![\"\"](\"https:\/\/world.edu\/wp-content\/uploads\/2022\/08\/AI-technology-medical.jpeg\")
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Hello Sir.\u00a0Please sit down.\u00a0So\u2026 how have you been since the last time?\u00a0\u00bb<\/p>\n
What if, in a few years, this innocuous sentence was no longer pronounced by a psychiatrist in the flesh but by an AI, an artificial intelligence?\u00a0With the\u00a0recent resurgence of psychiatry in the public debate<\/a>\u00a0,\u00a0in particular due to the health crisis<\/a>\u00a0, the idea of \u200b\u200bproposing mental health monitoring systems integrating AIs has resurfaced.<\/p>\n It is, let’s be honest, far from being new since we find the\u00a0first trace of a chatbot (dialogue program) dedicated to psychiatry, named ELIZA, from 1966<\/a>\u00a0.\u00a0In recent decades, advances in Artificial Intelligence have enabled the rise of\u00a0chatbots<\/a>\u00a0, \u201crobot therapists\u201d or other\u00a0systems for detecting the state of health through the voice<\/a>\u00a0.<\/p>\n Today there are\u00a0more than twenty robot-therapists <\/a>\u00a0validated by scientific studies in psychiatry<\/a>\u00a0.\u00a0Several of these works suggest that patients could\u00a0develop real therapeutic relationships with these technologies<\/a>\u00a0, and even that some of them would even feel more comfortable with a chatbot than with a human psychiatrist.<\/p>\n The ambitions are therefore high\u2026 Especially since, unlike their human counterparts, these digital \u201cprofessionals\u201d would promise objective, replicable and non-judgmental decisions \u2013 and to be available at all times.<\/p>\n The first dialogue software or chatbot is ELIZA, designed in 1966 to simulate a psychotherapist. DR<\/p><\/div>\n It should be noted, however, that while the name \u201crobot therapist\u201d evokes the image of a physical robot, most are text-based, possibly animated videos.\u00a0In addition to this absence of physical presence, important for the majority of patients, many fail to recognize all the difficulties experienced by the people with whom they converse.\u00a0How, then, to provide appropriate responses, such as referral to a dedicated help desk?<\/p>\n The psychiatrist, in his interview with his patient, is able to perceive important signals betraying the existence of suicidal thoughts or domestic violence, which current chatbots can miss.<\/p>\n Why does the psychiatrist still surpass his electronic version?\u00a0When this specialist announces “You have attention deficit disorder”, or “Your daughter has anorexia nervosa”, the process that led him to make these diagnoses depends on his “internal model”: a\u00a0set of mental processes , explicit or implicit, which allow him to make his diagnosis<\/a>\u00a0.<\/p>\n Just as\u00a0engineering is inspired by nature to design efficient systems<\/a>\u00a0, it may be relevant to analyze what is going on in the head of a psychiatrist (the way he designs and uses his internal model) when he makes his diagnosis to then better train the AI \u200b\u200bresponsible for imitating him\u2026 But to what extent are a human \u201cinternal model\u201d and that of a program similar?<\/p>\n This is what we asked ourselves in our\u00a0recent article in the journal Frontiers in Psychiatry<\/em><\/a>\u00a0.<\/p>\n Based on\u00a0previous studies <\/a>\u00a0on diagnostic reasoning in psychiatry<\/a>\u00a0, we have established a comparison between the internal model of the psychiatrist and that of RNs.\u00a0The formulation of a diagnosis goes through three main stages:<\/p>\n \u25cf\u00a0Collecting information and organizing it.\u00a0<\/strong>During his interview with a patient, the psychiatrist assembles a lot of information (from his medical file, his behavior, what is said, etc.), which he then selects according to their relevance.\u00a0This information can then be associated with pre-existing profiles with similar characteristics.<\/p>\n AI systems do the same: based on the data with which they have been trained, they extract from their exchange with the patient characteristics (in English\u00a0features<\/em>\u00a0) that they select and organize according to their importance (\u00a0feature selection<\/em>\u00a0).\u00a0They can then group them into profiles and thus make a diagnosis.<\/p>\n \u25cf\u00a0Building the model.\u00a0<\/strong>During their medical studies, then throughout their career (clinical practice, reading case reports, etc.), psychiatrists formulate diagnoses of which they know the outcome.\u00a0This ongoing training reinforces, in their model, the associations between the decisions they make and their consequences.<\/p>\n Here again, the AI \u200b\u200bmodels are trained in the same way: whether during their initial training or their learning, they constantly reinforce, in their internal model, the relations between the descriptors extracted from their databases and the diagnostic outcome.\u00a0These databases can be very large, even containing more cases than a clinician will see in their career.<\/p>\n \u25cf\u00a0Use of the model.\u00a0<\/strong>At the end of the two previous stages, the internal model of the psychiatrist is ready to be used to take charge of new patients.\u00a0Various external factors can influence how he will do this, such as his salary or his workload \u2013 which find their equivalents in the cost of equipment and the time required to train or use an AI.<\/p>\n As indicated above, it is often tempting to think that the psychiatrist is influenced in his professional practice by a whole set of subjective, fluctuating and uncertain factors: the quality of his training, his emotional state, the morning coffee, etc.\u00a0And that an AI, being a “machine”, would be rid of all these human vagaries… This is a mistake!\u00a0Because AI also includes an important part of subjectivity;\u00a0it is simply less immediately perceptible.<\/p>\n Indeed, all AI was designed by a human engineer.\u00a0Thus, if one wants to compare the thinking processes of the psychiatrist (and therefore the design and use of their internal model) and those of AI, one must consider the influence of the coder who created it.\u00a0This has its own internal model, in this case not to associate clinical data and diagnosis but type of AI and problem to be automated.\u00a0And there too, many technical choices but based on the human come into account (which system, which classification algorithm, etc.)<\/p>\n The internal model of this coder is necessarily influenced by the same factors as that of the psychiatrist: his experience, the quality of his training, his salary, the working time to write his code, his morning coffee, etc.\u00a0All will affect the design parameters of the AI \u200b\u200band therefore, indirectly, on the decision-making of the AI, that is to say on the diagnoses that it will make.<\/p>\n The other subjectivity that influences the internal model of AIs is that associated with the databases on which it is trained.\u00a0These databases are indeed designed, collected and annotated by one or more other people with their own subjectivities \u2013 subjectivity that will play in the choice of the types of data collected, the material involved, the measure chosen to annotate the database. , etc.<\/p>\n While AIs are presented as objective,\u00a0they actually reproduce the biases present in the databases on which they are trained<\/a>\u00a0.<\/p>\n It emerges from these comparisons that AI is not exempt from subjective factors and, for this reason in particular, is not yet ready to replace a \u201creal\u201d psychiatrist.\u00a0The latter has other relational and empathetic qualities to adapt the use of his model to the reality he encounters\u2026 which AI is still struggling to do.<\/p>\n The psychiatrist is thus capable of flexibility in collecting information during his clinical interview, which allows him to access very different temporal information: he can, for example, question the patient about a symptom that occurred weeks before or evolve its exchange in real time according to the answers obtained.\u00a0AIs are currently limited to a pre-established and therefore rigid scheme.<\/p>\n Another strong limitation of RNs is their lack of corporeality, a\u00a0very important factor in psychiatry<\/a>\u00a0.\u00a0Indeed, any clinical situation is based on an encounter between two people \u2013 and this encounter involves speech and non-verbal communication: gestures, position of bodies in space, reading of emotions on the face or recognition of non-verbal social signals. explicit\u2026 In other words, the physical presence of a psychiatrist constitutes an important part of the patient-caregiver relationship, which itself constitutes an important part of the care.<\/p>\n![\"\"](\"https:\/\/world.edu\/wp-content\/uploads\/2022\/08\/Eloiza.jpg\")
Diagnosis and internal model in the psychiatrist<\/strong><\/h4>\n
Man-Machine Comparison<\/strong><\/h4>\n
AI, really neutral and objective?<\/strong><\/h4>\n
The limits of AI in psychiatry<\/strong><\/h4>\n