Transcript: 'How AI Can Help Fix Our Brains'

The transcript of AI & I with Awais Aftab is below. Watch on X or YouTube, or listen on Spotify or Apple Podcasts.

Timestamps

1. Introduction: 00:01:20
2. The case Awais makes for pluralistic thinking in psychiatry: 00:03:38
3. A pragmatic approach to mental healthcare: 00:15:30
4. Awais’s take on why Dan’s OCD diagnosis took 10 years: 00:19:04
5. Why psychiatry is stuck where machine learning was decades ago: 00:24:19
6. Why psychiatry’s focus should shift from explanations to predictions: 00:31:05
7. How Awais thinks AI is already changing the psychiatric profession: 00:39:19

Transcript

(00:00:00)

Dan Shipper

Awais, welcome to the show.

Awais Aftab

Thanks, Dan. I'm happy to be here.

Dan Shipper

Happy to have you. So for people who don't know you, you are a psychiatrist. You're the clinical assistant professor of psychiatry at Case Western Reserve University, and the editor of Conversations in Critical Psychiatry. For people who are listening, who are watching, who are like, why are you on AI and I, I promise there's an explanation. I've been really obsessed with how AI might change science in part and in particular how it might change psychology, psychiatry, neuroscience, more complex areas of science where science has historically struggled and while you don't write specifically about AI. I've been reading your Substack for a while and we'll link to the show notes. I love it and I love your perspective, and I just feel like there's a lot of overlap in some of the things that we've been thinking about. And I wanted to understand more about your ideas and talk through some of the AI stuff and see if you think I'm crazy or not.

Awais Aftab

That sounds great.

Dan Shipper

Cool. So I think, if I had to pinpoint the one of the things that I like most about your work is I think most people who work in psychology or psychiatry doing research want to come up with a single theory that's like depression is anger turned inward, or it's serotonin imbalance, or it's this or I think those kinds of single theories are quite valuable. I think it's the intellectual lineage of them, which we can sort of trace back to physics and stuff makes a lot of sense, but they haven't worked that well in the domains that you care about, the domains that I care about and I think you tend to advocate for something called explanatory pluralism, so the idea that when we're when we're working in a domain-like psychiatry you have to bring to bear multiple different perspectives to really get a sense for the thing that you're trying to understand. Can you unpack that a little bit more for us?

Awais Aftab

Yes. And I'm glad to hear that this is an idea that has resonated with you quite a bit and one of the things that I've been trying to do is to promote more pluralistic thinking in psychiatry and clinical psychology. And I think that there are two ways we can understand this idea of pluralistic thinking. One kind of takes inspiration from this general philosophical attitude, what we call scientific pluralism. That things can be explained even within the realm of science.

Through a variety of different theoretical perspectives that rely on different assumptions, different background ideas, and that each perspective might offer certain theoretical advantages or empirical advantages. But there isn't necessarily one single correct, true perspective, but things are multifaceted and that multifaceted nature is not captured by one theoretical kind of perspective. And this applies particularly in situations where phenomena do not possess a singular essence. When something possesses a hidden property that makes it what it is, often identifying that essence is the single best way of characterizing that. I think a good example of that would be the periodic table of elements in chemistry.

It captures something really very real and objective about the structure of elements, the way their atomic nuclei constituted tremendous predictive power. And if different kinds of chemists at different points in time start out from different theories of what chemistry is if they do science well enough, they will all kind of converge on that kind of thing. But there are other phenomena than that. Don't have that kind of singular hidden essence behind them. And they can be theorized and conceptualized differently. And this is particularly the case in psychology and psychiatry where these phenomena are really complicated. And so the one idea simply is that there isn't a hidden essence. We have different ways of describing, explaining, understanding these ideas, and they come with advantages and disadvantages. But one is not a knockout winner, one doesn't displace the others. I think that that's the fundamental sentiment behind explanatory pluralism. Science is particularly, too, because we are dealing with a mind-body split. So there are theoretical perspectives that are more grounded, for example, in neuroscience trying to look at brain circuitry and receptor actions and other biological processes.

And then there are explanatory perspectives that are more that utilize cognitive terms or utilize kind of psychological f forces and unconscious psychological dynamics, etc. So there we are dealing with that split kind of thing. A related idea that often comes up is that of levels of explanation that things can be described at different levels of organization, different levels of coherence and that different levels in walk different kinds of relevant concepts so there is the physiological kind of level neurophysiology biology, there's kind of cognitive stuff, there's psychological stuff and then there's kind of there's social interpersonal stuff which happens because of multiple brains interacting with each other. And so there's this idea that when things interact new properties emerge that cannot be described adequately using concepts of the lower level. Sometimes people talk about pluralism in the context of psychiatry and psychology, just in the sense that these phenomena transcend multiple levels and can be described at multiple levels of organization.

Dan Shipper

That's really interesting. You said a lot there that I want to unpack so I think the first thing that, the first thing that made my brain go, ding ding, I want to talk about that, is you're talking about the periodic table of elements. And the idea that there are these sort of objective things that anyone who's doing science while I was going to find a periodic table of elements, you can organize the elements in such, in such a way that when you're going to transform an atom from one element to another and basically anyone's going to find that. I'm curious how, but there are other things that can only be described with different ways of looking at them and different different perspectives. I'm curious about your thought, and this is maybe getting a little philosophical really quickly, but there are a lot of, there are a lot of philosophers of science, for example, who might argue that even the periodic table of elements, that's one way to look at carbon for example and if we had a different set of requirements or a different set of intuitive ideas about how to interact with reality, we might find something else or structure things differently. So are you saying that or what are you saying? How far does this kind of pluralism go?

Awais Aftab

Yeah. So I mean, even in things like physics and chemistry or a situation like a periodic table it doesn't it doesn't necessarily mean that we have to rely on the periodic table description at all times. And other things have no role, but rather so it's very context dependent. So there can be other theoretical ways of looking at how to think about elements or how to divide them or map them up. And there might be certain contexts in a certain situation in which you want to achieve a certain goal. And that goal is best achieved using a classification of elements that is not the one that comes from the periodic table of elements. I don't know enough about fundamental physics to theorize what they would be, but I can imagine we can, we can theoretically imagine situations where a different, an alternative classification offers some advantage or benefit in a particular context. And so if we can imagine that, and in those concepts it would be very, it would be useful it would make sense to utilize the alternative one but, the priority of elements possesses such immense explanatory power that the majority of situations and the majority of context is going to be the useful one to use vs. there are other situations where there isn't a single perspective that dominates it in the same kind of way maybe 60 percent of the time or something. But there's going to be significant cases in clinical work or scientific work where we are relying and using other perspectives.

Dan Shipper

But aren't we sort of sliding in something that's sciency. I basically, I agree with you, but I want to present the other side of it, which is: By saying that aren't we sliding into something that's fundamentally unscienc-y? Because science is really about finding those context free, ultimately generalizable rules or facts about reality. So once you start to say, well, it's contextual. Is that really the goal of science?

(00:10:00)

Awais Aftab

So philosophers of science have been thinking about these things for decades and if not centuries and ultimately it all comes down to some form of context or another. The reason is that we don't have direct access to whatever mind-independent reality there is, so whatever the external reality is. We don't have direct access to that. We only have access to what we perceive or what we detect by means of other instruments or by means of experiment with you. So we have to make inferences based on the data that we are gathering and any kind of data that we are gathering, it is taking place in a certain way. Research context or in a certain scientific context. It is guided by certain theoretical assumptions and so are all observations, so philosophers often talk about all observations being theory laden, that there is no, there is no theory free observation. Because any observation you're making, you're making that within a certain theoretical context within a certain framework within certain goals. And they can change now. Some of the most fundamental theories that we have in science work really well in basically all contexts that we can apply them to and until we start encountering situations in which they don't apply. For example, quantum physics, there's so many aspects of it that we don't understand. Huge debate, but as far as empirical predictions of quantum physics are concerned, so far they have been unsurpassed, they have repeatedly proven true again.

So that's a really powerful theory that gives us a lot of power so there are the fundamental theories that tend to apply in all situations that we currently possess, but there would be new, fewer future situations in which they may not apply vs. then there are more, then there are theoretical models that are more circumscribed in scope that work well within certain contexts, but outside of that they don't work very well. And then this may be because they approximate something about that larger theory considering Newtonian laws of motion. They work very well within ordinary speeds but once we cross certain thresholds, they're not not as applicable so one way of thinking about this is in this respect, and then there are other situations in which we're simply dealing with very different kinds of phenomena.

So in physics we have the theory of general relativity at one end, and we kind of have quantum physics on the other end. And at the moment physicists kind of juggle and move back and forth between the two, depending on whether they're looking at galaxies or whether they're looking at Microsoft. And right now we don't have a way of unifying them. There may be a theoretical way of unifying them, but we don't know. And in a similar kind of way, we can think about theories that are examining the psyche from the cognitive framework in terms of predictive processing of beliefs again, these are things we're inferring because we don't we can observe them or we can kind of look at, look at these things from from a from a brain circuit perspective or kind of neurotransmitter perspective some of it is methodological as well. Can we unify them at some point? Perhaps we would want to, and what that would look like. We don't know. But we are not there yet.

Dan Shipper

Yeah, I agree. And it seems like probably the history of science, if you go back to Newton, is finding something that we think is super general and then realizing that it's actually contextual. We just didn't have a way to access the context in which it wouldn't hold.

Awais Aftab

Yes. This is and there's this again we hear these terms, the terms realism vs. anti-real in philosophy of science, which refers to the idea that these unobservable entities that we are hypothesizing what kind of status do they have, and realism, at least the kind of naive realist view is that the un unobservable entities really exist vs. kind of the anti realistic and anti-realist kind of view would be that these are perhaps useful fictions that we don't know what kind of reality they possess. We just know that they are useful enough that they guide our empirical work and they make predictions that turn out to be true.

Dan Shipper

Where do you fall on that continuum?

Awais Aftab

I think I take a more pragmatic view towards these things, which in some ways bridges the two, which has kind of one leg in realism and one leg in anti-realism.

Dan Shipper

And you mean philosophically pragmatic? The school of philosophy, pragmatism. Can you just tell us for people who don't know what that is, generally what that is?

Awais Aftab

Yeah, pragmatism by itself is a pretty broad term, but generally what it does is that it shifts the focus away from certain metaphysical questions towards our ability to make use of concepts in the world. It asks questions about what it is that we can do with a certain theoretical concept. What are its uses? How are we applying it? And it judges what a theoretical perspective is offering or how we understand any particular phenomena based on how it is being utilized in practice.

Dan Shipper

Yeah. So instead of asking, is this true, it's asking, is it useful for me to think of it as true and what can I do with that if I do.

Awais Aftab

Yes. And that’s a simplistic version of that.

Dan Shipper

Yeah there's a lot in there, but I want to get into psychiatry, psychology, and I think the reason that I am so into this, other than it's just fascinating. I have OCD and it was a mess for me to even figure that out. And it took 10 years and I went to a bunch of different therapists and eventually, I was just reading a bunch of stuff and I was like, I think I have OCD and there's a lot of debate about whether that's even helpful. For some people the label is bad. For me, it was quite freeing because I was like, well, for OCD, typical talk therapy tends not to work that well until until treatment is much better managed and even once I had gotten into the correct treatment for it, so exposure and response prevention that it took me a while to get to someone who actually even practiced that well enough for it to work and then it was a fucking nightmare to get on medication but once I did, it's been amazing. It literally changed my life. I'm a completely different person. And during that whole time, I've also just always been interested in philosophy of science stuff. I was like, the way that this works is fundamentally broken and bad and it's bad for me too. Talk to me about that.

Awais Aftab

Yeah And actually I think a lot of people. We'll relate to what you're saying and in my own clinical practice one of the diagnoses that seems to have been missed by other clinicians a lot is obsessive compulsive disorder, OCD, where people will have histories of being treated for depression and anxiety. And yet kind of I do a comprehensive interview and I'm like I think you have, I think you may have OCD and suddenly things are clicking into place for them. And I think the reason is that for one reason, one, I think it's not as popular of a diagnosis in the cultural imagination as things like depression, anxiety, or ADHD. So oftentimes when here's the thing in the psychological realm, even when we are describing, characterizing, talking about a phenomena, it is very sensitive regarding the language we use to even even talk about it. So, but what happens is that if someone, for example, if a person has no idea of what the OCD even is, they have never heard of it. They’re not familiar with obsessions in the technical sense. They might notice that they're getting really anxious. They might notice that they're having a lot of repetitive intrusive thoughts that kind of make them uncomfortable. One person might just think that, oh, I'm just, I'm just a really nervous person, or I just have really bad anxiety and this anxiety, and then my anxiety is just causing me kind of like these kind of really nervous, anxious thoughts.

(00:20:00)

Another person might think that. I have some kind of paranoia. I'm getting these really weird, scary thoughts that make me kind of uncomfortable. I may have paranoia or something like that, and another person just might interpret them. I get these racing thoughts, maybe I have some kind of bipolar, I'm getting these weird races there. So depending on how someone, the language someone might use to describe them. It might shift them in one or a different diagnostic direction. So it takes familiarity with a number of different di diagnostic categories to begin to recognize which direction is going. So one, oftentimes patients themselves don't tell the clinician that they, oh, well I'm having obsessions. Because they don't use that language. They'll say, I'm anxious, I'm having nervous thoughts, etc. And it would take a somewhat astute clinician to kind of do a good interview and pick up on the fact that someone is having intrusive thoughts and then ask further questions.

So I think that's one big difficulty and when you do have the right match, when you can match someone's presentation with this idea of OCD you can guide them in the right direction towards the right treatments that have been studied and that are known to work better. Exposure prevention, the other forms of psychotherapies, and then medications as well oftentimes we were using the same serotonin-based medications and other ones, but the dosages required are often different augmentation strategies are often different. So and so you're probably familiar, there's a lot of psychiatry discussions in the mental health ram and some people just say that, oh, we should just abandon all diagnosis and I think how can we talk accurately about these things with our diagnostic language?

And so I feel strongly that we need more sophisticated ways of talking about these phenomena. Now, the challenge here is that we can think, oh, obsessive compulsive disorder. It means that it's a thing in the brain that explains this category. There's some kind of a singular brain dysfunction that explains all of these symptoms. And so that's where I think people go wrong, where if they start thinking of categories in that manner and so OCD, as far as we know, it's not one thing. In fact even from a symptom standpoint, it has fuzzy boundaries. So its boundaries overlap with other anxiety disorders, overlap with depression, with other kinds of things. And biologically speaking, there is no one single thing that makes OCD, OCD, but rather its variety. So we have to respect that heterogeneity. But it offers us a certain descriptive potential. We can talk about it, we can identify it, we can use it for guiding treatment and so this would be a good example of something that's very helpful pragmatically. It's an entity that exists from a pragmatic standpoint, but not from an essentialist point of view.

Dan Shipper

Well, and, but the interesting implication of the pragmatic idea is that for some people it's not helpful and so part of being a good clinician is knowing when it is and is not helpful. And I mean, you're going to mess it up sometimes, but that's a really interesting thing, right? Because I think the entire thing, you've just led me into AI land. Thank you for that.

I think there's a lot of pressure to be able to reduce these things down into a checklist, right? Even if you don't have any clinical experience, you can just know I checked that off. I checked off the box. He has OCD or whatever. And I think what one of the things you're saying is you can do the checklist, but really you need to have, a good clinician has a little bit of a smell for it and I know and I can kind of explain this case why, but I can't fully. I think there's one, there's sort of scientific academic pressure to have a really clear cut theory that you can just write down exactly, this is exactly what it is. And then there's also a lot of like cost considerations and just scale considerations of if we want to if we want to make treatment available to a lot of people, then we need to be able to reduce it down into here are the rules for how to diagnose it and how to treat it.

And we make basically manualize therapy which has some works to some degree, but is not the same thing as the really, really skilled clinician so to get to my AI point these these questions are exactly the kinds of questions that early machine learning researchers faced, which is if you want to recognize a letter, you want to do character recognition do we define what an A is? Do we create a bunch of rules for it? And if so, there's a lot of different situations in which something might meet, might be an A, but it doesn't look at all like an A, it's very contextual. some people went down the route of let's define all the rules which did not work but what what ended up working is deep learning where basically what you can do is feed in a lot of examples into a neural network and the neural network creates distributed representations of that of whatever the examples are such that no individual neuron knows like, hey, this is like an A, but altogether basically, when you feed something into a neural network, what the network is doing more or less is testing out a bunch of different hypotheses for what the letter could be, and whether it could be all at once in a non-rule-like way, and then outputting, I think this is this is basically a without any individual neuron. Knowing the rules but at a high level, you may be able to say generally if the a has a little thing at the end, then it's going to say it's an A and so that's the, the basic kind of parallel I see to machine learning stuff. I'll stop there, but there's more stuff going on there. Is that something that you've run into before or thought about?

Awais Aftab

Yeah I mean, I think I think there's this recognition that this is what we call the space of psychopathology. So this kind of thing is an abstract conceptual space of the way symptoms are distributed in the mental health realm.

What are the ways in which this space of psychopathology can be carved? The original idea, the hope for a lot of people was that we can find single big causes or we can find essences and that'll provide us the way to carving this space. We can carve it, the nature at its joint kind of thing. And then now we recognize that, oh, it's just this big fluid fuzzy mess of. Interacting causes and mechanisms and you can just really map it in many different ways. So we have used different strategies, basically the what the DSM, ICD etc. have been doing in or in over the past 50–60 years is that they have been relying on clinician observation. So they started with clinician observation and kind of refined it through operationalization, etc.

There is an alternative effort called high top or hierarchical taxonomy of psychopathology that uses more statistical techniques like factor analysis and other PCA analysis to see patterns of symptom covariation. What if you change one symptom, what symptom changes with it? And it has come up with an alternative dimensional mapping of these symptoms, but the space of how to classify them is very flexible and they're more innovative ways you can do that. And this is where probably AI and machine learning, deep learning come in. It can help us identify new patterns and new ways of talking about the space of psychopathology that we might not have thought of ourselves. And I think people are looking into it and kind of approaching this to my understanding, I don't think it has produced any actionable results yet. I don't think it will come up. Someone has come up with a new mapping that it, that seems very useful and that has, but it, but I think in theory that's possible. I think it would be exciting to see.

Dan Shipper

Well, I think the interesting thing to me is— So one is talking about observing clinicians and then reducing how they operate to diagnostic rules. That's exactly how machine learning researchers started in AI and it's exactly what didn't work. It does work now, once you have a deep learning foundation, it does work now but at the very beginning when you're just trying to make it a checklist of rules instead of like a sort of fuzzy pattern matcher, it does not work very well. But I think the interesting thing to me is about factor analysis or high tops or whatever you're still trying to say like, why? So if there's OCD caused by some constellation of different factors, we can at least say what the factors are. And I think one of the interesting things to me about or one of the other interesting parallels to me about AI stuff with psychology and psychiatry is I think the development, for example of OCD or whether or not you're going to have OCD or whether or not it's going to work.

(00:30:00)

That question is a predictive question. I don't know how familiar you're with the way that language models work, but it's a little bit the way that language models work to predict the next word. So the way that a language model predicts the next word is it looks at the context of all the words that came before it, and it's been trained that all the words that came before it. Each changes the probability of the next word in the sequence and each affects each other. So all the words get a chance to talk to each other, and then all the words get a chance to basically figure out what comes next. And there's no one set of rules and you can't really, I mean, it does learn the rules of grammar. So there you can overall see it and be like, it knows grammar. Yeah, but if you're trying to understand, for example, when it might use the word OCD. It's very hard because it's so multifaceted.

It's like millions and millions and millions and millions of parameters all interacting with each other to say OCD comes next and I think that actual OCD probably works a lot like that, or can be worked with a lot like that. Let's just say that. And the reason that we haven't done that is because in science we prioritize explanatory power over predictive power a lot because in order to get. If your paper is accepted by a journal, you have to have a theory. And deep learning doesn't have theories. It just says, we know it works and so I don't know what my stump speech is, basically we should just throw out explanations and a lot of these cases and build predictive models with large data sets, instead of throwing 16 undergrads into a brain scanner and being like, I think of 15 minutes of meditation, slightly affects OCD on average in these 15 undergrads. We should just gather tons and tons and tons of both contextual data and biological data and chat logs and just throw it into a deep learning model to predict. When you're going to get OCD or what interventions might work or even if we don't have a theory, I think science is generally blind to that idea.

Awais Aftab

That's a great question and their suggestion and to my understanding is that researchers have been trying that kind of thing in psychiatry and psychopathology for a while. And so for example, we have had kind of people look at risk of suicide, for example, in large data sets and trying to predict, what kind of factors lead to suicide and to what kind of accuracy. We can predict the risk of suicide over a certain timeframe, and there were publications that reported really, really high accuracy or really high predictive power 90 percent or more in some samples what has happened so far is that. That accuracy hasn't translated very well outside the samples on which the program was trained. So a program might do very well in a large data set, but then you take a wildly different data set and then sort of like it, the kind of predictive power goes down. Now, that may change in the future, as the training gets better, but that's what happens so far, is that you get exceptionally good. The algorithm predicts what happens in one group, but then it fails outside. And so they have tried that with things like disease progression. If you take people at risk of psychosis, can you predict which one would transition to psychosis? They have developed bipolar disorder. If you take people with depression, can you predict who will go on many episodes? So I think that's where I have seen most, kind of machine learning, deep learning kind of stuff being used. Other stuff where this is kind of happening is in understanding patterns of brain circuit activation or patterns of kind of neuro imaging finding. So there were, for example, a series of papers last year that looked at brain circuit activation patterns in depression, anxiety, and identified various subtypes that correlated with certain clinical features, etc. So, that's another kind of situation where people have used, but I think we're still waiting for this kind of methodology to deliver really kind of results that are really actionable or that work well across many, many contexts.

Dan Shipper

Yeah, I think my response to that's a really important concern. My response to that is the same thing was true of earlier versions of text prediction or image image generation and the thing that worked was more data. More parameters, more compute and so I'm not familiar with all of the studies that have done this, but my guess would be that one, what counts as a large dataset in like in that world is actually comparatively not large. Two machine learning researchers who are dealing with terabytes of data and that's even that is probably pretty small. So one compiling the task becomes how do we get an actually gigantic data set? And I think a lot of the big tech companies have these data sets. If they wanted to donate them to science, I think they should and the second thing is, I think, a lot of these studies use more simplistic underpowered statistical models that are more understandable but end up overfitting and aren't able to represent the complex, non-linear interactions that end up actually predicting things like suicide or depression or whatever.

Awais Aftab

Yeah. I think that you're probably right. I think we're still early in this space and that there's so much innovation happening in the neuro learning space. And I think it probably takes some time before these kinds of methods start trickling into the clinical research space. So we probably haven't optimized what can be achieved using that. I agree with that, so I think there's reason to be optimistic and there's reason not to give up on that, but rather to continue exploring these methods.

One thing I'll say is that I think there are things we can practically start doing and sort of start exploring even now. So, for example, one area where AI is kind of getting some practical application in medicine is in note writing, where there are now softwares that have been developed that kind of listen in on the clinical encounter or the interview and generate and kind of a template of a medical note based on what the patient and the doctor discussed, right?

So that's what because it's a relatively the clinical encounter is relatively formulaic and follows a certain template, and I think it could have a lot of utility in clinical interview as well. So as you probably recognize from your clinical experience the average clinician is not super skilled at picking up the nuances of the presentation. But you could easily develop an AI version of a clinical interview that exceeds the average clinician. Someone could have a clinical interview that is facilitated by a large language model and the language is going to have the resources and the model is going to have the time and the resources to go into the nitty gritty of the symptoms and inquire about clarifying what you're experiencing than a rushed clinician who just has 10 minutes to talk to you in an appointment. So I think that's where I think we don't even have to wait for new scientific discoveries to talk about clinical application. If someone develops a good clinical interview AI thing it would be usable straight away.

Dan Shipper

I agree. I mean, a.) there are definitely a lot of people who are working on stuff like that, but b.) think like Chat is already sort of that to be honest and it is kind of this interesting thing where, I mean, I'm go to therapy every week and I'm a big fan of therapy and I have a real human therapist and a real human psychiatrist. So, but and I think the dream is obviously for everyone to be able to have that and everyone to be able to have a skilled clinician, but the reality of how expensive is it do that means that if you want to do that the clinician has to probably be undertrained, understaffed have 10 minutes to talk to you have a checklist and is going to get things wrong more.

(00:40:00)

And I think while ChatGPT is not being billed as a therapist, I would bet you if you look at the way people are using it. A lot of them are using it for things that are sort of therapy-like, and that 's actually probably a good thing because it basically democratizes access to the most basic level of mental and emotional support means that some people won't develop problems that might have otherwise developed them. But it also becomes this sort of funnel so that by the time that by the time you get to a therapist, maybe it's told you, hey, here are some things you should talk to your therapist about, or whatever that help the human clinician make progress more quickly.

Awais Aftab

Yeah, I agree. I think that many of my colleagues, especially in the psychotherapy world, are kind of wary of these developments and they're looking with suspicion but I am more optimistic in my orientation about these things, and I generally see this as a positive development. I think it's good and I think there are problems that are more amenable to this kind of self-directed therapy through ChatGPT, etc. And then there are other more entrenched problems that might require a relationship with a human, but to the extent that there are problems that can be addressed more in a somewhat satisfactory manner by AI, then why not utilize that? And I think a lot of people are drawn to the promise of that. And they have more control and they have to I think a lot of times clinicians, they have all of the quirks of humanity. They can be arrogant, dismissive, they can be rushed vs. ChatGPT is patient. It's all always there.

Dan Shipper

It's nonjudgmental. I think a lot of people don't want to say that, right?

Awais Aftab

No, it's not just not judgmental, right? So you can use it in ways that you can manipulate in ways that you cannot manipulate a human clinician.

Dan Shipper

I'm curious if you've used it at all for this kind of thing. because for me I don't know, I've been having these stress dreams the last couple nights and so I just record a voice note of me talking about my dream and then and throwing into ChatGPT and I have a whole log of a bunch of dreams in the last few nights. And it's just talking to me about different, little patterns in my psyche that I think are for real, not necessarily predicting the future kind of way. Just in here's the emotional landscape that you're in right now that might be useful for you to have in mind as you go through your day, which it definitely has been. Or, I often record all my meetings and throw them into Chat and I'm like, I'm having a problem with this person or whatever, can you walk me through like what to do about it vs. maybe I would go to therapy, but that's once a week and it relies on me having to be well, he said this and she said this, and then I said, it's just different, you know?

Awais Aftab

Yeah I haven't used the kind of Chat or Claude or anything in that from that angle I have mostly used it for brainstorming ideas or doing kind of superficial research on some topic that I'm not very familiar with or used it for editing. For example, if I wanted to edit a piece of writing and wanted input on how it could be worded differently or improved. So I've used it for those purposes. I have not, you personally used it for psychological exploration, although this is something I should probably try as well. Well, one thing I guess since we are talking about this stuff, so if we are talking about AI applications in the classification realm, for example, right? So to the extent that the process is going to be guided by human decision making, right? It's going to be about teaching the algorithms to kind of detect the diagnostic categories as clinicians do. But if we wanted to think about new forms of classification, how might an AI kind of training algorithm approach that kind of thing, if we wanted to, if we wanted it to detect class or come up with classification proposals that are different from the ones we already have.

Dan Shipper

I think it's a great question. I think the thing to think about is one is they work on examples. So if you give it a bunch of examples and ask it to. You can give it a preexisting categorization scheme and say, this example is like this or this example is that but you can also just say for example, predict whether or not this person will be helped by sertraline. And it will do its own internal classification of search lane or no search lane that goes across diagnostic categories and that we probably don't, it's super high dimensional. We probably find it very, very hard to understand. We probably could get some understanding of how it does it, but it's doing its own internal sorting so I think the best way to get it to come up with its own categorization is to set it a task that would require it to categorize it in a novel way. And then it will find a categorization that works for that task sometimes by default, that will be an internal one but you can also get it to write out its categorization scheme or write out the reasons for why it does things in the way it does. It takes a little bit more work to do that, but I think it's possible.

Awais Aftab

Okay. Yeah, that's helpful. And one of the interesting things is that sometimes cultures do that because we have different cultural variations and then sometimes different cultures talk about psychological phenomena in ways that are radically different. So we get these kinds of culture-bound syndromes, for example, in the mental health realm. But a while back, I came across this cultural description of this thing called “egoria”, which essentially translates into self-leakage. It was kind of this idea that a person's boundary essentially has been violated in some way. And a person's elements of their psyche are leaking out in certain ways and then this is a way of thinking that transcends, for example, traditional psychiatric classifications. Because it can cross into things like it could be delusional experiences, could be hallucinatory, but could be kind of other form. Even some forms of obsessive compulsive phenomena or there so I think sometimes cross-cultural comparisons of mental health descriptions can really be surprising. And there's, oh wow, this is a really this is a really different take on a familiar psychiatric concept.

Dan Shipper

Yeah, I think that makes sense. The way that I think about that generally is for things like psychiatric diagnosis or classification, it's emergent, so we're talking about something that's super high dimensional. So any classification system is only going to, and I think you agree with this, it's only going to give you a slice or a slice in a particular way, but it's not going to be the slice and it's a lot of musical genres, like what really counts as rock? That might seem obvious, but if you really think about it, there's a lot of stuff there where it's like they're on the border. What are the Beastie Boys? There's some rock influences there, but they're kind of rap. They're like, there's that kind of thing that I think is the same question and you can come up with your own categorization schemes, but the question is what are for what purpose? In order to reduce it down into a dimension that we can understand, you have to understand the purpose for which you're doing the ranking otherwise, the way that language models do this is they just create, they just map things into a high dimensional space. So they put things near each other and unlike things that are unlike things further away, but across many, many, many, many, many dimensions. And they don't have a huge dictionary of each thing or they don't have a full map of each thing. What they do is you give it a thing and then it generates its location in that space. And once you have its location, then you can kind of say, well, it's near this or it's not near this. And that's how you get away with not having a. universal understandable categorization scheme. You just map it in a space that allows for thousands and thousands of different dimensions.

Awais Aftab

Yeah. It's all really fascinating.

Dan Shipper

Yeah anyway this is fantastic. If people are interested in reading more of your work, where can they find you?

(00:50:00)

Awais Aftab

So I think the place where I'm most active these days is my Substack newsletter, Psychiatry at the Margins. So that's where I'm kind of talking about various kinds of controversies in the field and various debates and other developments that are taking place. I'm also present on X or Twitter, on Bluesky. And as you mentioned in the beginning recently there was a volume published by Oxford University Press called Conversations in Critical Psychiatry, which is an edited collection of interviews that I had done for Psychiatric Times. So I encourage people to check that out too, if you're interested in various debates in the field so yeah, so I think Substack and other social media platforms are probably the best.

Dan Shipper

Awesome. Thank you so much. Keep doing what you're doing. It was really great to talk to you.

Awais Aftab

Yeah. Thanks for having me.

Thanks to Scott Nover for editorial support.

Dan Shipper is the cofounder and CEO of Every, where he writes the Chain of Thought column and hosts the podcast AI & I. You can follow him on X at @danshipper and on LinkedIn, and Every on X at @every and on LinkedIn.

We also build AI tools for readers like you. Automate repeat writing with Spiral. Organize files automatically with Sparkle. Deliver yourself from email with Cora.

We also do AI training, adoption, and innovation for companies. Work with us to bring AI into your organization.

Get paid for sharing Every with your friends. Join our referral program.