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Since the emergence of generative AI, creative workers have spoken up about the career-based harms they have experienced arising from this new technology. A common theme in these accounts of harm is that generative AI models are trained on workers' creative output without their consent and without giving credit or compensation to the original creators. This paper reports findings from 20 interviews with creative workers in three domains: visual art and design, writing, and programming. We investigate the gaps between current AI governance strategies, what creative workers want out of generative AI governance, and the nuanced role of creative workers' consent, compensation and credit for training AI models on their work. Finally, we make recommendations for how generative AI can be governed and how operators of generative AI systems might more ethically train models on creative output in the future., Comment: Conditionally accepted at the ACM Conference on Human Factors in Computing Systems (CHI 2025)

Generative AI systems often generate outputs about real people, even when not explicitly prompted to do so. This can lead to significant reputational and privacy harms, especially when sensitive, misleading, and outright false. This paper considers what legal tools currently exist to protect such individuals, with a particular focus on defamation and data protection law. We explore the potential of libel law, arguing that it is a potential but not an ideal remedy, due to lack of harmonization, and the focus on damages rather than systematic prevention of future libel. We then turn to data protection law, arguing that the data subject rights to erasure and rectification may offer some more meaningful protection, although the technical feasibility of compliance is a matter of ongoing research. We conclude by noting the limitations of these individualistic remedies and hint at the need for a more systemic, environmental approach to protecting the infosphere against generative AI.

We introduce "book links" as a generalization of braids in open book decompositions; this new class of objects includes both braids and plats as special cases. We then prove a version of Markov's theorem in this general setting by extending the theory of open book foliations., Comment: 11 pages, 9 figures

Parenting brings emotional and physical challenges, from balancing work, childcare, and finances to coping with exhaustion and limited personal time. Yet, one in three parents never seek support. AI systems potentially offer stigma-free, accessible, and affordable solutions. Yet, user adoption often fails due to issues with explainability and reliability. To see if these issues could be solved using a co-design approach, we developed and tested NurtureBot, a wellbeing support assistant for new parents. 32 parents co-designed the system through Asynchronous Remote Communities method, identifying the key challenge as achieving a "successful chat". Aspart of co-design, parents role-played as NurturBot, rewriting its dialogues to improve user understanding, control, and outcomes. The refined prototype evaluated by 32 initial and 46 new parents, showed improved user experience and usability, with final CUQ score of 91.3/100, demonstrating successful interaction patterns. Our process revealed useful interaction design lessons for effective AI parenting support.

When selecting applicants for scholarships, universities, or jobs, practitioners often aim for a diverse cohort of qualified recipients. However, differing articulations, constructs, and notions of diversity prevents decision-makers from operationalising and progressing towards the diversity they all agree is needed. To understand this challenge of translation from values, to requirements, to decision support tools (DSTs), we conducted participatory design studies exploring professionals' varied perceptions of diversity and how to build for them. Our results suggest three definitions of diversity: bringing together different perspectives; ensuring representativeness of a base population; and contextualising applications, which we use to create the Diversity Triangle. We experience-prototyped DSTs reflecting each angle of the Diversity Triangle to enhance decision-making around diversity. We find that notions of diversity are highly diverse; efforts to design DSTs for diversity should start by working with organisations to distil 'diversity' into definitions and design requirements., Comment: 32 pages, 11 figures

We give some new link detection results for link Floer homology, Khovanov homology and annular Khovanov homology. The links we detect arise via different closure operations on $3$-braids. Examples of our results include that link Floer homology detects the Mazur link, that annular Khovanov homology detects the Mazur pattern, and that Khovanov homology detects L6a2 and L9n15. The Mazur pattern detection result depends on a new bound on the rank of the annular Khovanov homology of certain links., Comment: 28 pages, 4 figures

Martin showed that link Floer homology detects braid axes. In this paper we extend this result to give a topological characterisation of links which are almost braided from the point of view of link Floer homology. The result is inspired by work of Baldwin-Sivek and Li-Ye on nearly fibered knots. Applications include that Khovanov homology detects the Whitehead link and $L7n2$, as well as infinite families of detection results for link Floer homology and annular Khovanov homology., Comment: 67 pages, 15 figures

Emerging scholarship suggests that the EU legal concept of direct discrimination - where a person is given different treatment on grounds of a protected characteristic - may apply to various algorithmic decision-making contexts. This has important implications: unlike indirect discrimination, there is generally no 'objective justification' stage in the direct discrimination framework, which means that the deployment of directly discriminatory algorithms will usually be unlawful per se. In this paper, we focus on the most likely candidate for direct discrimination in the algorithmic context, termed inherent direct discrimination, where a proxy is inextricably linked to a protected characteristic. We draw on computer science literature to suggest that, in the algorithmic context, 'treatment on the grounds of' needs to be understood in terms of two steps: proxy capacity and proxy use. Only where both elements can be made out can direct discrimination be said to be `on grounds of' a protected characteristic. We analyse the legal conditions of our proposed proxy capacity and proxy use tests. Based on this analysis, we discuss technical approaches and metrics that could be developed or applied to identify inherent direct discrimination in algorithmic decision-making.

In a recent note F. Lin showed that if a rational homology sphere $Y$ admits a taut foliation then the Heegaard Floer module $HF^-(Y)$ contains a copy of $\mathbf{F}[U]/U$ as a summand (arXiv:2309.01222). This implies that either the $L$-space conjecture is false or that Heegaard Floer homology satisfies a geography restriction. We verify that Lin's geography restriction holds for a wide class of rational homology spheres. Indeed, we show that the Heegaard Floer module $HF^-(Y)$ may satisfy a stronger geography restriction., Comment: 19 pages

Dense systems of magnetic nanoparticles may exhibit dipolar collective behavior. However, two fundamental questions remain unsolved: i) whether the transition temperature may be affected by the particle anisotropy or it is essentially determined by the intensity of the interparticle dipolar interactions, and ii) what is the minimum ratio of dipole-dipole interaction ($E_\text{dd}$) to nanoparticle anisotropy ($K_{\text{ef}}V$, anisotropy $\times$ volume) energies necessary to crossover from individual to collective behavior. A series of particle assemblies with similarly intense dipolar interactions but widely varying anisotropy is studied. The $K_\text{ef}$ is tuned through different degrees of cobalt-doping in maghemite nanoparticles, resulting in a variation of nearly an order of magnitude. All the bare particle compacts display collective behavior, except the one made with the highest anisotropy particles, which presents ``marginal'' features. Thus, a threshold of $K_{\text{ef}} V/E_{\text{dd}} \approx 130$ to suppress collective behavior is derived, in good agreement with Monte Carlo simulations. This translates into a crossover value of $\approx 1.7$ for the easily accessible parameter $T_\text{MAX}$(interacting)$/T_\text{MAX}$(non-interacting) (ratio of the peak temperatures of the zero-field-cooled magnetization curves of interacting and dilute particle systems), which is successfully tested against the literature to predict the individual-like$/$collective behavior of any given interacting particle assembly comprising relatively uniform particles., Comment: 24 pages (proof version), 6 figures

Text-to-image (TTI) generative models can be used to generate photorealistic images from a given text-string input. These models offer great potential to mitigate challenges to the uptake of machine learning in the earth sciences. However, the rapid increase in their use has raised questions about fairness and biases, with most research to-date focusing on social and cultural areas rather than domain-specific considerations. We conducted a case study for the earth sciences, focusing on the field of fluvial geomorphology, where we evaluated subject-area specific biases in the training data and downstream model performance of Stable Diffusion (v1.5). In addition to perpetuating Western biases, we found that the training data over-represented scenic locations, such as famous rivers and waterfalls, and showed serious under- and over-representation of many morphological and environmental terms. Despite biased training data, we found that with careful prompting, the Stable Diffusion model was able to generate photorealistic synthetic river images reproducing many important environmental and morphological characteristics. Furthermore, conditional control techniques, such as the use of condition maps with ControlNet were effective for providing additional constraints on output images. Despite great potential for the use of TTI models in the earth sciences field, we advocate for caution in sensitive applications, and advocate for domain-specific reviews of training data and image generation biases to mitigate perpetuation of existing biases.

Detailed measurements of the spectral structure of cosmic-ray electrons and positrons from 10.6 GeV to 7.5 TeV are presented from over 7 years of observations with the CALorimetric Electron Telescope (CALET) on the International Space Station. Because of the excellent energy resolution (a few percent above 10 GeV) and the outstanding e/p separation (10$^5$), CALET provides optimal performance for a detailed search of structures in the energy spectrum. The analysis uses data up to the end of 2022, and the statistics of observed electron candidates has increased more than 3 times since the last publication in 2018. By adopting an updated boosted decision tree analysis, a sufficient proton rejection power up to 7.5 TeV is achieved, with a residual proton contamination less than 10%. The observed energy spectrum becomes gradually harder in the lower energy region from around 30 GeV, consistently with AMS-02, but from 300 to 600 GeV it is considerably softer than the spectra measured by DAMPE and Fermi-LAT. At high energies, the spectrum presents a sharp break around 1 TeV, with a spectral index change from -3.15 to -3.91, and a broken power law fitting the data in the energy range from 30 GeV to 4.8 TeV better than a single power law with 6.9 sigma significance, which is compatible with the DAMPE results. The break is consistent with the expected effects of radiation loss during the propagation from distant sources (except the highest energy bin). We have fitted the spectrum with a model consistent with the positron flux measured by AMS-02 below 1 TeV and interpreted the electron + positron spectrum with possible contributions from pulsars and nearby sources. Above 4.8 TeV, a possible contribution from known nearby supernova remnants, including Vela, is addressed by an event-by-event analysis providing a higher proton-rejection power than a purely statistical analysis., Comment: main text: 7 pages, 4 figures; supplemental material: 10 pages, 8 figures, 1 table

Data-driven decision-making and AI applications present exciting new opportunities delivering widespread benefits. The rapid adoption of such applications triggers legitimate concerns about loss of privacy and misuse of personal data. This leads to a growing and pervasive tension between harvesting ubiquitous data on the Web and the need to protect individuals. Decentralised personal data stores (PDS) such as Solid are frameworks designed to give individuals ultimate control over their personal data. But current PDS approaches have limited support for ensuring privacy when computations combine data spread across users. Secure Multi-Party Computation (MPC) is a well-known subfield of cryptography, enabling multiple autonomous parties to collaboratively compute a function while ensuring the secrecy of inputs (input privacy). These two technologies complement each other, but existing practices fall short in addressing the requirements and challenges of introducing MPC in a PDS environment. For the first time, we propose a modular design for integrating MPC with Solid while respecting the requirements of decentralisation in this context. Our architecture, Libertas, requires no protocol level changes in the underlying design of Solid, and can be adapted to other PDS. We further show how this can be combined with existing differential privacy techniques to also ensure output privacy. We use empirical benchmarks to inform and evaluate our implementation and design choices. We show the technical feasibility and scalability pattern of the proposed system in two novel scenarios -- 1) empowering gig workers with aggregate computations on their earnings data; and 2) generating high-quality differentially-private synthetic data without requiring a trusted centre. With this, we demonstrate the linear scalability of Libertas, and gained insights about compute optimisations under such an architecture.

The pair-angle distribution function (PADF) is a three- and four-atom correlation function that can characterise the local angular structure of disordered materials, particles or nanocrystalline materials. The PADF can be measured by x-ray or electron fluctuation diffraction experiments, which can be collected by scanning a small beam across a structurally disordered sample or flowing a sample across the beam path. It is a natural generalisation of the established pair-distribution methods, which do not provide angular information. This software package provides tools to calculate the PADF from from fluctuation diffraction data. The package includes tools for calculating the intensity correlation function, which is a necessary step in the PADF calculation and also the basis for other fluctuation scattering techniques., Comment: 21 pages, 3 figures

We prove conditions for global nonlinear stability of Oldroyd-B viscoelatic fluid flows in the Couette shear flow geometry. Global stability is inferred by analysing a new functional, called a perturbation entropy, to quantify the magnitude of the polymer perturbations from their steady-state values. The conditions for global stability extend, in a physically natural manner, classical results on global stability of Newtonian Couette flow.

We present the observation of a charge-sign dependent solar modulation of galactic cosmic rays (GCRs) with the CALorimetric Electron Telescope onboard the International Space Station over 6 yr, corresponding to the positive polarity of the solar magnetic field. The observed variation of proton count rate is consistent with the neutron monitor count rate, validating our methods for determining the proton count rate. It is observed by the CALorimetric Electron Telescope that both GCR electron and proton count rates at the same average rigidity vary in anticorrelation with the tilt angle of the heliospheric current sheet, while the amplitude of the variation is significantly larger in the electron count rate than in the proton count rate. We show that this observed charge-sign dependence is reproduced by a numerical ``drift model'' of the GCR transport in the heliosphere. This is a clear signature of the drift effect on the long-term solar modulation observed with a single detector., Comment: main text: 6 pages, 3 figures, supplemental material: 8 pages, 3 figures, 1 table

Since GDPR went into effect in 2018, many other data protection and privacy regulations have been released. With the new regulation, there has been an associated increase in industry professionals focused on data protection and privacy. Building on related work showing the potential benefits of knowledge management in organisational compliance and privacy engineering, this paper presents the findings of an exploratory qualitative study with data protection officers and other privacy professionals. We found issues with knowledge management to be the underlying challenge of our participants' feedback. Our participants noted four categories of feedback: (1) a perceived disconnect between regulation and practice, (2) a general lack of clear job description, (3) the need for data protection and privacy to be involved at every level of an organisation, (4) knowledge management tools exist but are not used effectively. This paper questions what knowledge management or automation solutions may prove to be effective in establishing better computer-supported work environments., Comment: 27 pages, 1 figure, 1 table, DRAFT and Unpublished

We present the results of a direct measurement of the cosmic-ray helium spectrum with the CALET instrument in operation on the International Space Station since 2015. The observation period covered by this analysis spans from October 13, 2015 to April 30, 2022 (2392 days). The very wide dynamic range of CALET allowed to collect helium data over a large energy interval, from ~40 GeV to ~250 TeV, for the first time with a single instrument in Low Earth Orbit. The measured spectrum shows evidence of a deviation of the flux from a single power-law by more than 8$\sigma$ with a progressive spectral hardening from a few hundred GeV to a few tens of TeV. This result is consistent with the data reported by space instruments including PAMELA, AMS-02, DAMPE and balloon instruments including CREAM. At higher energy we report the onset of a softening of the helium spectrum around 30 TeV (total kinetic energy). Though affected by large uncertainties in the highest energy bins, the observation of a flux reduction turns out to be consistent with the most recent results of DAMPE. A Double Broken Power Law (DBPL) is found to fit simultaneously both spectral features: the hardening (at lower energy) and the softening (at higher energy). A measurement of the proton to helium flux ratio in the energy range from 60 GeV/n to about 60 TeV/n is also presented, using the CALET proton flux recently updated with higher statistics.

We give a diagrammatic characterization of the $(1,1)$ knots in the three-sphere and lens spaces which admit large Dehn surgeries to manifolds with Heegaard Floer homology of next-to-minimal rank. This is inspired by a corresponding result for $(1,1)$ knots which admit large Dehn surgeries to manifolds with Heegaard Floer homology of minimal rank due to Greene-Lewallen-Vafaee., Comment: 20 pages, 13 figures

Heegaard Floer homology and knot Floer homology are powerful invariants of 3-manifolds and links respectively. L-space knots are knots which admit Dehn surgeries to 3-manifolds with Heegaard Floer homology of minimal rank. In this paper we study almost L-space knots, which are knots admitting large Dehn surgeries to 3-manifolds with Heegaard Floer homology of next-to-minimal rank. Our main result is a classification of the $CFK^\infty$ type of almost L-space knots. As corollaries we show that almost L-space knots satisfy various topological properties, including some given by Baldwin-Sivek. We also give some new cable link detection results., Comment: Comments welcome!

How much are we to trust a decision made by an AI algorithm? Trusting an algorithm without cause may lead to abuse, and mistrusting it may similarly lead to disuse. Trust in an AI is only desirable if it is warranted; thus, calibrating trust is critical to ensuring appropriate use. In the name of calibrating trust appropriately, AI developers should provide contracts specifying use cases in which an algorithm can and cannot be trusted. Automated explanation of AI outputs is often touted as a method by which trust can be built in the algorithm. However, automated explanations arise from algorithms themselves, so trust in these explanations is similarly only desirable if it is warranted. Developers of algorithms explaining AI outputs (xAI algorithms) should provide similar contracts, which should specify use cases in which an explanation can and cannot be trusted.

We present the measurement of the energy dependence of the boron flux in cosmic rays and its ratio to the carbon flux \textcolor{black}{in an energy interval from 8.4 GeV$/n$ to 3.8 TeV$/n$} based on the data collected by the CALorimetric Electron Telescope (CALET) during $\sim 6.4$ years of operation on the International Space Station. An update of the energy spectrum of carbon is also presented with an increase in statistics over our previous measurement. The observed boron flux shows a spectral hardening at the same transition energy $E_0 \sim 200$ GeV$/n$ of the C spectrum, though B and C fluxes have different energy dependences. The spectral index of the B spectrum is found to be $\gamma = -3.047\pm0.024$ in the interval $25 < E < 200$ GeV$/n$. The B spectrum hardens by $\Delta \gamma_B=0.25\pm0.12$, while the best fit value for the spectral variation of C is $\Delta \gamma_C=0.19\pm0.03$. The B/C flux ratio is compatible with a hardening of $0.09\pm0.05$, though a single power-law energy dependence cannot be ruled out given the current statistical uncertainties. A break in the B/C ratio energy dependence would support the recent AMS-02 observations that secondary cosmic rays exhibit a stronger hardening than primary ones. We also perform a fit to the B/C ratio with a leaky-box model of the cosmic-ray propagation in the Galaxy in order to probe a possible residual value $\lambda_0$ of the mean escape path length $\lambda$ at high energy. We find that our B/C data are compatible with a non-zero value of $\lambda_0$, which can be interpreted as the column density of matter that cosmic rays cross within the acceleration region., Comment: main text: 7 pages, 3 figures; supplemental material: 13 pages, 8 figures, 3 tables

A precise measurement of the cosmic-ray proton spectrum with the Calorimetric Electron Telescope (CALET) is presented in the energy interval from 50 GeV to 60 TeV, and the observation of a softening of the spectrum above 10 TeV is reported. The analysis is based on the data collected during $\sim$6.2 years of smooth operations aboard the International Space Station and covers a broader energy range with respect to the previous proton flux measurement by CALET, with an increase of the available statistics by a factor of $\sim$2.2. Above a few hundred GeV we confirm our previous observation of a progressive spectral hardening with a higher significance (more than 20 sigma). In the multi-TeV region we observe a second spectral feature with a softening around 10 TeV and a spectral index change from =2.6 to -2.9 consistently, within the errors, with the shape of the spectrum reported by DAMPE. We apply a simultaneous fit of the proton differential spectrum which well reproduces the gradual change of the spectral index encompassing the lower energy power-law regime and the two spectral features observed at higher energies., Comment: main text: 8 pages, 5 figures, supplemental material: 9 pages, 7 figures, 1 table, marked as a PRL Editor's Suggestion

We apply sutured Floer homology techniques to study the knot and link Floer homologies of various links with annuli embedded in their exteriors. Our main results include, for large $m$, characterizations of links with the same link Floer homology as $(n,nm)$-cables of $L$-space knots or the same knot Floer homology as $(2,2m)$-cables of $L$-space knots. Note that Knot Floer homology carries less grading data than Link Floer homology, so the latter characterizations are stronger than former. These characterizations yield some new link detection results., Comment: 16 pages; Accepted version to be published in MRL

The CALorimetric Electron Telescope (CALET) on the International Space Station (ISS) consists of a high-energy cosmic ray CALorimeter (CAL) and a lower-energy CALET Gamma ray Burst Monitor (CGBM). CAL is sensitive to electrons up to 20 TeV, cosmic ray nuclei from Z = 1 through Z $\sim$ 40, and gamma rays over the range 1 GeV - 10 TeV. CGBM observes gamma rays from 7 keV to 20 MeV. The combined CAL-CGBM instrument has conducted a search for gamma ray bursts (GRBs) since Oct. 2015. We report here on the results of a search for X-ray/gamma ray counterparts to gravitational wave events reported during the LIGO/Virgo observing run O3. No events have been detected that pass all acceptance criteria. We describe the components, performance, and triggering algorithms of the CGBM - the two Hard X-ray Monitors (HXM) consisting of LaBr$_{3}$(Ce) scintillators sensitive to 7 keV to 1 MeV gamma rays and a Soft Gamma ray Monitor (SGM) BGO scintillator sensitive to 40 keV to 20 MeV - and the high-energy CAL consisting of a CHarge-Detection module (CHD), IMaging Calorimeter (IMC), and fully active Total Absorption Calorimeter (TASC). The analysis procedure is described and upper limits to the time-averaged fluxes are presented., Comment: 27 pages, 10 figures. Accepted for publication in ApJ

A recently published pre-print titled 'GDPR and the Lost Generation of Innovative Apps' by Jan{\ss}en et al. observes that a third of apps on the Google Play Store disappeared from this app store around the introduction of the GDPR in May 2018. The authors deduce 'that GDPR is the cause'. The effects of the GDPR on the app economy are an important field to study. Unfortunately, the paper currently lacks a control condition and a key variable. As a result, the effects on app exits reported in the paper are likely overestimated, as we will discuss. We believe there are other factors which may better explain these changes in the Play Store aside from the GDPR., Comment: Response to NBER preprint 'GDPR and the Lost Generation of Innovative Apps'

Critical examinations of AI systems often apply principles such as fairness, justice, accountability, and safety, which is reflected in AI regulations such as the EU AI Act. Are such principles sufficient to promote the design of systems that support human flourishing? Even if a system is in some sense fair, just, or 'safe', it can nonetheless be exploitative, coercive, inconvenient, or otherwise conflict with cultural, individual, or social values. This paper proposes a dimension of interactional ethics thus far overlooked: the ways AI systems should treat human beings. For this purpose, we explore the philosophical concept of respect: if respect is something everyone needs and deserves, shouldn't technology aim to be respectful? Despite its intuitive simplicity, respect in philosophy is a complex concept with many disparate senses. Like fairness or justice, respect can characterise how people deserve to be treated; but rather than relating primarily to the distribution of benefits or punishments, respect relates to how people regard one another, and how this translates to perception, treatment, and behaviour. We explore respect broadly across several literatures, synthesising perspectives on respect from Kantian, post-Kantian, dramaturgical, and agential realist design perspectives with a goal of drawing together a view of what respect could mean for AI. In so doing, we identify ways that respect may guide us towards more sociable artefacts that ethically and inclusively honour and recognise humans using the rich social language that we have evolved to interact with one another every day., Comment: To appear in the Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society (AIES '22)