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  • 1.
    Aler Tubella, Andrea
    et al.
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Coelho Mollo, Dimitri
    Umeå universitet, Humanistiska fakulteten, Institutionen för idé- och samhällsstudier.
    Dahlgren, Adam
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Devinney, Hannah
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Dignum, Virginia
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Ericson, Petter
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Jonsson, Anna
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Kampik, Timotheus
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap. SAP Signavio, Germany.
    Lenaerts, Tom
    Université Libre de Bruxelles, Belgium; University of California, Berkeley, USA.
    Mendez, Julian Alfredo
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    Nieves, Juan Carlos
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för datavetenskap.
    ACROCPoLis: a descriptive framework for making sense of fairness2023Inngår i: FAccT '23: Proceedings of the 2023 ACM conference on fairness, accountability, and transparency, ACM Digital Library, 2023, s. 1014-1025Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Fairness is central to the ethical and responsible development and use of AI systems, with a large number of frameworks and formal notions of algorithmic fairness being available. However, many of the fairness solutions proposed revolve around technical considerations and not the needs of and consequences for the most impacted communities. We therefore want to take the focus away from definitions and allow for the inclusion of societal and relational aspects to represent how the effects of AI systems impact and are experienced by individuals and social groups. In this paper, we do this by means of proposing the ACROCPoLis framework to represent allocation processes with a modeling emphasis on fairness aspects. The framework provides a shared vocabulary in which the factors relevant to fairness assessments for different situations and procedures are made explicit, as well as their interrelationships. This enables us to compare analogous situations, to highlight the differences in dissimilar situations, and to capture differing interpretations of the same situation by different stakeholders.

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  • 2.
    Coelho Mollo, Dimitri
    Umeå universitet, Humanistiska fakulteten, Institutionen för idé- och samhällsstudier.
    A quick overview of scientific representation and modelling: James Nguyen and Roman Frigg: Scientific representation. Cambridge elements in the philosophy of science. Cambridge: Cambridge University Press, 2022, 75 pp2023Inngår i: Metascience, ISSN 0815-0796, Vol. 32, s. 321-324Artikkel, omtale (Annet vitenskapelig)
  • 3. Coelho Mollo, Dimitri
    Against Computational Perspectivalism2021Inngår i: British Journal for the Philosophy of Science, ISSN 0007-0882, E-ISSN 1464-3537, Vol. 72, nr 4, s. 1129-1153Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Computational perspectivalism has been recently proposed as an alternative to mainstream accounts of physical computation, and especially to the teleologically-based mechanistic view. It takes physical computation to be partly dependent on explanatory perspectives and eschews appeal to teleology in helping individuate computational systems. I assess several varieties of computational perspectivalism, showing that they either collapse into existing non-perspectival views or end up with unsatisfactory or implausible accounts of physical computation. Computational perspectivalism fails, therefore, to be a compelling alternative to perspective-independent theories of computation in physical systems. I conclude that a teleologically-based, non-perspectival mechanistic account of physical computation is to be preferred.

  • 4.
    Coelho Mollo, Dimitri
    Umeå universitet, Humanistiska fakulteten, Institutionen för idé- och samhällsstudier.
    AI-as-exploration: Navigating intelligence spaceManuskript (preprint) (Annet vitenskapelig)
    Abstract [en]

    Artificial Intelligence is a field that lives many lives, and the term has come to encompass a motley collection of scientific and commercial endeavours. In this paper, I articulate the contours of a rather neglected but central scientific role that AI has to play, which I dub `AI-as-exploration'.The basic thrust of AI-as-exploration is that of creating and studying systems that can reveal candidate building blocks of intelligence that may differ from the forms of human and animal intelligence we are familiar with. In other words, I suggest that AI is one of the best tools we have for exploring intelligence space, namely the space of possible intelligent systems. I illustrate the value of AI-as-exploration by focusing on a specific case study, i.e., recent work on the capacity to combine novel and invented concepts in humans and Large Language Models. I show that the latter, despite showing human-level accuracy in such a task, most probably solve it in ways radically different, but no less relevant to intelligence research, to those hypothesised for humans.

  • 5.
    Coelho Mollo, Dimitri
    Berlin School of Mind and Brain, Humboldt Universitaet zu Berlin, Berlin, Germany.
    Are There Teleological Functions to Compute?2019Inngår i: Philosophy of science (East Lansing), ISSN 0031-8248, E-ISSN 1539-767X, Vol. 86, nr 3, s. 431-452Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    I analyze a tension at the core of the mechanistic view of computation generated by its joint commitment to the medium independence of computational vehicles and to computational systems possessing teleological functions to compute. While computation is individuated in medium-independent terms, teleology is sensitive to the constitutive physical properties of vehicles. This tension spells trouble for the mechanistic view, suggesting that there can be no teleological functions to compute. I argue that, once considerations about the relevant function-bestowing factors for computational systems are brought to bear, the tension dissolves: physical systems can have the teleological function to compute.

  • 6.
    Coelho Mollo, Dimitri
    Department of Philosophy, King’s College, London, UK; Institut für Philosophie, Humboldt-Universität zu Berlin, Berlin, Germany.
    Being Clear on Content - Commentary on Hutto and Satne2015Inngår i: Philosophia, ISSN 0048-3893, E-ISSN 1574-9274, Vol. 43, nr 3, s. 687-699Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In the target article Hutto and Satne propose a new approach to studying mental content. Although I believe there is much to commend in their proposal, I argue that it makes no space for a kind of content that is of central importance to cognitive science, and which need not be involved in beliefs and desires: I will use the expression ‘representational content’ to refer to it. Neglecting representational content leads to an undue limitation of the contribution that the neo-Cartesian approach can offer to the naturalising content project. I claim that neo-Cartesians can, on the one hand, help account for the nature of representational content and clarify what makes representational states contentful. On the other, besides explaining the natural origins of Ur-intentionality, neo-Cartesians should also take the role of accounting for the natural origins of contentful states that fall short of beliefs and desires. Finally, I argue that the only alternative for the authors is to embrace some form of non-representationalism, as Hutto elsewhere does. The success of the proposal thereby turns on the fate of the radical non-representationalist position that it accompanies.

  • 7.
    Coelho Mollo, Dimitri
    Umeå universitet, Humanistiska fakulteten, Institutionen för idé- och samhällsstudier.
    Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models2023Inngår i: Transactions on Machine Learning ResearchArtikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Language models demonstrate both quantitative improvement and new qualitative capabilities with increasing scale. Despite their potentially transformative impact, these new capabilities are as yet poorly characterized. In order to inform future research, prepare for disruptive new model capabilities, and ameliorate socially harmful effects, it is vital that we understand the present and near-future capabilities and limitations of language models. To address this challenge, we introduce the Beyond the Imitation Game benchmark (BIG-bench). BIG-bench currently consists of 204 tasks, contributed by 442 authors across 132 institutions. Task topics are diverse, drawing problems from linguistics, childhood development, math, common-sense reasoning, biology, physics, social bias, software development, and beyond. BIG-bench focuses on tasks that are believed to be beyond the capabilities of current language models. We evaluate the behavior of OpenAI's GPT models, Google-internal dense transformer architectures, and Switch-style sparse transformers on BIG-bench, across model sizes spanning millions to hundreds of billions of parameters. In addition, a team of human expert raters performed all tasks in order to provide a strong baseline. Findings include: model performance and calibration both improve with scale, but are poor in absolute terms (and when compared with rater performance); performance is remarkably similar across model classes, though with benefits from sparsity; tasks that improve gradually and predictably commonly involve a large knowledge or memorization component, whereas tasks that exhibit "breakthrough" behavior at a critical scale often involve multiple steps or components, or brittle metrics; social bias typically increases with scale in settings with ambiguous context, but this can be improved with prompting. 

  • 8.
    Coelho Mollo, Dimitri
    Department of Philosophy, King’s College London, London, UK; Institut für Philosophie, Humboldt-Universität zu Berlin, Berlin, Germany.
    Content Pragmatism Defended2017Inngår i: Topoi: An International Review of Philosophy, ISSN 0167-7411, E-ISSN 1572-8749, Vol. 39, nr 1, s. 103-113Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In the literature on the nature and role of cognitive representation, three positions are taken across the conceptual landscape: robust realism, primitivism, and eliminativism. Recently, a fourth alternative that tries to avoid the shortcomings of traditional views has been proposed: content pragmatism. My aim is to defend pragmatism about content against some recent objections moved against the view. According to these objections, content pragmatism (a) fails to capture the role played by representation in the cognitive sciences; and/or (b) is an unstable view that ends up collapsing into one of the traditional alternatives. I argue that those arguments fail. I show that content pragmatism has as much claim to descriptive adequacy as the traditional theories. Moreover, I defend the robustness of the view by arguing that it does not collapse into any of the traditional positions. Content pragmatism therefore offers a valid and coherent account of the nature of representational content.

    Fulltekst (pdf)
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  • 9.
    Coelho Mollo, Dimitri
    Humboldt-Universität zu Berlin, Exzellenzcluster Science of Intelligence & Berlin School of Mind and Brain, Berlin, Germany; Institut für Philosophie, Berlin, Germany.
    Deflationary realism: Representation and idealisation in cognitive science2021Inngår i: Mind and language, ISSN 0268-1064, E-ISSN 1468-0017Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Debate on the nature of representation in cognitive systems tends to oscillate between robustly realist views and various anti-realist options. I defend an alternative view, deflationary realism, which sees cognitive representation as an offshoot of the extended application to cognitive systems of an explanatory model whose primary domain is public representation use. This extended application, justified by a common explanatory target, embodies idealisations, partial mismatches between model and reality. By seeing representation as part of an idealised model, deflationary realism avoids the problems with robust realist views, while keeping allegiance to realism.

    Fulltekst (pdf)
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  • 10.
    Coelho Mollo, Dimitri
    Department of Philosophy, King’s College, London, UK; Institut für Philosophie, Humboldt-Universität zu Berlin, Berlin, Germany.
    Functional individuation, mechanistic implementation: the proper way of seeing the mechanistic view of concrete computation2017Inngår i: Synthese, ISSN 0039-7857, E-ISSN 1573-0964, Vol. 195, nr 8, s. 3477-3497Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    I examine a major objection to the mechanistic view of concrete computation, stemming from an apparent tension between the abstract nature of computational explanation and the tenets of the mechanistic framework: while computational explanation is medium-independent, the mechanistic framework insists on the importance of providing some degree of structural detail about the systems target of the explanation. I show that a common reply to the objection, i.e. that mechanistic explanation of computational systems involves only weak structural constraints, is not enough to save the standard mechanistic view of computation—it trivialises the appeal to mechanism, and thus makes the account collapse into a purely functional view. I claim, however, that the objection can be put to rest once the account is appropriately amended: computational individuation is indeed functional, while mechanistic explanation plays a role in accounting for computational implementation. Since individuation and implementation are crucial elements in a satisfying account of computation in physical systems, mechanism keeps its central importance in the theory of concrete computation. Finally, I argue that my version of the mechanistic view helps to provide a convincing reply to a powerful objection against non-semantic theories of concrete computation: the argument from the multiplicity of computations.

    Fulltekst (pdf)
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  • 11.
    Coelho Mollo, Dimitri
    Umeå universitet, Humanistiska fakulteten, Institutionen för idé- och samhällsstudier. Cluster Science of Intelligence, Berlin, Germany.
    Intelligent Behaviour2024Inngår i: Erkenntnis, ISSN 0165-0106, E-ISSN 1572-8420, Vol. 89, nr 2, s. 705-721Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The notion of intelligence is relevant to several fields of research, including cognitive and comparative psychology, neuroscience, artificial intelligence, and philosophy, among others. However, there is little agreement within and across these fields on how to characterise and explain intelligence. I put forward a behavioural, operational characterisation of intelligence that can play an integrative role in the sciences of intelligence, as well as preserve the distinctive explanatory value of the notion, setting it apart from the related concepts of cognition and rationality. Finally, I examine a popular hypothesis about the underpinnings of intelligence: the capacity to manipulate internal representations of the environment. I argue that the hypothesis needs refinement, and that so refined, it applies only to some forms of intelligence.

    Fulltekst (pdf)
    fulltext
  • 12.
    Coelho Mollo, Dimitri
    Humboldt-Universität zu Berlin, Exzellenzcluster Science of Intelligence & Berlin School of Mind and Brain & Institut für Philosophie, Berlin, Germany.
    Why go for a computation-based approach to cognitive representation2021Inngår i: Synthese, ISSN 0039-7857, E-ISSN 1573-0964, Vol. 199, nr 3-4, s. 6875-6895Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    An influential view in (philosophy of) cognitive science is that computation in cognitive systems is semantic, conceptually depending on representation: to compute is to manipulate representations. I argue that accepting the non-semantic teleomechanistic view of computation lays the ground for a promising alternative strategy, in which computation helps to explain and naturalise representation, rather than the other way around. I show that this computation-based approach to representation presents six decisive advantages over the semantic view. I claim that it can improve the two most influential current theories of representation, teleosemantics and structural representation, by providing them with precious tools to tackle some of their main shortcomings. In addition, the computation-based approach opens up interesting new theoretical paths for the project of naturalising representation, in which teleology plays a role in individuating computations, but not representations.

    Fulltekst (pdf)
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  • 13. Coelho Mollo, Dimitri
    et al.
    Millière, Raphael
    Rathkopf, Charles
    Stinson, Catherine
    Conceptual Combinations - Benchmark Task for BIG-Bench2021Annet (Fagfellevurdert)
    Abstract [en]

    This is a task accepted in July 2021 as part of Google’s “Beyond the Imitation Game collaborative benchmark for measuring and extrapolating the capabilities of language models”. It is published at https://github.com/google/BIG-bench/tree/main/bigbench/benchmark_tasks/conceptual_combinations. Links to the collection of queries are below, followed by the ReadMe file that explains the task, its justification, and its performance with existing AI language models.

  • 14.
    Coelho Mollo, Dimitri
    et al.
    Umeå universitet, Humanistiska fakulteten, Institutionen för idé- och samhällsstudier.
    Millière, Raphaël
    Philosophy Department, Center for Science and Society, Columbia University, New York, USA.
    The vector grounding problemManuskript (preprint) (Annet vitenskapelig)
    Abstract [en]

    The remarkable performance of large language models (LLMs) on complex linguistic tasks has sparked a lively debate on the nature of their capabilities. Unlike humans, these models learn language exclusively from textual data, without direct interaction with the real world. Nevertheless, they can generate seemingly meaningful text about a wide range of topics. This impressive accomplishment has rekindled interest in the classical 'Symbol Grounding Problem,' which questioned whether the internal representations and outputs of classical symbolic AI systems could possess intrinsic meaning. Unlike these systems, modern LLMs are artificial neural networks that compute over vectors rather than symbols. However, an analogous problem arises for such systems, which we dub the Vector Grounding Problem. This paper has two primary objectives. First, we differentiate various ways in which internal representations can be grounded in biological or artificial systems, identifying five distinct notions discussed in the literature: referential, sensorimotor, relational, communicative, and epistemic grounding. Unfortunately, these notions of grounding are often conflated. We clarify the differences between them, and argue that referential grounding is the one that lies at the heart of the Vector Grounding Problem. Second, drawing on theories of representational content in philosophy and cognitive science, we propose that certain LLMs, particularly those fine-tuned with Reinforcement Learning from Human Feedback (RLHF), possess the necessary features to overcome the Vector Grounding Problem, as they stand in the requisite causal-historical relations to the world that underpin intrinsic meaning. We also argue that, perhaps unexpectedly, multimodality and embodiment are neither necessary nor sufficient conditions for referential grounding in artificial systems.

  • 15.
    Coelho Mollo, Dimitri
    et al.
    Umeå universitet, Humanistiska fakulteten, Institutionen för idé- och samhällsstudier.
    Vernazzani, Alfredo
    Institut für Philosophie II, Ruhr-Universität Bochum, Bochum, Germany.
    The formats of cognitive representation: a computational account2023Inngår i: Philosophy of science (East Lansing), ISSN 0031-8248, E-ISSN 1539-767XArtikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Cognitive representations are typically analysed in terms of content, vehicle and format. While current work on formats appeals to intuitions about external representations, such as words and maps, in this paper we develop a computational view of formats that does not rely on intuitions. In our view, formats are individuated by the computational profiles of vehicles, i.e., the set of constraints that fix the computational transformations vehicles can undergo. The resulting picture is strongly pluralistic, it makes space for a variety of different formats, and is intimately tied to the computational approach to cognition in cognitive science and artificial intelligence.

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