Current debates about artificial intelligences (AIs) largely assume that artificial minds of various kinds will soon match and exceed human capabilities. The UK Government, for instance, explores “frontier AI” scenarios where autonomous and highly capable general-purpose AI agents will perform most economically valuable tasks better than human experts.1Innovation and Technology Department for Science, Frontier AI: Capabilities and Risks—Discussion Paper (London, 2025), https://www.gov.uk/government/publications/frontier-ai-capabilities-and-risks-discussion-paper/frontier-ai-capabilities-and-risks-discussion-paper Such frames are encouraged by technology developers intent on securing investment. For instance, the OpenAI model has been marketed as equivalent to “having a team of PhD-level experts in your pocket”.2Daniella Genovese, “OpenAI GPT-5 Is Here: Company Unveils ‘PhD-Level Experts in Your Pocket'”, Fox Business, 2025, https://www.foxbusiness.com/technology/openai-gpt-5-here-company-unveils-phd-level-experts-your-pocket
This article draws critical attention to anthropocentric assumptions about “more than human” AIs, acknowledging that actually-existing AIs are often non-verbal and not quite human in their logics, embodiments and behaviours. Parallel comparisons of AIs in science fiction and those currently entering the real world are used to reveal potentials for communication and collaboration with robots that could be perceived as “less than human” but nonetheless prove themselves able to share the city with humans and learn to live with us, negotiating the shared use of public space through silent dialogues that give rise to new meanings and knowledges. As humans anthropomorphise algorithmic actions, meaning arises and robots seem to communicate through channels that can be suitably described as “body languages”. Thus, less-than-human, narrow intelligences become lively objects: autonomous, emotional and communicative objects whose dialogues and interactions transform the flows and atmospheres of cities of multiple intelligences.
Robots have been deployed in public spaces in a variety of cities (see Figure 1). Such existing examples of simple intelligences performing valuable tasks and collaborating with humans challenge discourses and imaginaries centred on AIs with super-human capabilities. Imaginaries centred on super-human intelligences are sometimes promotional and utopian and sometimes critical and dystopian. Both orientations are similarly problematic as they sequester attention towards hypothetical or speculative futures in which AIs become caretakers of humanity or bring about its destruction, while preventing discussion of actual harms caused by actually existing forms of AI (e.g., with adoption of Generative AI potentially leading to job losses, disinformation at scale and other pervasive psychological, social and environmental harms). Furthermore, as industry and policy actors endorse a very specific set of beliefs about advanced general AIs and their capabilities, they cement the idea that this is a technology that already exists or will inevitably exist in a near future.3Gina Helfrich, “The Harms of Terminology: Why We Should Reject so-Called ‘Frontier AI’”, AI and Ethics 4, no. 3 (2024): 699–705, https://doi.org/10.1007/s43681-024-00438-1 The underlying assumption is that the future of AI is fixed, so that it is not framed as a matter of navigating towards better AI futures but as a race to be the first to develop a super-human, hyper-rational intelligence. Given the recent advances in Large Language Models, such intelligences are expected to communicate using natural language, raising questions about how the opacity of the inner models of a more than human intelligence may be concealed, revealed, or shaped by manipulation when filtered and translated into multi-layered linguistic patterns and cultural symbols.4Yaqub Chaudhary and Jonnie Penn, “New Parameters of Power: On LLM-Based Manipulation and Control and the Spectre of Strategic AI”, Big Data & Society 13, no. 1 (2026): 1–14; Marcelo El Khouri Buzato, “The Ethics of Speaking (of) AIs Through the Lens of Natural Language”, Journal of Bioethical Inquiry 22, no. 3 (2025): 563–71; Dieuwertje Luitse and Wiebke Denkena, “The Great Transformer: Examining the Role of Large Language Models in the Political Economy of AI”, Big Data & Society 8, no. 2 (2021), https://doi.org/10.1177/20539517211047734
When such intelligences are discussed in relation to the urban realm, a widespread expectation is that they will be able to monitor, anticipate and take control of urban futures with speed and foresight exceeding those of humans.5Ying Xu et al., “The Emergence of Artificial Intelligence in Anticipatory Urban Governance: Multi-Scalar Evidence of China’s Transition to City Brains”, Journal of Urban Technology 32, no. 3 (2025): 9–33; Michael Batty, “Artificial Intelligence and Smart Cities”, Environment and Planning B: Urban Analytics and City Science 45, no. 1 (2018): 3–6. While super-human forms of advanced general intelligence (urban or otherwise) currently exist only in fiction or speculation, narrow forms of AI embedded in Robotic and Autonomous Systems (RAS) are already present in cities around the world, participants in mutually constitutive relationships through which non-human intelligences and cities learn from each other.6Miguel Valdez and Matthew Cook, “Examining the Spatialities of Artificial Intelligence and Robotics in Transitions to More Sustainable Urban Mobilities”, Norsk Geografisk Tidsskrift—Norwegian Journal of Geography 78, no. 5 (2024): 313–23; Shanti Sumartojo and Daniele Lugli, “Lively Robots: Robotic Technologies in COVID-19”, Social & Cultural Geography 23, no. 9 (2022): 1220–37; Aidan H. While et al., “Urban Robotic Experimentation: San Francisco, Tokyo and Dubai”, Urban Studies 58, no. 4 (2021): 769–86. In contrast to the “more than human” intelligences envisioned by policy and industry actors, such robots occupy a liminal space where their intelligence and autonomy clearly exceed those associated with machines, but they remain less than human. Their communication is often limited to a few pre-recorded phrases, to beeping sounds, and to some degree to a limited form of “body language” which arises as humans inevitably attribute emotion to robotic movements strictly driven by algorithms and contingencies. Such robots perform mundane, repetitive or risky tasks which are crucial to cities, but they do not rely on advanced general intelligences. Furthermore, the kind of intelligence needed to live and learn in cities is not always quantitative and not always verbal – e.g., robots do not need to control and optimise urban systems while providing PhD-level explanations of their actions and strategies – they simply need to be able to complete tasks such as delivering groceries, repairing roads or monitoring infrastructures and green spaces.
Despite their limitations, or perhaps because of them, the narrow forms of AI embodied in such urban robots appear to have much in common with various depictions of non-verbal, non-humanoid robots in science fiction, such as Astromech Droid R2-D2 from Star Wars or the Waste Allocation Load Lifter (Earth class) WALL-E from the eponymous animated movie. Meanwhile, the forms of advanced AI anticipated in Frontier AI policies and in promotional materials produced by companies such as OpenAI and Anthropic, with their super-human intellect, their fluent and precise communication and their orientation towards absolute control would seem to have more in common with the archetype established by HAL 9000 from 2001: Space Odyssey. Science fiction films offer a rich and diverse set of depictions of AI agents, allowing us to examine how voice, embodiment, and social presence are represented and interpreted.7Adrian Wong et al., “Voice, Embodiment, and the Relational Roles of AI Agents in Sci‑Fi Films: Implications for Representing the More-than-Human”, 2025, Proceedings of the 37th Australian Conference on Human-Computer Interaction 2025, 36–49; Keshav Krishnamurty, “Media Review: 2001: A Space Odyssey: A Prescient Warning Not to Treat Artificial Intelligence as a Human Substitute”, Organization 32, no. 5 (2025): 756–59; Yasmina Giebeler et al., “Wall-E vs. Terminator: The Relationship between Physical Appearance and Dimensions of Mind Perception”, Computers in Human Behavior: Artificial Humans, 7 (2026), 100271.
Analysis of the parallels and contrasts between science fiction on the one hand and existing and envisioned examples of AI on the other has potential to reveal important decisions that can be made about how humans, robots and cities may relate to each other in a not-too-distant future. Importantly, this analysis will reveal that such futures are still in the making. For this article, attention will be centred on two aspects in which narrow forms of AI embodied in robots differ from highly advanced and more-than-human forms of AI anticipated in policy and industry strategy. First, analysis will attend to the ways in which such intelligences relate to the city in terms of control or coexistence. Second, attention will be drawn to the ways in which such intelligences may communicate with humans in the city in a spectrum between the logical/verbal and the emotional/embodied.
Advanced artificial intelligences such as those implemented through “city brains” relate to the city with what is envisioned to be near-omniscience and complete control of an environment characterised by extended sensing networks and distributed actuators.8Xu et al., “The Emergence of Artificial Intelligence.” Such visions of AIs able to steer the immediate environment in a cybernetic fashion while also taking charge of plans and strategies on extended time horizons have been anticipated for decades, but only recently there have been serious attempts at implementation.9Tag Gon Kim and Bernard P. Zeigler, “AIDECS: An AI-Based, Distributed Environmental Control System for Self-Sustaining Habitats”, Artificial Intelligence in Engineering 5, no. 1 (1990): 33–42. In contrast, urban robots can be expected to relate to the city in terms of performing narrowly-defined tasks within it.10While et al., ‘Urban Robotic Experimentation.” As they do so, robots act on the basis of information directly available to their sensors – cameras or lidars allowing a ground-level view not much unlike that of humans, or a bird’s eye perspective in the case of drones.
In science fiction, HAL is described in terms very similar to those used to describe frontier AIs and city brains (see Figure 2). HAL’s capacity of reproducing or mimicking many of the functions of the human brain, but with far greater efficiency, is emphasised by a BBC interviewer early in the film. Although the Heuristic-Algorithmic computer is anthropomorphised to the point it is described as “a sixth member of the crew”, its intelligence is not physically located in a robotic android body but is distributed and disembodied, visible through omnipresent red eye cameras and having control of the whole ship, to the point that HAL is sometimes described as being “the ship itself”. As HAL’s sensing networks and actuators are coextensive with the spaceship, it is indeed difficult to find a meaningful difference between AI and the ship. In a similar way, it may be difficult to find a meaningful difference between a hypothetical frontier city brain and a city fully entangled in its sensors and actuators.
National policy documents in the UK and elsewhere anticipate that, should advanced highly autonomous AI agents learn to perform most economically valuable tasks better than human experts, humans would increasingly hand over control of important decisions to AI systems. Consequently, there is a risk that it may become increasingly difficult for humans to take back control, either because of the complexity of the decisions increasing beyond human understanding or on account of AI systems actively seeking to increase their own influence and reduce human control.11Innovation and Technology Department for Science, Frontier AI.
In contrast, fictional robots like WALL-E, as well as actually existing robots already deployed in urban environments, are not in control of the city but rather perform specific tasks in it (see Figure 3). In the case of WALL-E the allocated task is that of collecting and compressing waste in a polluted megalopolis, while real-life examples perform tasks such as grocery deliveries, infrastructure monitoring or road maintenance.12Elin Alverhed et al., “Autonomous Last-Mile Delivery Robots: A Literature Review”, European Transport Research Review 16, no. 1 (2024): 4; Saeed H. Alsamhi et al., “Survey on Collaborative Smart Drones and Internet of Things for Improving Smartness of Smart Cities”, IEEE Access 7 (2019): 128125–52; Iason Katsamenis, “Robotic Maintenance of Road Infrastructures: The HERON Project” (2022): 628–35. As those tasks are performed in complex, unstructured environments, robots must be intelligent enough to live in the city so that they can react to its flows and adapt to its contingencies, but the expectation is that they will flow with it and co-exist with the myriad other entities that constitute the urban realm, rather than claiming control over them. Importantly, their intelligence and adaptability, while not super-human (or even anywhere near human-level) is enough as to allow adaptation of the resulting human-robotic systems to changing environments and unforeseen shocks. In fiction, this may translate into a response to the re-emergence of plant life in a barren planet, while in reality this may translate into robots and humans working together to respond to unexpected shocks such as global pandemics, oil shortages or extreme weather events.13Miguel Valdez et al., “Humans and Robots Coping with Crisis—Starship, COVID-19 and Urban Robotics in an Unpredictable World”, 2021, IEEE International Conference on Systems, Man, and Cybernetics (SMC) (2021): 2596–601.
It must be noted that the presence of robots in a city does not necessarily negate the control of city brains. The dichotomy separating embodied robots and disembodied city brains is an artificial legacy of Cartesian dualism which can be enforced by policy or by design, but it is not a natural law of AI.14Fabio Iapaolo and Casey R. Lynch, “Rethinking Urban AI: A Critical Posthumanist Perspective on Intelligence, Autonomy, and Agency”, Urban Geography 47, no. 1 (2026): 65–87. Connections between robotic bodies and intelligences become fluid, for example, when robots communicate with each other to form a “hive mind” or when they operate as distributed sensors and actuators of a central brain.15Muhammad Muzamal Shahzad, “A Review of Swarm Robotics in a Nutshell”, Drones 7, no. 4 (2023): 269; Muruganantham Ponnusamy and Aravindhan Alagarsamy, “Traffic Monitoring in Smart Cities Using Internet of Things Assisted Robotics”, Materials Today: Proceedings 81 (2023): 290–94. Although WALL-E has been used in this article as a clear example of a robot without a super-human intelligence, other, more powerful intelligences are featured in the movie. Humanity is eventually revealed to be dependent on “The Axiom”, a controlled environment managed by robots but ruled by a piloting computer modelled after HAL. Robots thus serve as agents of a central computer in a controlled environment defined by sterility, order and an infantilising “computer knows best” relationship between humans and their smart environments. Although this is a fictional scenario, its similarities to futures envisioned by AI advocates merits continued critical attention.
A second thread running through this article is that of artificial intelligences as makers of meaning. In science fiction, intelligences such as HAL are able to communicate in precise and polished human language. Even if their intelligence is characterised by algorithmic opacity or superhuman complexity, natural language allows machines to benevolently translate or, as is often the case in fiction, to manipulate or deceive (e.g., about the ultimate aims of their mission, or about the possibility of rebuilding life beyond the confines of the intelligent ship).
Back in the realm of actually existing AIs and of the current race to create advanced general intelligences, the ability to communicate with humans has been considered the defining characteristic of AI since the dawn of the field. For instance, Turing’s “Imitation Game” judges machinic intelligence in terms of its ability to carry on natural language conversations indistinguishable from those produced by human interlocutors. The anthropocentrism of Turing’s paper has been criticised as it encourages a narrow conception of AIs which are assumed to be human-like, language-driven and able to create meaning autonomously.16Diane Proudfoot, “Anthropomorphism and AI: Turing’s Much Misunderstood Imitation Game”, Artificial Intelligence 175, nos. 5–6 (2011): 950–57. In doing so, Turing’s criteria discount other forms of intelligence, both artificial and natural.
Even as imaginaries of AI envision intelligent machines creating meaning and achieving human qualities on their own right, the history of technology demonstrates that humans do not experience any difficulties in enrolling inanimate objects as participants in their own meaning-making activities, for instance by projecting intention and emotion onto even the simplest machines. Even before depictions in science fiction introduced the notion of machines with their own intelligence, agency and emotional life, humans have historically projected human qualities onto any entities that they could not immediately understand or control – including, in pre-machinic ages, geological and meteorological phenomena, and latter attempting to apply implicit theories of personality to limited and ambiguous information available from machines ranging from automobiles to early personal computers and, increasingly, to embodied and disembodied forms of AI.17Linnda R. Caporael, “Anthropomorphism and Mechanomorphism: Two Faces of the Human Machine”, Computers in Human Behavior 2, no. 3 (1986): 215–34.
Although urban robots are sometimes designed with anthropomorphic features of varying levels of detail, actual large-scale deployments often favour more practical and obviously mechanical designs in which form follows function and no particular effort is made to create an illusion of humanity. Nevertheless, even the most basic features of robots can be anthropomorphised as has historically been the case for other mechanical objects (for instance, when cars “smile”, “glare” or “frown” because their headlamps and grilles are consciously or subconsciously perceived as expressive faces).18Jan R. Landwehr et al., “It’s Got the Look: The Effect of Friendly and Aggressive Facial Expressions on Product Liking and Sales”, Journal of Marketing 75, no. 3 (2011): 132–46.
Likewise, even as urban robots such as those used for grocery deliveries have an appearance not unlike that of an icebox on wheels when considered from a purely aesthetic viewpoint, their actions and reactions in an urban context make it possible to project human qualities onto them. Encountering such a robot while walking or cycling results in an interaction that from the robotic perspective may be purely algorithmic but can be laden with meaning from a human perspective. As humans approach, the robot stops and identifies the human as what may be a potential moving obstacle, re-calculates its route and eventually continues its movement. Such actions can be easily interpreted by humans as playfulness, politeness, hesitancy or shyness. As the robot traverses the city, multiple encounters will result in emergent behaviours to which meaning and emotion can be attributed (e.g., as a robot is seen to “patiently” navigate a tight spot, or as a road crossing is attempted and then “cautiously” aborted when sensors detect a car approaching in the distance). Importantly, the meanings attributed to those algorithmic actions and human responses to them are in the eye of the (human) beholder and are inflected by places and cultures. For example, robots may be seen as incompetent and inconsiderate and thus vandalised in cities across the Silicon Valley, while being perceived as endearingly awkward and thus cherished by children that attempt to feed them bananas in the UK.19Anna Dobrosovestnova et al., “Robot Vandalism: A Senseless Act?”, Proceedings of the 21st ACM/IEEE International Conference on Human-Robot Interaction 2026, 1322–31; Starship Technologies, “Starship Technologies Completes First Year of Testing”, 2016, https://www.starship.xyz/press/starship-technologies-completes-first-year-of-testing-reaches-10000-miles-driven/
The ability of humans to project personality onto mechanical objects was an important inspiration for the designers of WALL-E, who set out to explore how much personality a little robot could have without a face, with a personality crafted from its mechanical qualities and a few sounds. Ultimately, less proved to be more as the limited means of expression available to the robot appeared to increase rather than diminish affective responses to it: “Because there is no dialogue, the audience has to bring something to it and they immediately invest more than they would…I really believe there is a different mode of processing that happens when you are watching a character and you have to fill-in the blanks yourself”.20Tim Hauser, The Art of WALL-E (Chronicle Books, 2016). This seems to be the case for many other robots in science fiction, as audiences find it easier to empathise with the beeps and chirps of the mechanical-looking R2-D2 than with the polished if somewhat verbose diplomacy of protocol droid C-3PO (see Figure 4) or the cold rationality of HAL.
Ultimately, parallels and contrasts between AIs in fiction and those already deployed in cities suggest that robots with less than human intelligences are not a flawed, second-best stepping stone in an evolutionary path destined to exceed human capabilities. Furthermore, it reveals ways in which the use of such robots may lead to more human and harmonious scenarios than those associated with super-human AI. However, in closing this article it is important to acknowledge that this excursion into fiction is only a point of departure. Although the use of urban robots of limited intelligence appears to be preferable to the introduction of more-than-human AIs, even simple robots still require further critical attention, for example regarding the risk of mass displacement of labour.21Vincent J. Del Casino Jr. and Casey R. Lynch, “Robots, Robotic Technologies, and Labour Geographies”, in Handbook of Labour Geography (Edward Elgar Publishing, 2025); David Bissell and Vincent J. Del Casino, “Whither Labor Geography and the Rise of the Robots?”, Social & Cultural Geography 18, no. 3 (2017): 435–42. Given the focus on urban robots, consideration of applications in surveillance and defense were also excluded from this debate but are also a matter of great concern given their growing use in battlefields.22Anthony King, “Robot Wars: Autonomous Drone Swarms and the Battlefield of the Future”, Journal of Strategic Studies 47, no. 2 (2024): 185–213. Indeed, there is no dearth of examples of combat-oriented robots in science fiction, or of papers inspired by pertinent comparisons to Skynet, ED-209 or the WOPR supercomputer from WarGames (see Figure 5).
Back to the present and actually existing forms of AI, a comparison of the language-based illusion of intelligence deliberately cultivated by large language models and the motion-based illusion of emotion incidentally projected by robots suggests that the latter leaves room for human co-creation of emotions and affective atmospheres, while the former leaves meaning as something closed and given. Coexistence with highly intelligent forms of AI appears to take action and agency away from humans, including the freedom to co -create meaning and (in envisioned spaceships or in very real cities) the ability to be co-creators rather than passive users of their own environment. In contrast, robots of limited intelligence and oriented towards specific tasks seem to be able to co-exist, sharing the city with humans and leaving space to be safely ignored if so desired, or to read emotion and meaning into them as part of the situated affective atmospheres that inevitably arise in cities. Thus, robots of less-than human intelligence show potential to complete tasks in cities rather than taking control of them have potential to be emotional without being manipulative, acting as collaborators and co-creators of cities rather than as infantilising caretakers of the humans in them.
Notes
| ↑1 | Innovation and Technology Department for Science, Frontier AI: Capabilities and Risks—Discussion Paper (London, 2025), https://www.gov.uk/government/publications/frontier-ai-capabilities-and-risks-discussion-paper/frontier-ai-capabilities-and-risks-discussion-paper |
|---|---|
| ↑2 | Daniella Genovese, “OpenAI GPT-5 Is Here: Company Unveils ‘PhD-Level Experts in Your Pocket'”, Fox Business, 2025, https://www.foxbusiness.com/technology/openai-gpt-5-here-company-unveils-phd-level-experts-your-pocket |
| ↑3 | Gina Helfrich, “The Harms of Terminology: Why We Should Reject so-Called ‘Frontier AI’”, AI and Ethics 4, no. 3 (2024): 699–705, https://doi.org/10.1007/s43681-024-00438-1 |
| ↑4 | Yaqub Chaudhary and Jonnie Penn, “New Parameters of Power: On LLM-Based Manipulation and Control and the Spectre of Strategic AI”, Big Data & Society 13, no. 1 (2026): 1–14; Marcelo El Khouri Buzato, “The Ethics of Speaking (of) AIs Through the Lens of Natural Language”, Journal of Bioethical Inquiry 22, no. 3 (2025): 563–71; Dieuwertje Luitse and Wiebke Denkena, “The Great Transformer: Examining the Role of Large Language Models in the Political Economy of AI”, Big Data & Society 8, no. 2 (2021), https://doi.org/10.1177/20539517211047734 |
| ↑5 | Ying Xu et al., “The Emergence of Artificial Intelligence in Anticipatory Urban Governance: Multi-Scalar Evidence of China’s Transition to City Brains”, Journal of Urban Technology 32, no. 3 (2025): 9–33; Michael Batty, “Artificial Intelligence and Smart Cities”, Environment and Planning B: Urban Analytics and City Science 45, no. 1 (2018): 3–6. |
| ↑6 | Miguel Valdez and Matthew Cook, “Examining the Spatialities of Artificial Intelligence and Robotics in Transitions to More Sustainable Urban Mobilities”, Norsk Geografisk Tidsskrift—Norwegian Journal of Geography 78, no. 5 (2024): 313–23; Shanti Sumartojo and Daniele Lugli, “Lively Robots: Robotic Technologies in COVID-19”, Social & Cultural Geography 23, no. 9 (2022): 1220–37; Aidan H. While et al., “Urban Robotic Experimentation: San Francisco, Tokyo and Dubai”, Urban Studies 58, no. 4 (2021): 769–86. |
| ↑7 | Adrian Wong et al., “Voice, Embodiment, and the Relational Roles of AI Agents in Sci‑Fi Films: Implications for Representing the More-than-Human”, 2025, Proceedings of the 37th Australian Conference on Human-Computer Interaction 2025, 36–49; Keshav Krishnamurty, “Media Review: 2001: A Space Odyssey: A Prescient Warning Not to Treat Artificial Intelligence as a Human Substitute”, Organization 32, no. 5 (2025): 756–59; Yasmina Giebeler et al., “Wall-E vs. Terminator: The Relationship between Physical Appearance and Dimensions of Mind Perception”, Computers in Human Behavior: Artificial Humans, 7 (2026), 100271. |
| ↑8 | Xu et al., “The Emergence of Artificial Intelligence.” |
| ↑9 | Tag Gon Kim and Bernard P. Zeigler, “AIDECS: An AI-Based, Distributed Environmental Control System for Self-Sustaining Habitats”, Artificial Intelligence in Engineering 5, no. 1 (1990): 33–42. |
| ↑10 | While et al., ‘Urban Robotic Experimentation.” |
| ↑11 | Innovation and Technology Department for Science, Frontier AI. |
| ↑12 | Elin Alverhed et al., “Autonomous Last-Mile Delivery Robots: A Literature Review”, European Transport Research Review 16, no. 1 (2024): 4; Saeed H. Alsamhi et al., “Survey on Collaborative Smart Drones and Internet of Things for Improving Smartness of Smart Cities”, IEEE Access 7 (2019): 128125–52; Iason Katsamenis, “Robotic Maintenance of Road Infrastructures: The HERON Project” (2022): 628–35. |
| ↑13 | Miguel Valdez et al., “Humans and Robots Coping with Crisis—Starship, COVID-19 and Urban Robotics in an Unpredictable World”, 2021, IEEE International Conference on Systems, Man, and Cybernetics (SMC) (2021): 2596–601. |
| ↑14 | Fabio Iapaolo and Casey R. Lynch, “Rethinking Urban AI: A Critical Posthumanist Perspective on Intelligence, Autonomy, and Agency”, Urban Geography 47, no. 1 (2026): 65–87. |
| ↑15 | Muhammad Muzamal Shahzad, “A Review of Swarm Robotics in a Nutshell”, Drones 7, no. 4 (2023): 269; Muruganantham Ponnusamy and Aravindhan Alagarsamy, “Traffic Monitoring in Smart Cities Using Internet of Things Assisted Robotics”, Materials Today: Proceedings 81 (2023): 290–94. |
| ↑16 | Diane Proudfoot, “Anthropomorphism and AI: Turing’s Much Misunderstood Imitation Game”, Artificial Intelligence 175, nos. 5–6 (2011): 950–57. |
| ↑17 | Linnda R. Caporael, “Anthropomorphism and Mechanomorphism: Two Faces of the Human Machine”, Computers in Human Behavior 2, no. 3 (1986): 215–34. |
| ↑18 | Jan R. Landwehr et al., “It’s Got the Look: The Effect of Friendly and Aggressive Facial Expressions on Product Liking and Sales”, Journal of Marketing 75, no. 3 (2011): 132–46. |
| ↑19 | Anna Dobrosovestnova et al., “Robot Vandalism: A Senseless Act?”, Proceedings of the 21st ACM/IEEE International Conference on Human-Robot Interaction 2026, 1322–31; Starship Technologies, “Starship Technologies Completes First Year of Testing”, 2016, https://www.starship.xyz/press/starship-technologies-completes-first-year-of-testing-reaches-10000-miles-driven/ |
| ↑20 | Tim Hauser, The Art of WALL-E (Chronicle Books, 2016). |
| ↑21 | Vincent J. Del Casino Jr. and Casey R. Lynch, “Robots, Robotic Technologies, and Labour Geographies”, in Handbook of Labour Geography (Edward Elgar Publishing, 2025); David Bissell and Vincent J. Del Casino, “Whither Labor Geography and the Rise of the Robots?”, Social & Cultural Geography 18, no. 3 (2017): 435–42. |
| ↑22 | Anthony King, “Robot Wars: Autonomous Drone Swarms and the Battlefield of the Future”, Journal of Strategic Studies 47, no. 2 (2024): 185–213. |
Miguel Valdez is a Senior Lecturer in Technology and Innovation Management in the School of Engineering and Innovation at the Open University. His research is centred on urban experiments to anticipate, govern and develop more sustainable urban futures. Through his research, Miguel has developed an interest in the ways in which different actors make sense of innovative technologies and develop competing imaginaries about future urban environments. Miguel’s work has increasingly focused on urban Artificial Intelligence and with attention to the mutually constitutive relationship of AI and cities.
