn't seem to be much math involved.

This is just so wrong. Ten years were spent developing a mathematical system called the Facial Action Coding System: https://en.wikipedia.org/wiki/Facial_Action_Coding_System. This system is used to add together all the muscle movements of the face. When this is done, you can discern from the muscle movements what emotion is being displayed.

Emotion science is known to be a field of psychology that really thrives from science. I can't think of any other field where BA's and BSc's can work together on their research and where MD's can reliably use the work they develop. There's very little fragmentation and the work each group does and contributes to the other is valuable.

Emotions are so deeply tied to the sciences that you can see them occurring in the brain as you give it an MRI. The amygdala activates and registers uniquely for each of the six emotions.

All basic emotions originate from the amygdala. All basic emotions are displayed universally and symmetrically (perhaps with the exception of contempt, but a whole article can be done on that), all basic emotions on the face, all basic emotions are universal, and all basic emotions register as we see other basic emotions.

The last one is interesting. When it comes to clinical psychology, we can actually see patterns in emotion recognition and tie them to mental health disorders. Borderline Personality Disorder scored on par with a baseline, but they selected anger as the emotion when defaulting. Bipolar assumed more emotions were happy during mania periods and sad during depressed periods. Anti-Social saw people who failed to reach par with baseline with either failing to recognize fear or failing to recognize disgust in other individuals.

On top of that, we also know that displays of emotions are important as well. Major Depression saw individuals display a wide array of emotions; almost like they were screaming for someone to see their feelings. And then, psychologists also saw Major Depressive people exhibit minimal emotions with slight movements in the upper face. These people were in a completely different segment and were at a high risk of committing suicide.

We can derive from the muscle movements, the activation of the brain, how these expressions are universal, and how we can mathematically that this science is not "fuzzy". There is a lot of hard work and much consideration from all facets of research that contributes to these results.

Bartweiss3• 8 years ago

The history-of-psychology content here is fascinating - it's hard to overstate the harm done by Ekman's theory to everything from police investigations to Pysch 101 textbooks. But the attempt to tie AI into all of this is weirdly presumptuous. It assumes that the progress of AI development is predicated on psychology theory without supporting that claim in any way. The rebuttal is painfully obvious: children learn to read emotions without some grand backing theory, so why do we assume AI will need one to reach human levels?

It ought to be telling that this is a piece about AI written by a historian, citing a psychologist, a historian, and a fictional philosopher - but not a single person with an AI or even computing background. The result is a painfully slow and sloppy retreading of existing ideas. First p-zombies and then the Chinese Room question are sketched out without any reference to that original work, ending with a question-begging assertion that perfect imitation of an emotion is meaningfully different from feeling the emotion.

The first article in the series, grandly titled Silicon Valley Thinks Everyone Feels the Same Six Emotions, is even worse. It critiques Ekman and his work with the TSA, then talks about Alexa, but offers no evidence at all that Alexa or any other Valley project involves Ekman's six-emotion model. (Anyone with a cursory knowledge of machine learning will tell you that it almost certainly doesn't. Reducing inputs down to six artificial categories is not the sort of thing that improves training.)

Given all of that, the parting shot of this piece is especially galling. After indicating total unfamiliarity with AI theory, AI ethics, and post-1970 philosophy in general, the author blithely declares: "if I were contemplating a career in philosophy right now, I’d be thinking about making my central field the ethics of emotion AI. There’s much to be done."

jack_pp• 8 years ago

Children learn to read emotion using a brain that evolved to do so over millions of years

snowwrestler• 8 years ago

Yes, and children experience emotions before they learn to reason or use language, so they have a personal basis to work from when learning to reason about the emotions of others.

"Empathy" is the name of the reasoning process by which children analyze the experience of their own emotions and behaviors, to draw inferences about the emotional state of others based on observing their behaviors.

But long before that, they are reacting emotionally to the behaviors of others. For example, you can scare a baby.

BenMorganIO5• 8 years ago

The scale of the learning is interesting in itself. From a few months, to years old, to all the way to preteens, emotions are constantly being reevaluated and developing new ones as well.

Bartweiss3• 8 years ago

True, and I don't mean to underplay the difficulty of that style of learning. In particular, it seems important that our emotion-reading is reflexive - we learn to map other people's expressions to our emotions, and it's not clear how similar a learning process without some reference class of emotions.

(We have a decent example in autism of how emotion without instinctive mirroring plays out in learning emotional signals. The associations are learned consciously, which works out alright. But I'm not sure there's any precedent for people who have mirroring but nonexistent emotions. Is there something like abulia for lack of emotion? ...is it abulia?)

I'm going to stand by the original statement, though. We have proof that this sort of learning without a backing theory can be done, and no real evidence that having a general theory would make it easier to actually learn the specific associations needed to make predictions. To steal an example from the article: knowing whether the six-emotion model is right or wrong doesn't automatically help us recognize a clenched fist as threat or celebration, and fretting about the impact of psych textbooks on AI without proposing an actual connection isn't particularly compelling.

mr_overalls• 8 years ago

“The question of whether a computer can think is no more interesting than the question of whether a submarine can swim.” ― Edsger W. Dijkstra

Replace "think" with "emote" and the insight of the original quote still holds true, I believe. The advanced of artificial intelligence is not built on a bedrock of psychological understanding of human emotion.

ninegunpi• 8 years ago

We may never be able to build a machine that can recognize the full diversity of human emotional experience

Even humans have a lot of problems recognizing full diversity of their own emotional experience, unless trained appropriately.

Emotion Science Keeps Getting More Complicated. Can AI Keep Up?

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