Training large multimodal language models with ethical values

The rapid expansion of artificial intelligence (AI) in modern society, exemplified by systems like ChatGPT and Stable Diffusion, has given rise to significant ethical considerations. These systems, increasingly prevalent in diverse sectors such as mental health treatment, as in Koko, and art creation, necessitate a careful examination of their alignment with human values. This thesis addresses the pressing need for ethical evaluation of multimodal AI systems - those capable of processing and responding to both text and image inputs. Our research is twofold: initially, we focus on developing a multimodal ethical database through interactive human feedback. Participants assess various examples, determining their ethical appropriateness. This process culminates in a dataset that serves as a foundation for the subsequent phase - designing and testing algorithms capable of autonomously evaluating the morality of AI responses. We explore the effectiveness of two models in this context: a RoBERTa-large classifier and a multilayer perceptron classifier. Furthermore, this thesis highlights significant limitations in the existing multimodal AI systems studied. We propose alternative models, offering a comparative analysis mainly in terms of performance. This comprehensive study not only contributes to the field of AI alignment but also proposes methodologies for enhancing the moral framework within which these influential technologies operate.L'expansion rapide de l'intelligence artificielle (IA) dans la société moderne, illustrée par des systèmes tels que ChatGPT et Stable Diffusion, a suscité d'importantes considérations éthiques. Ces systèmes, de plus en plus présents dans divers secteurs tels que le traitement de la santé mentale, avec Koko, et la création artistique, nécessitent un examen attentif de leur alignement avec les valeurs humaines. Ce mémoire aborde le besoin pressant d'une évaluation éthique des systèmes d'IA multimodaux - capables de traiter et de répondre à la fois aux entrées textuelles et visuelles. Notre recherche est double : initialement, nous nous concentrons sur le développement d'une base de données éthiques multimodales par le biais de retours interactifs d'utilisateurs. Les participants évaluent divers exemples pour déterminer leur éthique. Ce processus aboutit à un ensemble de données qui sert de fondement à la phase suivante - la conception et le test d'algorithmes capables d'évaluer de manière autonome la moralité des réponses de l'IA. Nous explorons l'efficacité de deux modèles dans ce contexte : un classificateur RoBERTa-large et un perceptron multicouche. De plus, ce mémoire met en évidence des limitations significatives dans les systèmes d'IA multimodaux existants étudiés. Nous proposons des modèles alternatifs, offrant une analyse comparative en termes de performance. Cette étude complète contribue non seulement au domaine de l'alignement de l'IA, mais propose également des méthodologies pour améliorer le cadre moral dans lequel ces technologies influentes opèrent

Le Produit d'Epargne Retraite Populaire (PERP) : caractéristiques des détenteurs et projection des niveaux de rentes

Un produit d'épargne retraite universel a été lancé en France en 2003, le Plan d'Epargne Retraite Populaire (PERP), dont l'objectif est de permettre aux ménages de compléter leur futur retraite. A l'aide de données issues d'une large enquête réalisée par TNS SOFRES en 2007 dont un volet porte sur les ménages détenteurs d'un PERP, nous montrons que ce produit s'est diffusé dans l'ensemble des couches sociales et touche en proportion aussi bien les cadres et professions libérales que les ouvriers ou les employés. L'âge des détenteurs suit approximativement une courbe en U avec une participation relativement plus importante des 25-34 ans et des 50-54 ans. Nous appliquons dans un second temps la méthode des résidus simulés pour obtenir des distributions de capital et de versements à partir des données en tranche fournies par l'enquête. Cela nous permet d'estimer le montant accumulé par les ménages de l'échantillon au moment de la liquidation de leur plan et d'évaluer ainsi quel supplément de ressources ces derniers sont susceptibles d'obtenir pendant la retraite en proportion du dernier revenu d'activité. Les résultats des simulations indiquent que la plupart des souscripteurs bénéficieront d'un revenu d'appoint inférieur à 1% de leur dernier revenu d'activité.épargne retraite

The Madden Julian Oscillation and its relationship with rainfall in Queensland

The Madden Julian Oscillation is a large-scale atmospheric phenomenon that is generated above the tropical Indian Ocean. It is associated with large convective systems that propagate eastward across the Pacific Ocean. Since it is an atmospheric event limited to the equatorial domain, it was believed that it has little effect on non-tropical regions. However, recent research found correlations between the positioning of the active Madden Julian Oscillation phase along the Equator and rainfall events northeast Australia. The correlations were significant throughout Queensland. The phenomenon is subject to a study by climate scientists at four Australian institutions. It aims to develop a simple predictive tool of rainfall events that are linked with the active phase of the Madden Julian Oscillation and that is applicable throughout Queensland and possible beyond. The outcome of this research is to be linked with agricultural production systems model in order to help Queensland farmers to better time planting and harvesting, as well as scheduling of contractors whose operations might be delayed by rain

Towards ethical multimodal systems

Generative AI systems (ChatGPT, DALL-E, etc) are expanding into multiple areas of our lives, from art Rombach et al. [2021] to mental health Rob Morris and Kareem Kouddous [2022]; their rapidly growing societal impact opens new opportunities, but also raises ethical concerns. The emerging field of AI alignment aims to make AI systems reflect human values. This paper focuses on evaluating the ethics of multimodal AI systems involving both text and images - a relatively under-explored area, as most alignment work is currently focused on language models. We first create a multimodal ethical database from human feedback on ethicality. Then, using this database, we develop algorithms, including a RoBERTa-large classifier and a multilayer perceptron, to automatically assess the ethicality of system responses.Comment: 5 pages, multimodal ethical dataset building, accepted in the NeurIPS 2023 MP2 worksho

A recruiting failure turned success

<p>Abstract</p> <p>Background</p> <p>This paper describes an attempt that was made to recruit child-bearing women into a nutrition-based research study and the knowledge that was gained when this approach was unsuccessful. The Assessment Before Children Develop Obesity Study was a cross-sectional survey which planned to follow-up women and children who had previously been, or were currently enrolled in the Mathematical Model of Pregnancy Study.</p> <p>Methods</p> <p>Ethics approval was sought and obtained over an eight month period. After just six weeks it was obvious that our research objectives were not achievable because of an inadequate response rate (10%). This led to a review of the recruiting methodology as well as all written materials provided to potential participants. Advice was sought from those with expertise in the design of large public health campaigns and literature was consulted to refine our recruitment strategy.</p> <p>Results</p> <p>In subsequent redevelopment, the Assessment Before Children Develop Obesity Study was merged with the Mathematical Model of Pregnancy Study to become what is now known as the Women and Their Children's Health Study. Consent rates improved from 10% and 35% in the Assessment Before Children Develop Obesity and Mathematical Model of Pregnancy studies respectively, to 61% in the Women and Their Children's Health Study (chi square test, p < 0.001). Successful recruitment for this research continues. The significant improvement in the participation rate is attributed to numerous factors including changes to the study name, recruiting method and information materials.</p> <p>Conclusion</p> <p>By sharing our experience we aim to assist other researcher in avoiding the same pitfalls and offer effective strategies for improving response rates.</p

Comment le sens est-il extrait de l'information visuelle ? Le système visuel exploré des catégories à la conscience

Comment le sens est-il extrait de l'information visuelle ? Cette thèse est focalisée sur la capacité du système visuel d'humains et de singes à extraire et représenter l'information visuelle sur différents niveaux de complexité. Nous avons étudié différent niveaux de représentations visuelles, de la production de représentations visuelles primaires jusqu'à l'élaboration de représentations visuelles conscientes. Ce manuscrit présente six travaux dans lesquels nous avons exploré : (1) les attributs visuels nécessaires pour réaliser la tâche de catégorisation ultra rapide chez l'homme et le singe au moyen de méthodes psychophysiques, (2) la dynamique spatio-temporelle de l'attention visuelle chez l'homme au moyen de méthodes psychophysiques, (3) les corrélats neuronaux des représentations de haut niveau en EEG grâce au développement d'une nouvelle technique appelée SWIFT, (4) les corrélats neuronaux de la conscience visuelle dans la rivalité binoculaire en EEG, (5) la synchronie des signaux cérébraux en fonction de la reconnaissance consciente au moyen d'enregistrements intracrâniens chez des patients épileptiques et (6) les corrélats neuronaux associés à la prise de conscience chez le singe au moyen d'enregistrements intracrâniens. Les résultats de ces travaux nous ont permis d'ébaucher un modèle de la perception visuelle cherchant à dissocier l'attention et la conscience.How does sense emerges in the visual system? In this thesis we will be focused on the visual system of human and non-human primates and their large capacity of extract and represent visual information. We studied several levels of visual representations from those related to the extraction of coarse visual features to the emergence of conscious visual representations. This manuscript presents six works in which we explored: (1) the visual features necessary to perform ultra-rapid visual categorization in monkeys and humans using psychophysics, (2) the spatio-temporal dynamics of visual attention in humans using psychophysics, (3) the neural correlates of high-level visual representations using EEG tanks to the development of an innovative technique called SWIFT, (4) the neural correlates of visual consciousness under binocular rivalry using EEG, (5) the synchrony of brain signals as a function of conscious recognition using intracranial electrodes implanted in epileptic patients and (6) the neural correlates associated with conscious perception in monkeys using intracranial electrodes. The results of these works allowed outlining a tentative model of visual perception aimed to dissociate attention and consciousness

Central Modulation of Neuroinflammation by Neuropeptides and Energy-Sensing Hormones during Obesity

Centralnervoussystem(CNS)sensesenergyhomeostasisbyintegratingbothperipheralandautonomicsignalsandrespondingto thembyneurotransmittersandneuropeptidesrelease.Althoughitispreviouslyconsideredanimmunologicallyprivilegedorgan, we now know that this is not so. Cells belonging to the immune system, such as B and T lymphocytes, can be recruited into the CNS to face damage or infection, in addition to possessing resident immunological cells, called microglia. In this way, positive energybalanceduringobesitypromotesaninflammatorystateintheCNS.Saturatedfattyacidsfromthediethavebeenpointed out as powerful candidates to trigger immune response in peripheral system and in the CNS. However, how central immunity communicatestoperipheralimmuneresponseremainstobeclarified.Recentlytherehasbeenagreatinterestintheneuropeptides, POMC derived peptides, ghrelin, and leptin, due to their capacity to suppress or induce inflammatory responses in the brain, respectively. These may be potential candidates to treat different pathologies associated with autoimmunity and inflammation. In this review, we will discuss the role of lipotoxicity associated with positive energy balance during obesity in proinflammatory responseinmicroglia,BandTlymphocytes,anditsmodulationbyneuropeptides