004 Datenverarbeitung; Informatik
Refine
Has Fulltext
- yes (230)
Is part of the Bibliography
- yes (230) (remove)
Year of publication
Document Type
- Journal article (123)
- Doctoral Thesis (68)
- Preprint (19)
- Working Paper (13)
- Conference Proceeding (5)
- Report (2)
Language
- English (230) (remove)
Keywords
- virtual reality (15)
- Leistungsbewertung (13)
- Quran (8)
- Robotik (8)
- Koran (7)
- Text Mining (7)
- Mobiler Roboter (6)
- Autonomer Roboter (5)
- Komplexitätstheorie (5)
- Maschinelles Lernen (5)
Institute
- Institut für Informatik (156)
- Theodor-Boveri-Institut für Biowissenschaften (29)
- Institut Mensch - Computer - Medien (17)
- Institut für deutsche Philologie (17)
- Institut für Klinische Epidemiologie und Biometrie (7)
- Center for Computational and Theoretical Biology (4)
- Graduate School of Science and Technology (3)
- Medizinische Klinik und Poliklinik II (3)
- Institut für Funktionsmaterialien und Biofabrikation (2)
- Institut für Geographie und Geologie (2)
Schriftenreihe
Sonstige beteiligte Institutionen
- Cologne Game Lab (1)
- DATE Lab, KITE Research Insititute, University Health Network, Toronto, Canada (1)
- EMBL Heidelberg (1)
- INAF Padova, Italy (1)
- Jacobs University Bremen, Germany (1)
- Servicezentrum Medizin-Informatik (Universitätsklinikum) (1)
- Social and Technological Systems (SaTS) lab, School of Art, Media, Performance and Design, York University, Toronto, Canada (1)
- TH Köln (1)
- University of Cologne (1)
- University of Padova, Italy (1)
Parametric weighted finite automata (PWFA) are a multi-dimensional generalization of weighted finite automata. The expressiveness of PWFA contains the expressiveness of weighted finite automata as well as the expressiveness of affine iterated function system. The thesis discusses theory and applications of PWFA. The properties of PWFA definable sets are studied and it is shown that some fractal generator systems can be simulated using PWFA and that various real and complex functions can be represented by PWFA. Furthermore, the decoding of PWFA and the interpretation of PWFA definable sets is discussed.
Background
Information extraction techniques that get structured representations out of unstructured data make a large amount of clinically relevant information about patients accessible for semantic applications. These methods typically rely on standardized terminologies that guide this process. Many languages and clinical domains, however, lack appropriate resources and tools, as well as evaluations of their applications, especially if detailed conceptualizations of the domain are required. For instance, German transthoracic echocardiography reports have not been targeted sufficiently before, despite of their importance for clinical trials. This work therefore aimed at development and evaluation of an information extraction component with a fine-grained terminology that enables to recognize almost all relevant information stated in German transthoracic echocardiography reports at the University Hospital of Würzburg.
Methods
A domain expert validated and iteratively refined an automatically inferred base terminology. The terminology was used by an ontology-driven information extraction system that outputs attribute value pairs. The final component has been mapped to the central elements of a standardized terminology, and it has been evaluated according to documents with different layouts.
Results
The final system achieved state-of-the-art precision (micro average.996) and recall (micro average.961) on 100 test documents that represent more than 90 % of all reports. In particular, principal aspects as defined in a standardized external terminology were recognized with f 1=.989 (micro average) and f 1=.963 (macro average). As a result of keyword matching and restraint concept extraction, the system obtained high precision also on unstructured or exceptionally short documents, and documents with uncommon layout.
Conclusions
The developed terminology and the proposed information extraction system allow to extract fine-grained information from German semi-structured transthoracic echocardiography reports with very high precision and high recall on the majority of documents at the University Hospital of Würzburg. Extracted results populate a clinical data warehouse which supports clinical research.
This thesis is devoted to the study of computational complexity theory, a branch of theoretical computer science. Computational complexity theory investigates the inherent difficulty in designing efficient algorithms for computational problems. By doing so, it analyses the scalability of computational problems and algorithms and places practical limits on what computers can actually accomplish. Computational problems are categorised into complexity classes. Among the most important complexity classes are the class NP and the subclass of NP-complete problems, which comprises many important optimisation problems in the field of operations research. Moreover, with the P-NP-problem, the class NP represents the most important unsolved question in computer science. The first part of this thesis is devoted to the study of NP-complete-, and more generally, NP-hard problems. It aims at improving our understanding of this important complexity class by systematically studying how altering NP-hard sets affects their NP-hardness. This research is related to longstanding open questions concerning the complexity of unions of disjoint NP-complete sets, and the existence of sparse NP-hard sets. The second part of the thesis is also dedicated to complexity classes but takes a different perspective: In a sense, after investigating the interior of complexity classes in the first part, the focus shifts to the description of complexity classes and thereby to the exterior in the second part. It deals with the description of complexity classes through leaf languages, a uniform framework which allows us to characterise a great variety of important complexity classes. The known concepts are complemented by a new leaf-language model. To a certain extent, this new approach combines the advantages of the known models. The presented results give evidence that the connection between the theory of formal languages and computational complexity theory might be closer than formerly known.
In this paper, we bridge the gap between procedural content generation (PCG) and user-generated content (UGC) by proposing and demonstrating an interactive agent-based model of self-assembling ensembles that can be directed though user input. We motivate these efforts by considering the opportunities technology provides to pursue game designs based on according game design frameworks. We present three different use cases of the proposed model that emphasize its potential to (1) self-assemble into predefined 3D graphical assets, (2) define new structures in the context of virtual environments by self-assembling layers on the surfaces of arbitrary 3D objects, and (3) allow novel structures to self-assemble only considering the model’s configuration and no external dependencies. To address the performance restrictions in computer games, we realized the prototypical model implementation by means of an efficient entity component system (ECS). We conclude the paper with an outlook on future steps to further explore novel interactive, dynamic PCG mechanics and to ensure their efficiency.
Heat and excessive solar radiation can produce abiotic stresses during apple maturation, resulting fruit quality. Therefore, the monitoring of temperature on fruit surface (FST) over the growing period can allow to identify thresholds, above of which several physiological disorders such as sunburn may occur in apple.
The current approaches neglect spatial variation of FST and have reduced repeatability, resulting in unreliable predictions. In this study, LiDAR laser scanning and thermal imaging were employed to detect the temperature on fruit surface by means of 3D point cloud. A process for calibrating the two sensors based on an active board target and producing a 3D thermal point cloud was suggested. After calibration, the sensor system was utilised to scan the fruit trees, while temperature values assigned in the corresponding 3D point cloud were based on the extrinsic calibration. Whereas a fruit detection algorithm was performed to segment the FST from each apple.
• The approach allows the calibration of LiDAR laser scanner with thermal camera in order to produce a 3D thermal point cloud.
• The method can be applied in apple trees for segmenting FST in 3D. Whereas the approach can be utilised to predict several physiological disorders including sunburn on fruit surface.
The ecosystem of the high northern latitudes is affected by the recently changing environmental conditions. The Arctic has undergone a significant climatic change over the last decades. The land coverage is changing and a phenological response to the warming is apparent. Remotely sensed data can assist the monitoring and quantification of these changes. The remote sensing of the Arctic was predominantly carried out by the usage of optical sensors but these encounter problems in the Arctic environment, e.g. the frequent cloud cover or the solar geometry. In contrast, the imaging of Synthetic Aperture Radar is not affected by the cloud cover and the acquisition of radar imagery is independent of the solar illumination. The objective of this work was to explore how polarimetric Synthetic Aperture Radar (PolSAR) data of TerraSAR-X, TanDEM-X, Radarsat-2 and ALOS PALSAR and interferometric-derived digital elevation model data of the TanDEM-X Mission can contribute to collect meaningful information on the actual state of the Arctic Environment. The study was conducted for Canadian sites of the Mackenzie Delta Region and Banks Island and in situ reference data were available for the assessment. The up-to-date analysis of the PolSAR data made the application of the Non-Local Means filtering and of the decomposition of co-polarized data necessary.
The Non-Local Means filter showed a high capability to preserve the image values, to keep the edges and to reduce the speckle. This supported not only the suitability for the interpretation but also for the classification. The classification accuracies of Non-Local Means filtered data were in average +10% higher compared to unfiltered images. The correlation of the co- and quad-polarized decomposition features was high for classes with distinct surface or double bounce scattering and a usage of the co-polarized data is beneficial for regions of natural land coverage and for low vegetation formations with little volume scattering. The evaluation further revealed that the X- and C-Band were most sensitive to the generalized land cover classes. It was found that the X-Band data were sensitive to low vegetation formations with low shrub density, the C-Band data were sensitive to the shrub density and the shrub dominated tundra. In contrast, the L-Band data were less sensitive to the land cover. Among the different dual-polarized data the HH/VV-polarized data were identified to be most meaningful for the characterization and classification, followed by the HH/HV-polarized and the VV/VH-polarized data. The quad-polarized data showed highest sensitivity to the land cover but differences to the co-polarized data were small. The accuracy assessment showed that spectral information was required for accurate land cover classification. The best results were obtained when spectral and radar information was combined. The benefit of including radar data in the classification was up to +15% accuracy and most significant for the classes wetland and sparse vegetated tundra. The best classifications were realized with quad-polarized C-Band and multispectral data and with co-polarized X-Band and multispectral data. The overall accuracy was up to 80% for unsupervised and up to 90% for supervised classifications. The results indicated that the shortwave co-polarized data show promise for the classification of tundra land cover since the polarimetric information is sensitive to low vegetation and the wetlands. Furthermore, co-polarized data provide a higher spatial resolution than the quad-polarized data.
The analysis of the intermediate digital elevation model data of the TanDEM-X showed a high potential for the characterization of the surface morphology. The basic and relative topographic features were shown to be of high relevance for the quantification of the surface morphology and an area-wide application is feasible. In addition, these data were of value for the classification and delineation of landforms. Such classifications will assist the delineation of geomorphological units and have potential to identify locations of actual and future morphologic activity.
Psycho-pathological conditions, such as depression or schizophrenia, are often accompanied by a distorted perception of time. People suffering from this conditions often report that the passage of time slows down considerably and that they are “stuck in time.” Virtual Reality (VR) could potentially help to diagnose and maybe treat such mental conditions. However, the conditions in which a VR simulation could correctly diagnose a time perception deviation are still unknown. In this paper, we present an experiment investigating the difference in time experience with and without a virtual body in VR, also known as avatar. The process of substituting a person’s body with a virtual body is called avatar embodiment. Numerous studies demonstrated interesting perceptual, emotional, behavioral, and psychological effects caused by avatar embodiment. However, the relations between time perception and avatar embodiment are still unclear. Whether or not the presence or absence of an avatar is already influencing time perception is still open to question. Therefore, we conducted a between-subjects design with and without avatar embodiment as well as a real condition (avatar vs. no-avatar vs. real). A group of 105 healthy subjects had to wait for seven and a half minutes in a room without any distractors (e.g., no window, magazine, people, decoration) or time indicators (e.g., clocks, sunlight). The virtual environment replicates the real physical environment. Participants were unaware that they will be asked to estimate their waiting time duration as well as describing their experience of the passage of time at a later stage. Our main finding shows that the presence of an avatar is leading to a significantly faster perceived passage of time. It seems to be promising to integrate avatar embodiment in future VR time-based therapy applications as they potentially could modulate a user’s perception of the passage of time. We also found no significant difference in time perception between the real and the VR conditions (avatar, no-avatar), but further research is needed to better understand this outcome.
The IronChip evaluation package: a package of perl modules for robust analysis of custom microarrays
(2010)
Background: Gene expression studies greatly contribute to our understanding of complex relationships in gene regulatory networks. However, the complexity of array design, production and manipulations are limiting factors, affecting data quality. The use of customized DNA microarrays improves overall data quality in many situations, however, only if for these specifically designed microarrays analysis tools are available. Results: The IronChip Evaluation Package (ICEP) is a collection of Perl utilities and an easy to use data evaluation pipeline for the analysis of microarray data with a focus on data quality of custom-designed microarrays. The package has been developed for the statistical and bioinformatical analysis of the custom cDNA microarray IronChip but can be easily adapted for other cDNA or oligonucleotide-based designed microarray platforms. ICEP uses decision tree-based algorithms to assign quality flags and performs robust analysis based on chip design properties regarding multiple repetitions, ratio cut-off, background and negative controls. Conclusions: ICEP is a stand-alone Windows application to obtain optimal data quality from custom-designed microarrays and is freely available here (see “Additional Files” section) and at: http://www.alice-dsl.net/evgeniy. vainshtein/ICEP/
In this paper, we work to understand the global IPX network from the perspective of an MVNO. In order to do this, we provide a brief description of the global architecture of mobile carriers. We provide initial results with respect to mapping the vast and complex interconnection network enabling global roaming from the point of view of a single MVNO. Finally, we provide preliminary results regarding the quality of service observed under global roaming conditions.
We attempt to identify sequences of signaling dialogs, to strengthen our understanding of the signaling behavior of IoT devices by examining a dataset containing over 270.000 distinct IoT devices whose signaling traffic has been observed over a 31-day period in a 2G network [4]. We propose a set of rules that allows the assembly of signaling dialogs into so-called sessions in order to identify common patterns and lay the foundation for future research in the areas of traffic modeling and anomaly detection.
In this article, we present approaches to interactive simulations of biohybrid systems. These simulations are comprised of two major computational components: (1) agent-based developmental models that retrace organismal growth and unfolding of technical scaffoldings and (2) interfaces to explore these models interactively. Simulations of biohybrid systems allow us to fast forward and experience their evolution over time based on our design decisions involving the choice, configuration and initial states of the deployed biological and robotic actors as well as their interplay with the environment. We briefly introduce the concept of swarm grammars, an agent-based extension of L-systems for retracing growth processes and structural artifacts. Next, we review an early augmented reality prototype for designing and projecting biohybrid system simulations into real space. In addition to models that retrace plant behaviors, we specify swarm grammar agents to braid structures in a self-organizing manner. Based on this model, both robotic and plant-driven braiding processes can be experienced and explored in virtual worlds. We present an according user interface for use in virtual reality. As we present interactive models concerning rather diverse description levels, we only ensured their principal capacity for interaction but did not consider efficiency analyzes beyond prototypic operation. We conclude this article with an outlook on future works on melding reality and virtuality to drive the design and deployment of biohybrid systems.
Crowdsourced network measurements (CNMs) are becoming increasingly popular as they assess the performance of a mobile network from the end user's perspective on a large scale. Here, network measurements are performed directly on the end-users' devices, thus taking advantage of the real-world conditions end-users encounter. However, this type of uncontrolled measurement raises questions about its validity and reliability. The problem lies in the nature of this type of data collection. In CNMs, mobile network subscribers are involved to a large extent in the measurement process, and collect data themselves for the operator. The collection of data on user devices in arbitrary locations and at uncontrolled times requires means to ensure validity and reliability. To address this issue, our paper defines concepts and guidelines for analyzing the precision of CNMs; specifically, the number of measurements required to make valid statements. In addition to the formal definition of the aspect, we illustrate the problem and use an extensive sample data set to show possible assessment approaches. This data set consists of more than 20.4 million crowdsourced mobile measurements from across France, measured by a commercial data provider.
Background
The actin cytoskeleton is a hallmark of eukaryotic cells. Its regulation as well as its interaction with other proteins is carefully orchestrated by actin interaction domains. One of the key players is the WH2 motif, which enables binding to actin monomers and filaments and is involved in the regulation of actin nucleation. Contrasting conserved domains, the identification of this motif in protein sequences is challenging, as it is short and poorly conserved.
Findings
To identify divergent members, we combined Hidden-Markov-Model (HMM) to HMM alignments with orthology predictions. Thereby, we identified nearly 500 proteins containing so far not annotated WH2 motifs. This included shootin-1, an actin binding protein involved in neuron polarization. Among others, WH2 motifs of ‘proximal to raf’ (ptr)-orthologs, which are described in the literature, but not annotated in genome databases, were identified.
Conclusion
In summary, we increased the number of WH2 motif containing proteins substantially. This identification of candidate regions for actin interaction could steer their experimental characterization. Furthermore, the approach outlined here can easily be adapted to the identification of divergent members of further domain families.
Even today, the automatic digitisation of scanned documents in general, but especially the automatic optical music recognition (OMR) of historical manuscripts, still remains an enormous challenge, since both handwritten musical symbols and text have to be identified. This paper focuses on the Medieval so-called square notation developed in the 11th–12th century, which is already composed of staff lines, staves, clefs, accidentals, and neumes that are roughly spoken connected single notes. The aim is to develop an algorithm that captures both the neumes, and in particular its melody, which can be used to reconstruct the original writing. Our pipeline is similar to the standard OMR approach and comprises a novel staff line and symbol detection algorithm based on deep Fully Convolutional Networks (FCN), which perform pixel-based predictions for either staff lines or symbols and their respective types. Then, the staff line detection combines the extracted lines to staves and yields an F\(_1\) -score of over 99% for both detecting lines and complete staves. For the music symbol detection, we choose a novel approach that skips the step to identify neumes and instead directly predicts note components (NCs) and their respective affiliation to a neume. Furthermore, the algorithm detects clefs and accidentals. Our algorithm predicts the symbol sequence of a staff with a diplomatic symbol accuracy rate (dSAR) of about 87%, which includes symbol type and location. If only the NCs without their respective connection to a neume, all clefs and accidentals are of interest, the algorithm reaches an harmonic symbol accuracy rate (hSAR) of approximately 90%. In general, the algorithm recognises a symbol in the manuscript with an F\(_1\) -score of over 96%.
The concept of digital literacy has been introduced as a new cultural technique, which is regarded as essential for successful participation in a (future) digitized world. Regarding the increasing importance of AI, literacy concepts need to be extended to account for AI-related specifics. The easy handling of the systems results in increased usage, contrasting limited conceptualizations (e.g., imagination of future importance) and competencies (e.g., knowledge about functional principles). In reference to voice-based conversational agents as a concrete application of AI, the present paper aims for the development of a measurement to assess the conceptualizations and competencies about conversational agents. In a first step, a theoretical framework of “AI literacy” is transferred to the context of conversational agent literacy. Second, the “conversational agent literacy scale” (short CALS) is developed, constituting the first attempt to measure interindividual differences in the “(il) literate” usage of conversational agents. 29 items were derived, of which 170 participants answered. An explanatory factor analysis identified five factors leading to five subscales to assess CAL: storage and transfer of the smart speaker’s data input; smart speaker’s functional principles; smart speaker’s intelligent functions, learning abilities; smart speaker’s reach and potential; smart speaker’s technological (surrounding) infrastructure. Preliminary insights into construct validity and reliability of CALS showed satisfying results. Third, using the newly developed instrument, a student sample’s CAL was assessed, revealing intermediated values. Remarkably, owning a smart speaker did not lead to higher CAL scores, confirming our basic assumption that usage of systems does not guarantee enlightened conceptualizations and competencies. In sum, the paper contributes to the first insights into the operationalization and understanding of CAL as a specific subdomain of AI-related competencies.
Social patterns and roles can develop when users talk to intelligent voice assistants (IVAs) daily. The current study investigates whether users assign different roles to devices and how this affects their usage behavior, user experience, and social perceptions. Since social roles take time to establish, we equipped 106 participants with Alexa or Google assistants and some smart home devices and observed their interactions for nine months. We analyzed diverse subjective (questionnaire) and objective data (interaction data). By combining social science and data science analyses, we identified two distinct clusters—users who assigned a friendship role to IVAs over time and users who did not. Interestingly, these clusters exhibited significant differences in their usage behavior, user experience, and social perceptions of the devices. For example, participants who assigned a role to IVAs attributed more friendship to them used them more frequently, reported more enjoyment during interactions, and perceived more empathy for IVAs. In addition, these users had distinct personal requirements, for example, they reported more loneliness. This study provides valuable insights into the role-specific effects and consequences of voice assistants. Recent developments in conversational language models such as ChatGPT suggest that the findings of this study could make an important contribution to the design of dialogic human–AI interactions.
The design and evaluation of assisting technologies to support behavior change processes have become an essential topic within the field of human-computer interaction research in general and the field of immersive intervention technologies in particular. The mechanisms and success of behavior change techniques and interventions are broadly investigated in the field of psychology. However, it is not always easy to adapt these psychological findings to the context of immersive technologies. The lack of theoretical foundation also leads to a lack of explanation as to why and how immersive interventions support behavior change processes. The Behavioral Framework for immersive Technologies (BehaveFIT) addresses this lack by 1) presenting an intelligible categorization and condensation of psychological barriers and immersive features, by 2) suggesting a mapping that shows why and how immersive technologies can help to overcome barriers and finally by 3) proposing a generic prediction path that enables a structured, theory-based approach to the development and evaluation of immersive interventions. These three steps explain how BehaveFIT can be used, and include guiding questions for each step. Further, two use cases illustrate the usage of BehaveFIT. Thus, the present paper contributes to guidance for immersive intervention design and evaluation, showing that immersive interventions support behavior change processes and explain and predict 'why' and 'how' immersive interventions can bridge the intention-behavior-gap.
Plenty of theories, models, measures, and investigations target the understanding of virtual presence, i.e., the sense of presence in immersive Virtual Reality (VR). Other varieties of the so-called eXtended Realities (XR), e.g., Augmented and Mixed Reality (AR and MR) incorporate immersive features to a lesser degree and continuously combine spatial cues from the real physical space and the simulated virtual space. This blurred separation questions the applicability of the accumulated knowledge about the similarities of virtual presence and presence occurring in other varieties of XR, and corresponding outcomes. The present work bridges this gap by analyzing the construct of presence in mixed realities (MR). To achieve this, the following presents (1) a short review of definitions, dimensions, and measurements of presence in VR, and (2) the state of the art views on MR. Additionally, we (3) derived a working definition of MR, extending the Milgram continuum. This definition is based on entities reaching from real to virtual manifestations at one time point. Entities possess different degrees of referential power, determining the selection of the frame of reference. Furthermore, we (4) identified three research desiderata, including research questions about the frame of reference, the corresponding dimension of transportation, and the dimension of realism in MR. Mainly the relationship between the main aspects of virtual presence of immersive VR, i.e., the place-illusion, and the plausibility-illusion, and of the referential power of MR entities are discussed regarding the concept, measures, and design of presence in MR. Finally, (5) we suggested an experimental setup to reveal the research heuristic behind experiments investigating presence in MR. The present work contributes to the theories and the meaning of and approaches to simulate and measure presence in MR. We hypothesize that research about essential underlying factors determining user experience (UX) in MR simulations and experiences is still in its infancy and hopes this article provides an encouraging starting point to tackle related questions.
Artificial Intelligence (AI) covers a broad spectrum of computational problems and use cases. Many of those implicate profound and sometimes intricate questions of how humans interact or should interact with AIs. Moreover, many users or future users do have abstract ideas of what AI is, significantly depending on the specific embodiment of AI applications. Human-centered-design approaches would suggest evaluating the impact of different embodiments on human perception of and interaction with AI. An approach that is difficult to realize due to the sheer complexity of application fields and embodiments in reality. However, here XR opens new possibilities to research human-AI interactions. The article’s contribution is twofold: First, it provides a theoretical treatment and model of human-AI interaction based on an XR-AI continuum as a framework for and a perspective of different approaches of XR-AI combinations. It motivates XR-AI combinations as a method to learn about the effects of prospective human-AI interfaces and shows why the combination of XR and AI fruitfully contributes to a valid and systematic investigation of human-AI interactions and interfaces. Second, the article provides two exemplary experiments investigating the aforementioned approach for two distinct AI-systems. The first experiment reveals an interesting gender effect in human-robot interaction, while the second experiment reveals an Eliza effect of a recommender system. Here the article introduces two paradigmatic implementations of the proposed XR testbed for human-AI interactions and interfaces and shows how a valid and systematic investigation can be conducted. In sum, the article opens new perspectives on how XR benefits human-centered AI design and development.
As an emerging market for voice assistants (VA), the healthcare sector imposes increasing requirements on the users’ trust in the technological system. To encourage patients to reveal sensitive data requires patients to trust in the technological counterpart. In an experimental laboratory study, participants were presented a VA, which was introduced as either a “specialist” or a “generalist” tool for sexual health. In both conditions, the VA asked the exact same health-related questions. Afterwards, participants assessed the trustworthiness of the tool and further source layers (provider, platform provider, automatic speech recognition in general, data receiver) and reported individual characteristics (disposition to trust and disclose sexual information). Results revealed that perceiving the VA as a specialist resulted in higher trustworthiness of the VA and of the provider, the platform provider and automatic speech recognition in general. Furthermore, the provider’s trustworthiness affected the perceived trustworthiness of the VA. Presenting both a theoretical line of reasoning and empirical data, the study points out the importance of the users’ perspective on the assistant. In sum, this paper argues for further analyses of trustworthiness in voice-based systems and its effects on the usage behavior as well as the impact on responsible design of future technology.