Digital surveillance technologies using artificial intelligence (AI) tools such as computer vision and facial recognition are becoming cheaper and easier to integrate into governance practices worldwide. Morocco serves as an example of how such technologies are becoming key tools of governance in authoritarian contexts. Based on qualitative fieldwork including semi-structured interviews, observation, and extensive desk reviews, this chapter focusses on the role played by AI-enhanced technology in urban surveillance and the control of migration between the Moroccan–Spanish borders. Two cross-cutting issues emerge: first, while international donors provide funding for urban and border surveillance projects, their role in enforcing transparency mechanisms in their implementation remains limited; second, Morocco’s existing legal framework hinders any kind of public oversight. Video surveillance is treated as the sole prerogative of the security apparatus, and so far public actors have avoided to engage directly with the topic. The lack of institutional oversight and public debate on the matter raise serious concerns on the extent to which the deployment of such technologies affects citizens’ rights. AI-enhanced surveillance is thus an intrinsically transnational challenge in which private interests of economic gain and public interests of national security collide with citizens’ human rights across the Global North/Global South divide.
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Over the past few years a growing number of artists have critiqued the ubiquity of identity recognition technologies. Specifically, the use of these technologies by state security programs, tech-giants and multinational corporations has met with opposition and controversy. A popular form of resistance to recognition technology is sought in strategies of masking and camouflage. Zach Blas, Leo Selvaggio, Sterling Crispin and Adam Harvey are among a group of internationally acclaimed artists who have developed subversive anti-facial recognition masks that disrupt identification technologies. This paper examines the ontological underpinnings of these popular and widely exhibited mask projects. Over and against a binary understanding and criticism of identity recognition technology, I propose to take a relational turn to reimagine these technologies not as an object for our eyes, but as a relationship between living organisms and things. A relational perspective cuts through dualist and anthropocentric conceptions of recognition technology opening pathways to intersectional forms of resistance and critique. Moreover, if human-machine relationships are to be understood as coming into being in mutual dependency, if the boundaries between online and offline are always already blurred, if the human and the machine live intertwined lives and it is no longer clear where the one stops and the other starts, we need to revise our understanding of the self. A relational understanding of recognition technology moves away from a notion of the self as an isolated and demarcated entity in favour of an understanding of the self as relationally connected, embedded and interdependent. This could alter the way we relate to machines and multiplies the lines of flight we can take out of a culture of calculated settings.
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We present a novel hierarchical model for human activity recognition. In contrast with approaches that successively recognize actions and activities, our approach jointly models actions and activities in a unified framework, and their labels are simultaneously predicted. The model is embedded with a latent layer that is able to capture a richer class of contextual information in both state-state and observation-state pairs. Although loops are present in the model, the model has an overall linear-chain structure, where the exact inference is tractable. Therefore, the model is very efficient in both inference and learning. The parameters of the graphical model are learned with a structured support vector machine. A data-driven approach is used to initialize the latent variables; therefore, no manual labeling for the latent states is required. The experimental results from using two benchmark datasets show that our model outperforms the state-of-the-art approach, and our model is computationally more efficient.
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Chemo-enzymatic peptide synthesis is unique in enabling the fast and sustainable synthesis of cyclic peptides, complex peptides and functionalized mini-proteins. The starting materials are routinely obtained by solid-phase peptide synthesis. One of the starting materials requires an oxo-ester functionality for recognition by the enzymes active site. The SPPS-based synthesis of the oxo-ester functionality still suffers from significant byproduct formation and low overall synthesis yields. The solution to this is introduction of the oxo-ester functionality at the end of the SPPS via a so-called Passerini reaction. Such a process does not only result in a more efficient production of cyclic or long peptides, but also expand the scope towards proteins derived from biological synthesis (i.e. recombinant proteins). To highlight the relevance of this proposed methodology, we will demonstrate a site-selective modification of the pharmaceutically important drug insulin.
In the past decade, particularly smaller drones have started to claim their share of the sky due to their potential applications in the civil sector as flying-eyes, noses, and very recently as flying hands. Network partners from various application domains: safety, Agro, Energy & logistic are curious about the next leap in this field, namely, collaborative Sky-workers. Their main practical question is essentially: “Can multiple small drones transport a large object over a high altitude together in outdoor applications?” The industrial partners, together with Saxion and RUG, will conduct feasibility study to investigate if it is possible to develop these collaborative Sky-workers and to identify which possibilities this new technology will offer. Design science research methodology, which focuses on solution-oriented applied research involving multiple iterations with rigorous evaluations, will be used to research the feasibility of the main technological building blocks. They are: • Accurate localization based on onboard sensors. • Safe and optimal interaction controller for collaborative aerial transport Within this project, the first proof-of-concepts will be developed. The results of this project will be used to expand the existing network and formulate a bigger project to address additional critical aspects in order to develop a complete framework for collaborative drones.
"Speak the Future" presents a novel test case at the intersection of scientific innovation and public engagement. Leveraging the power of real-time AI image generation, the project empowers festival participants to verbally describe their visions for a sustainable and regenerative future. These descriptions are instantly transformed into captivating imagery using SDXL Turbo, fostering collective engagement and tangible visualisation of abstract sustainability concepts. This unique interplay of speech recognition, AI, and projection technology breaks new ground in public engagement methods. The project offers valuable insights into public perceptions and aspirations for sustainability, as well as understanding the effectiveness of AI-powered visualisation and regenerative applications of AI. Ultimately, this will serve as a springboard for PhD research that will aim to understand How AI can serve as a vehicle for crafting regenerative futures? By employing real-time AI image generation, the project directly tests its effectiveness in fostering public engagement with sustainable futures. Analysing participant interaction and feedback sheds light on how AI-powered visualisation tools can enhance comprehension and engagement. Furthermore, the project fosters public understanding and appreciation of research. The interactive and accessible nature of "Speak the Future" demystifies the research process, showcasing its relevance and impact on everyday life. Moreover, by directly involving the public in co-creating visual representations of their aspirations, the project builds an emotional connection and sense of ownership, potentially leading to continued engagement and action beyond the festival setting. "Speak the Future" promises to be a groundbreaking initiative, bridging the gap between scientific innovation and public engagement in sustainability discourse. By harnessing the power of AI for collective visualisation, the project not only gathers valuable data for researchers but also empowers the public to envision and work towards a brighter, more sustainable future.
