The recent rise in relevance and diffusion of Artificial Intelligence (AI)-based systems and the increasing number and power of applications of AI methods invites a profound reflection on the impact of these innovative systems on scientific research and society at large. The Universal Scientific Education and Research Network (USERN), an organization that promotes initiatives to support interdisciplinary science and education across borders and actively works to improve science policy, collects here the vision of its Advisory Board members, together with a selection of AI experts, to summarize how we see developments in this exciting technology impacting science and society in the foreseeable future. In this review, we first attempt to establish clear definitions of intelligence and consciousness, then provide an overview of AI's state of the art and its applications. A discussion of the implications, opportunities, and liabilities of the diffusion of AI for research in a few representative fields of science follows this. Finally, we address the potential risks of AI to modern society, suggest strategies for mitigating those risks, and present our conclusions and recommendations.

Objective: We examined whether the treatment effects from a previous RCT of Internet-delivered Emotional Awareness and Expression Therapy (I-EAET) for somatic symptom disorder were maintained 12 months after treatment.

Method: 12-month assessments of self-reported somatic symptoms, pain severity, and several secondary outcomes were compared with baseline and post-treatment levels within the I-EAET condition only, given that the waitlist control condition had already received treatment. Twenty-eight out of the original 37 participants (76%) in the I-EAET condition provided follow-up data.

Results: The beneficial effects of I-EAET on somatic symptoms observed at post-treatment were maintained at the 12-month follow-up (d = -0.22, 95% CI: -0.72 to 0.28), as well as for pain intensity (d = -0.02, 95% CI: -0.52 to 0.48). From pre-treatment to 12-month follow-up, there was a medium effect on somatic symptoms (d = 0.74, 95% CI 0.23 to 1.24), and a small, non-significant effect for pain intensity (d = 0.43, 95% CI -0.06 to 0.93). Response rates (at least 50% symptom reduction) at 12-month follow-up were 25% for somatic symptoms, and 12% for pain intensity.

Conclusion: I-EAET seems to have positive long-term effects for somatic symptom disorder. Larger studies with controls and comparisons to other treatments are needed.

Objectives: Interpersonal problems are a fundamental feature of depression, but study-level meta-analyses of their association with treatment outcome have been limited by heterogeneity in primary studies' analyses and reported results. We conducted a pre-registered individual participant data meta-analysis (IPD-MA) to examine this relationship for adult depression. This meta-analytic strategy can reduce variability by standardizing data analysis across primary studies. Methods: We included studies examining the efficacy of five treatments for adult depression and assessing interpersonal problems at baseline. One-stage IPD-MA was conducted with three-level mixed models to determine whether baseline overall interpersonal distress, agency, and communion predicted depressive symptom level at post-treatment, 12-month, and 24-month follow-up. The moderating effect of treatment type was also investigated. Results: Ten studies (including n = 1282 participants) met inclusion criteria. Only overall interpersonal distress was negatively related with outcomes at post-treatment (γ = 0.11, CI95[0.06, 0.16], r = 0.11), 12-month follow-up (γ = 0.17, CI95[0.08, 0.25], r = 0.17), and 24-month follow-up (γ = 0.16, CI95[0.05, 0.26], r = 0.16), indicative of smaller effect sizes. The agency and communion dimensions were not significantly related to outcome. Treatment type did not significantly moderate interpersonal distress-outcome associations. Discussion: Results show a small association between patient baseline overall interpersonal distress and subsequent depression treatment outcome in brief treatments for depression. Further studies might require to account for therapist effects.

There is a growing interest in clinical interventions targeting emotion regulation difficulties across mental health conditions. Experiential dynamic therapies (EDTs) are transdiagnostic, affect-focused, short-term psychodynamic therapy models that emphasize in-session emotional processing. This review provides a 10-year update on the efficacy of EDTs for mood, anxiety, personality and somatic symptom disorders in adults and children/adolescents. A comprehensive search identified 57 randomized controlled trials (n = 4330) conducted in Western (k = 38; n = 3178) and non-Western countries (k = 19; n = 1152) between 1978 and 2024. Random-effects meta-analyses on primary outcomes indicated large, significant effects for EDTs compared to inactive controls at post-treatment (Hedge's g = −0.96; k = 41) and follow-up (g = −1.11; k = 20). Compared to active controls, effects were small and non-significant post-treatment (g = −0.17; k = 27) but became significant at follow-up (g = −0.40; k = 19), suggesting a potential modest long-term advantage of EDTs. Despite substantial heterogeneity (I2 > 75%), results remained robust in sensitivity analyses. Moderator analyses revealed few significant findings, indicating relative consistency across diagnostic groups, treatment formats and active comparators. Non-Western and lower quality studies reported larger effects compared to inactive, but not active, controls. While cautious interpretation is warranted due to unexplained heterogeneity, findings support EDTs as efficacious transdiagnostic interventions for emotional disorders, with sustained benefits over time. Future research should prioritize large-scale, methodologically rigorous trials that explore mechanisms of change, optimize treatment delivery and identify moderators of long-term outcomes.

Background: Alcohol-related issues are widespread worldwide and are fairly substantial. Numerous studies have identified and clarified the effects and prevalence of alcohol use across different contexts. However, when it comes to the prevalence of alcohol in psychiatry and its impact on treatment outcomes compared to other patient groups, studies are relatively scarce, and results often vary, sometimes with different outcomes. This study focuses on investigating the effectiveness of psychological treatment in psychiatric clinics for outpatients, considering those with and without hazardous alcohol use under naturalistic conditions.

Methods: Patients were recruited between 2012 and 2016 from psychiatric clinics in Sormland, Sweden, as part of the regular services. Patients completed symptom assessment instruments regarding depression, anxiety, quality-of-life, and alcohol consumption at the beginning of their psychological treatment, upon completion, and during a follow-up 1 year after completion. Completion of questionnaires was ongoing for some patients until 2021. A total of 324 patients were included in the study, distributed among 59 participating therapists.

Results: Among all patients in the study, 30.2% showed hazardous alcohol use at the start of their psychological treatment, with a higher proportion being men. There was a significant reduction in the proportion of patients with hazardous use and a notable decrease in the mean audit score upon completion of psychological treatment. At follow-up, there was no significant change compared to completion. There were 31.2% of the patients who achieved recovery or improvement in the audit score upon completion of treatment. Patients with hazardous alcohol use consistently scored higher mean values on the symptom assessment instruments and lower on the quality-of-life instrument at the beginning. More individuals with hazardous alcohol use typically achieved better results across all outcome instruments at both at completion and follow-up.

Conclusion: Patients with hazardous alcohol use demonstrate significant improvements in their alcohol consumption through standard psychological treatment in psychiatry, despite the treatment not specifically focusing on alcohol consumption. The progress/improvement appears to be largely maintained at follow-up. Moreover, patients with hazardous alcohol use tend to show greater progress across all outcome instruments. No significant gender differences were detected in this context.

This paper presents an interdisciplinary framework, Machine Psychology, which integrates principles from operant learning psychology with a particular Artificial Intelligence model, the Non-Axiomatic Reasoning System (NARS), to advance Artificial General Intelligence (AGI) research. Central to this framework is the assumption that adaptation is fundamental to both biological and artificial intelligence, and can be understood using operant conditioning principles. The study evaluates this approach through three operant learning tasks using OpenNARS for Applications (ONA): simple discrimination, changing contingencies, and conditional discrimination tasks. In the simple discrimination task, NARS demonstrated rapid learning, achieving 100% correct responses during training and testing phases. The changing contingencies task illustrated NARS’s adaptability, as it successfully adjusted its behavior when task conditions were reversed. In the conditional discrimination task, NARS managed complex learning scenarios, achieving high accuracy by forming and utilizing complex hypotheses based on conditional cues. These results validate the use of operant conditioning as a framework for developing adaptive AGI systems. NARS’s ability to function under conditions of insufficient knowledge and resources, combined with its sensorimotor reasoning capabilities, positions it as a robust model for AGI. The Machine Psychology framework, by implementing aspects of natural intelligence such as continuous learning and goal-driven behavior, provides a scalable and flexible approach for real-world applications. Future research should explore using enhanced NARS systems, more advanced tasks and applying this framework to diverse, complex tasks to further advance the development of human-level AI.

We present the integration of a Non-Axiomatic Reasoning System (NARS) with mobile robots for planning and decision making. NARS enables robots to effectively handle uncertainty in real-time with complete sensor and actuator integration, thereby ensuring adaptability to evolving scenarios. We discuss essential parts of the logic, the architecture and working principles of NARS, and the integration of NARS as a ROS node. A case study is provided demonstrating the system's proficiency to carry out a garbage collection task in an open-air environment by operating a mobile robot with manipulator arm, and we demonstrate its ability to learn about the place-dependent accumulation of garbage items. Case study also reveals that our approach performs more effectively on the overall task than the Belief-Desire-Intention model we compared with.

Most research showing results of psychotherapy come from efficacy studies or effectiveness studies from university counselling centers, or therapy clinics at universities. This study is an effectiveness study that aims to investigate the results of psychological treatment in psychiatric clinics for outpatients under naturalistic conditions. The study contributes unique insights regarding the outcomes of psychological treatment for patients with severe psychiatric problems in the complex real environment where many influencing variables exist. Patients were recruited from 2012 to 2016 from psychiatric clinics in Sormland, Sweden in the regular service. They received psychological treatment lasting between 1 and 50 months. The entire period of assessment took place between 2012 and 2021. A total of 325 patients received treatment from 59 participating therapists. Patients completed symptom assessment instruments regarding anxiety, depression, and quality of life at the start of therapy, upon the completion of therapy and, at follow-up one year after completion. Analyses indicated a significant improvement in all outcome instruments between start and completion of therapy. The improvement was largely maintained until follow-up. The effect sizes were moderate. Between 49.1% and 62.9% of patients “improved” or “recovered” as measured by the symptom assessment instruments at completion of therapy. The proportion of improved/recovered on the quality-of-life instrument was 37.4%. In a naturalistic cohort with comparatively severe psychiatric problems, substantial and stable improvements were achieved. The outcomes were respectable considering the population. The study provides external validity to efficacy studies on how psychological treatment works in a real-life context.

Background: Driving requires a series of cognitive abilities, many of which are affected by age and medical conditions. The psychosocial importance of continued driving ushers the need for valid measurements in fitness-to-drive assessments. A driving simulator test could prove useful in these assessments, having greater face validity than other off-road tests and being more cost-effective and safer than ordinary on-road testing. The aim of this study was to validate a driving simulator test for assessment of cognitive ability in fitness-to-drive assessments.

Methods: The study included 67 healthy participants. Internal consistency of the simulator subtests was estimated. A correlation analysis between results on the simulator and the cognitive tests Trail Making Test (TMT) A and B and the Useful field of View test (UFOV) and multiple regression analysis were conducted. Finally, a comparison of results between age groups (>65 years) and (<65 years) was done.

Results: Results showed good internal consistency. Significant and moderate correlations were found for all reaction time in the simulator’s subtests and UFOV 3, and all but two with TMT A. Lane positioning in the simulator showed significant and low to moderate correlations with UFOV 3 in all subtests. Reaction time and Double reaction time on subtest 3 were significantly correlated with UFOV 2 and UFOV 3 and TMT A, respectively. Test on Centerline (position) in subtest 3 as dependent variable was significantly correlated with UFOV 3. Significant means differences and large effect sizes between the age groups were found for all reaction time and lane positioning tests.

Conclusion: The findings of concurrent validity, especially with TMT A and UFOV 3 and its sensitivity for age-related differences, indicate potential for the simulator to be used as a complement in fitness-to-drive assessments. However, a clinical study is necessary to further examine its usefulness for patients with cognitive deficits.

Background: Short-term psychodynamic psychotherapy (STPP) is frequently used to treat depression, but it is unclear which patients might benefit specifically. Individual participant data (IPD) meta-analyses can provide more precise effect estimates than conventional meta-analyses and identify patient-level moderators. This IPD meta-analysis examined the efficacy and moderators of STPP for depression compared to control conditions.

Methods: PubMed, PsycInfo, Embase, and Cochrane Library were searched September 1st, 2022, to identify randomized trials comparing STPP to control conditions for adults with depression. IPD were requested and analyzed using mixed-effects models.

Results: IPD were obtained from 11 of the 13 (84.6%) studies identified (n = 771/837, 92.1%; mean age = 40.8, SD = 13.3; 79.3% female). STPP resulted in significantly lower depressive symptom levels than control conditions at post-treatment (d = −0.62, 95%CI [−0.76, −0.47], p < .001). At post-treatment, STPP was more efficacious for participants with longer rather than shorter current depressive episode durations.

Conclusions: These results support the evidence base of STPP for depression and indicate episode duration as an effect modifier. This moderator finding, however, is observational and requires prospective validation in future large-scale trials.