An international treaty to implement a global compute cap for advanced artificial intelligence

This paper presents an international treaty to reduce risks from the development of advanced artificial intelligence (AI). The main provision of the treaty is a global compute cap: a ban on the development of AI systems above an agreed-upon computational resource threshold. The treaty also proposes the development and testing of emergency response plans, negotiations to establish an international agency to enforce the treaty, the establishment of new communication channels and whistleblower protections, and a commitment to avoid an AI arms race. We hope this treaty serves as a useful template for global leaders as they implement governance regimes to protect civilization from the dangers of advanced artificial intelligence

Development and validation of the illness perceptions questionnaire for youth anxiety and depression (IPQ-Anxiety and IPQ-Depression)

Background: The Revised Illness Perceptions Questionnaire (IPQ-R) is a well-established measure for measuring illness representations with sound psychometric properties. However, one limitation is that it provides a generic measure of illness representations and lacks specificity to individual health conditions, making it difficult to capture the nuances of illness beliefs for different populations. Objective: The aim of this study was to develop reliable and valid versions of the IPQ-R for young people with anxiety and depression to better understand how they perceive and cognitively represent the course, severity, impact, and treatability of their anxiety and depression. Methods: This mixed-methods study consisted of a qualitative study, involving semi-structured interviews (n = 26) followed by think-aloud interviews (n = 13), and a quantitative study (n = 349), resulting in the development of the IPQ-Anxiety (IPQ-A) and IPQ-Depression (IPQ-D). Item development is reported, along with the psychometric properties of the measures. Concurrent validity was assessed by correlating the IPQ-A and IPQ-D with the Brief Illness Perceptions Questionnaire (B-IPQ) across equivalent dimensions. Results: Results suggest that the IPQ-A, IPQ-D, B-IPQ-A and B-IPQ-D are valid and reliable tools for measuring mental illness representations. The measures show acceptable model fit, high factor loadings, and good to excellent internal consistency, test – retest reliability across subscales and concurrent validity with mental health measures. Conclusions: The development of these measures represents an important step in the field of youth mental health by providing the opportunity for reliable assessment of young people’s conceptualisations of their anxiety and depression. Better understanding of young people’s illness beliefs has the potential to open a range of intervention possibilities by prioritising illness perceptions over the supposed objective condition severity and trajectory

Development and validation of the illness perceptions questionnaire for youth anxiety and depression (IPQ-Anxiety and IPQ-Depression)

Background: The Revised Illness Perceptions Questionnaire (IPQ-R) is a well-established measure for measuring illness representations with sound psychometric properties. However, one limitation is that it provides a generic measure of illness representations and lacks specificity to individual health conditions, making it difficult to capture the nuances of illness beliefs for different populations. Objective: The aim of this study was to develop reliable and valid versions of the IPQ-R for young people with anxiety and depression to better understand how they perceive and cognitively represent the course, severity, impact, and treatability of their anxiety and depression. Methods: This mixed-methods study consisted of a qualitative study, involving semi-structured interviews (n = 26) followed by think-aloud interviews (n = 13), and a quantitative study (n = 349), resulting in the development of the IPQ-Anxiety (IPQ-A) and IPQDepression (IPQ-D). Item development is reported, along with the psychometric properties of the measures. Concurrent validity was assessed by correlating the IPQ-A and IPQ-D with the Brief Illness Perceptions Questionnaire (B-IPQ) across equivalent dimensions. Results: Results suggest that the IPQ-A, IPQ-D, B-IPQ-A and B-IPQ-D are valid and reliable tools for measuring mental illness representations. The measures show acceptable model fit, high factor loadings, and good to excellent internal consistency, test – retest reliability across subscales and concurrent validity with mental health measures. Conclusions: The development of these measures represents an important step in the field of youth mental health by providing the opportunity for reliable assessment of young people’s conceptualisations of their anxiety and depression. Better understanding of young people’s illness beliefs has the potential to open a range of intervention possibilities by prioritising illness perceptions over the supposed objective condition severity and trajectory

Nonprofessional Peer Support to Improve Mental Health: Randomized Trial of a Scalable Web-Based Peer Counseling Course

Background: Millions of people worldwide are underserved by the mental health care system. Indeed, most mental health problems go untreated, often because of resource constraints (eg, limited provider availability and cost) or lack of interest or faith in professional help. Furthermore, subclinical symptoms and chronic stress in the absence of a mental illness diagnosis often go unaddressed, despite their substantial health impact. Innovative and scalable treatment delivery methods are needed to supplement traditional therapies to fill these gaps in the mental health care system. Objective: This study aims to investigate whether a self-guided web-based course can teach pairs of nonprofessional peers to deliver psychological support to each other. Methods: In this experimental study, a community sample of 30 dyads (60 participants, mostly friends), many of whom presented with mild to moderate psychological distress, were recruited to complete a web-based counseling skills course. Dyads were randomized to either immediate or delayed access to training. Before and after training, dyads were recorded taking turns discussing stressors. Participants’ skills in the helper role were assessed before and after taking the course: the first author and a team of trained research assistants coded recordings for the presence of specific counseling behaviors. When in the client role, participants rated the session on helpfulness in resolving their stressors and supportiveness of their peers. We hypothesized that participants would increase the use of skills taught by the course and decrease the use of skills discouraged by the course, would increase their overall adherence to the guidelines taught in the course, and would perceive posttraining counseling sessions as more helpful and their peers as more supportive. Results: The course had large effects on most helper-role speech behaviors: helpers decreased total speaking time, used more restatements, made fewer efforts to influence the speaker, and decreased self-focused and off-topic utterances (ds=0.8-1.6). When rating the portion of the session in which they served as clients, participants indicated that they made more progress in addressing their stressors during posttraining counseling sessions compared with pretraining sessions (d=1.1), but they did not report substantive changes in feelings of closeness and supportiveness of their peers (d=0.3). Conclusions: The results provide proof of concept that nonprofessionals can learn basic counseling skills from a scalable web-based course. The course serves as a promising model for the development of web-based counseling skills training, which could provide accessible mental health support to some of those underserved by traditional psychotherapy

Taking control: Policies to address extinction risks from advanced AI

This paper provides policy recommendations to reduce extinction risks from advanced artificial intelligence (AI). First, we briefly provide background information about extinction risks from AI. Second, we argue that voluntary commitments from AI companies would be an inappropriate and insufficient response. Third, we describe three policy proposals that would meaningfully address the threats from advanced AI: (1) establishing a Multinational AGI Consortium to enable democratic oversight of advanced AI (MAGIC), (2) implementing a global cap on the amount of computing power used to train an AI system (global compute cap), and (3) requiring affirmative safety evaluations to ensure that risks are kept below acceptable levels (gating critical experiments). MAGIC would be a secure, safety-focused, internationally-governed institution responsible for reducing risks from advanced AI and performing research to safely harness the benefits of AI. MAGIC would also maintain emergency response infrastructure (kill switch) to swiftly halt AI development or withdraw model deployment in the event of an AI-related emergency. The global compute cap would end the corporate race toward dangerous AI systems while enabling the vast majority of AI innovation to continue unimpeded. Gating critical experiments would ensure that companies developing powerful AI systems are required to present affirmative evidence that these models keep extinction risks below an acceptable threshold. After describing these recommendations, we propose intermediate steps that the international community could take to implement these proposals and lay the groundwork for international coordination around advanced AI

Stigma toward individuals with mental illness among Indian adolescents: Findings from three secondary schools and a cross-cultural comparison

Despite the importance of understanding public attitudes toward mental illnesses, few studies have examined the views of young people or individuals in non-western settings. We aimed to assess the prevalence of stigma toward individuals with mental illness among youths in India, examine factors associated with stigma, and compare stigma cross-culturally with a sample of American youths. Our sample consisted of 945 Indian secondary school students (49.7% female, Mean age=14.21) from three high schools in Maharashtra, India. Participants completed a social distance scale to assess stigma, as well as measures of depressive symptoms and anxiety symptoms. Stigma toward individuals with mental illness was commonly reported: only 42% of students reported that they were willing to talk with someone with a mental illness, and 41% were willing to be friends with someone with a mental illness. Gender and age were significantly associated with stigma, with males and younger students reporting greater stigma. Participants’ depressive symptoms and anxiety symptoms were not associated with stigma. Furthermore, compared to American adolescents from a different sample who completed the same stigma measure, Indian adolescents reported significantly more stigma (d = 0.55). Overall, this study provides one of the first direct cross-cultural comparisons of stigma among youths and highlights the need for greater awareness about mental illnesses among Indian adolescents. These findings raise concern for the potential consequences of psychiatric labels for youths in non-western settings. Strategies and approaches to combat the harmful effects of stigma are discussed

Race and socioeconomic status as predictors of willingness to use internet-based treatments or face-to-face psychotherapy: A nationally representative study

Background: There is an ongoing debate about whether digital mental health interventions (DMHIs) can reduce racial and socioeconomic inequities in access to mental health care. One key factor in this debate involves the extent to which racial and ethnic minoritized and socioeconomically disadvantaged individuals are willing to use, and pay for, DMHIs. Objective: We examined racial and ethnic as well as socioeconomic differences in participants’ willingness to pay (WTP) for DMHIs vs. one-on-one therapy (1:1 therapy). Methods: We conducted a national survey of people in the United States (N = 423, women: n = 204, age: M = 45.15, SD = 16.19, Non-Hispanic White: n = 293) via Prolific. After reading descriptions of DMHIs and 1:1 therapy, participants rated their willingness to use each treatment for 1) free, 2) for a small fee, 3) as a maximum dollar amount, and 4) as a percentage of their total monthly income. At the end of the study there was a decision task to potentially receive more information about DMHIs and 1:1 therapy. Results: Race and ethnicity were associated with willingness to pay higher amounts of one’s income, as a percent or the dollars, and was also associated with information-seeking for DMHIs in the behavioral task. By and large, race and ethnicity was not associated with willingness to try 1:1 therapy. Greater educational attainment was associated to willingness to try DMHIs for free, the decision to learn more about DMHIs, and willingness to pay for 1:1 therapy. Income was inconsistently associated to willingness to try DMHIs and 1:1 therapy. Conclusions: If they are available for free or at very low costs, DMHIs may reduce inequities by expanding access to mental healthcare for racial and ethnic minoritized individuals and economically disadvantaged groups

Not all depressive symptoms matter equally: Ratings of the relative importance of nine DSM symptoms in a sample of Indian adolescents

Background: There is widespread debate about the extent to which western diagnostic criteria for depression are appropriate cross-culturally. A key aspect of this debate involves the extent to which individual symptoms are considered important, impairing, and concerning by individuals in low- and middle-income countries. Here, we describe a novel method to understand the degree to which symptoms of depression are most important to individuals, and we illustrate its application in a non-western sample. Methods: We surveyed 1,237 Indian adolescents (47.8% female, Mage= 14.11). Adolescents received the Patient Health Questionnaire-9, a measure of nine DSM-derived depressive symptoms. For each symptom, participants answered three questions designed to assess the degree to which they perceive the symptom as distressing and impairing. The three scores were averaged to form a Subjective Importance Rating (SIR) for each symptom. Results: Anhedonia received the highest SIR, followed by Sad Mood, Suicidal Ideation, and Feeling like a Failure; Psychomotor Problems received the lowest SIRs. Females reported greater SIRs than males, and older students reported greater SIRs than younger students. There was a non-linear relationship between participants' own depressive symptoms and SIRs. Limitations: Participants were recruited from the general population; findings may not generalize to patients or individuals in other countries. Conclusion: Not all symptoms of depression were viewed as equally important. We discuss how the SIR approach can help global mental health researchers identify specific symptoms that are considered most concerning, evaluate the cross-cultural relevance of western diagnostic criteria, and inform the validation of measurement tools

A Review of Popular Smartphone Apps for Depression and Anxiety: Assessing the Inclusion of Evidence-Based Content

Smartphone applications for the treatment of depression and anxiety have acquired millions of users, yet little is known about whether they include evidence-based therapeutic content. We examined the extent to which popular mental health applications (MH apps) for depression and anxiety contain treatment elements found in empirically supported psychotherapy protocols (i.e., “common elements”). Of the 27 MH apps reviewed, 23 included at least one common element, with a median of three elements. Psychoeducation (in 52% of apps), relaxation (44%), meditation (41%), mindfulness (37%), and assessment (37%) were the most frequent elements, whereas several elements (e.g., problem solving) were not found in any apps. We also identified gaps between app content and empirically supported treatments. Cognitive restructuring was more common in depression protocols than in depression apps (75% of protocols vs. 31% of apps), as was problem solving (34% vs. 0%). For anxiety, exposure (85%, 12%), cognitive restructuring (60%, 12%), and problem solving (25%, 0%) were more common in protocols than apps. Overall, our findings highlight empirically supported treatment elements that are poorly represented in current MH apps. The absence of several core treatment elements underscores the need for future research, including randomized trials testing the effectiveness of popular MH apps