Thanks and goodbye

Thank You and farewell from the TAS Functionality Node.

As the Trustworthy Autonomous Systems Functionality Node project comes to an end, we want to express our sincere gratitude to everyone who supported and engaged with our research over the past three years. This interdisciplinary project brought together experts across robotics, computer science, ethics, law, and social science to investigate the challenges of developing trustworthy autonomous systems with evolving functionality.

One of our key findings is that giving autonomous systems the ability to adapt and change their functionality over time raises significant considerations for how these systems need to be specified, designed, verified, and regulated to ensure they remain safe, reliable, and ethical. We developed novel approaches in areas like formal verification of swarm robotics, design guidelines for soft robots with evolving properties, and regulatory frameworks for autonomous systems that can learn and change during operation. For a broader list of outputs please have a look at our post here or explore our website.

Throughout the project, we strove to explore not just the technical aspects, but the broader societal contexts and implications of autonomous systems with evolving functionality. Our work highlighted the importance of public understanding, transparency, and accountability as these technologies become more prevalent. Ethical issues around trust, consent, and moral responsibility were critically examined.

Engaging diverse stakeholders was vital to our research. We held numerous public engagement events, including interactive demonstrations, hands-on workshops, podcasts, and panel discussions. Connecting with members of the public, industry partners, policymakers, and other scholars enriched our perspectives and shaped the responsible development of trustworthy autonomous systems.

Recently we talked to members of the public about our research at the Festival of Tomorrow, and as part of that ran a Design a Robot competition for students at the Deanery Academy and Covingham Park primary – check out our blog here to find details of the entries and what they had to do. The winner at primary level was the shopper robot from Ruby- one of her prizes was a 3D model of her robot.

As we wrap up this chapter, we are immensely grateful to our partners, the broader TAS Hub community, and everyone who participated in and supported this important work. The future of evolving autonomous systems remains full of possibilities and challenges that will require ongoing multidisciplinary collaboration. We hope the foundations laid by this project will pave the way for continued innovation and dialogue in this dynamic field.

Please check out our video below, and follow us on our twitter to see the longer version, coming soon.

Our outputs

Below you’ll find a list of some of our outputs- but do check back soon or follow us on X for our upcoming work, including our ARET study.


  • AERoS: Assurance of Emergent Behaviour in Autonomous Robotic Swarms
  • Link:
  • If you’re interested in finding out more about: processes for the safety assurance of emergent behaviour in autonomous robotic swarms.
  • Abstract: The behaviours of a swarm are not explicitly engineered. Instead, they are an emergent consequence of the interactions of individual agents with each other and their environment. This emergent functionality poses a challenge to safety assurance. The main contribution of this paper is a process for the safety assurance of emergent behaviour in autonomous robotic swarms called AERoS, following the guidance on the Assurance of Machine Learning for use in Autonomous Systems (AMLAS). We explore our proposed process using a case study centred on a robot swarm operating a public cloakroom


  • Emergence of norms in interactions with complex rewards
  • Link:
  • If you’re interested in finding out more about: novel agent-based modelling approaches to investigating norm emergence.
  • Abstract: Autonomous agents are becoming increasingly ubiquitous and are playing an increasing role in wide range of safety-critical systems, such as driverless cars, exploration robots and unmanned aerial vehicles. These agents operate in highly dynamic and heterogeneous environments, resulting in complex behaviour and interactions. Therefore, the need arises to model and understand more complex and nuanced agent interactions than have previously been studied. In this paper, we propose a novel agent-based modelling approach to investigating norm emergence, in which such interactions can be investigated. To this end, while there may be an ideal set of optimally compatible actions there are also combinations that have positive rewards and are also compatible. Our approach provides a step towards identifying the conditions under which globally compatible norms are likely to emerge in the context of complex rewards. Our model is illustrated using the motivating example of self-driving cars, and we present the scenario of an autonomous vehicle performing a left-turn at a T-intersection


  • On Specifying for Trustworthiness
  • Link:
  • If you’re interested in finding out more about: the key specification challenges in the domains of resilience, trust, functionality, verifiability, security, and governance and regulation of Autonomous Systems.
  • Abstract: As autonomous systems (AS) increasingly become part of our daily lives, ensuring their trustworthiness is crucial. In order to demonstrate the trustworthiness of an AS, we first need to specify what is required for an AS to be considered trustworthy. This roadmap paper identifies key challenges for specifying for trustworthiness in AS, as identified during the “Specifying for Trustworthiness” workshop held as part of the UK Research and Innovation (UKRI) Trustworthy Autonomous Systems (TAS) programme. We look across a range of AS domains with consideration of the resilience, trust, functionality, verifiability, security, and governance and regulation of AS and identify some of the key specification challenges in these domains. We then highlight the intellectual challenges that are involved with specifying for trustworthiness in AS that cut across domains and are exacerbated by the inherent uncertainty involved with the environments in which AS need to operate




  • Clinicians and AI use: where is the professional guidance?
  • Link:
  • If you’re interested in finding out more about: the clinical, professional and reputational safety risks associated with deficits in professional guidance for clinical users of AI clinical decision support systems.
  • Abstract: With the introduction of artificial intelligence (AI) to healthcare, there is also a need for professional guidance to support its use. New (2022) reports from National Health Service AI Lab & Health Education England focus on healthcare workers’ understanding and confidence in AI clinical decision support systems (AI-CDDSs), and are concerned with developing trust in, and the trustworthiness of these systems. While they offer guidance to aid developers and purchasers of such systems, they offer little specific guidance for the clinical users who will be required to use them in patient care. This paper argues that clinical, professional and reputational safety will be risked if this deficit of professional guidance for clinical users of AI-CDDSs is not redressed. We argue it is not enough to develop training for clinical users without first establishing professional guidance regarding the rights and expectations of clinical users.



  • AI regulation: a pro-innovation approach – policy proposals: TASHub Response
  • Link:
  • Summary: Response to open consultation from: Department for Science, Innovation and Technology and Office for Artificial Intelligence



  • On Determinism of Game Engines used for Simulation-based Autonomous Vehicle Verification
  • Link:
  • If you’re interested in finding out more about: the potential causes of non-deterministic behaviours in game engines.
  • Abstract: Game engines are increasingly used as simulation platforms by the autonomous vehicle (AV) community to develop vehicle control systems and test environments. A key requirement for simulation-based development and verification is determinism, since a deterministic process will always produce the same output given the same initial conditions and event history. Thus, in a deterministic simulation environment, tests are rendered repeatable and yield simulation results that are trustworthy and straightforward to debug. However, game engines are seldom deterministic. This paper reviews and identifies the potential causes of non-deterministic behaviours in game engines. A case study using CARLA, an open-source autonomous driving simulation environment powered by Unreal Engine, is presented to highlight its inherent shortcomings in providing sufficient precision in experimental results. Different configurations and utilisations of the software and hardware are explored to determine an operational domain where the simulation precision is sufficiently low i.e.\ variance between repeated executions becomes negligible for development and testing work. Finally, a method of a general nature is proposed, that can be used to find the domains of permissible variance in game engine simulations for any given system configuration


  • Engineering Responsible And Explainable Models In Human-Agent Collectives
  • Link:
  • If you’re interested in finding out more about: novel engineering methodology based on formal model checking as a step towards providing evidence for the certification of responsible and explainable decision-making within human-agent collectives.
  • Abstract: In human-agent collectives, humans and agents need to work collaboratively and agree on collective decisions. However, ensuring that agents responsibly make decisions is a complex task, especially when encountering dilemmas where the choices available to agents are not unambiguously preferred over another. Therefore, methodologies that allow the certification of such systems are urgently needed. In this paper, we propose a novel engineering methodology based on formal model checking as a step toward providing evidence for the certification of responsible and explainable decision making within human-agent collectives. Our approach, which is based on the MCMAS model checker, verifies the decision-making behavior against the logical formulae specified to guarantee safety and controllability, and address ethical concerns. We propose the use of counterexample traces and simulation results to provide a judgment and an explanation to the AI engineer as to the reasons actions may be refused or allowed. To demonstrate the practical feasibility of our approach, we evaluate it using the real-world problem of human-UAV (unmanned aerial vehicle) teaming in dynamic and uncertain environments.


Swarm robotics

  • Building Trustworthiness by Minimizing the Sim-to-Real Gap in Fault Detection for Robot Swarms
  • Link:
  • If you’re interested in finding out more about: how well metrics can transfer from simulation to a real-world setting.
  • Abstract: As robot swarm applications move to the real-world, ensuring the safety of such systems will be critical for trust and adoption. Fault detection is an essential component in systems which require a level of safety. Previous work has identified metrics with high discriminatory power between faulty and normal states of a robot in the swarm. The method for identifying such metrics has been implemented in simulation. Here, we implement metric extraction in a real-world environment and evaluate whether the extracted metrics can overcome the “sim-to-real gap” – in other words how well it transfers from simulation to a real-world setting


  • A Data-Driven Method for Metric Extraction to Detect Faults in Robot Swarms
  • Link:
  • If you’re interested in finding out more about: self-detection of faults in robots, including methods for identifying and evaluating metrics that may be used in building a model for fault detection.
  • Abstract: Robot swarms are increasingly deployed in real-world applications. Making swarms safe will be critical to improve adoption and trust. Fault detection is a useful component in systems which require a level of safety: a key element of which are metrics that allow us to differentiate between faulty and normal (non-faulty) robots – metrics which are measurable on-board the individual robots for self-detection of faults. In this paper, we develop a method for identifying and evaluating such metrics and discuss how these metrics may be used in building a model for fault detection. We demonstrate this method for real-time error detection in a realistic use-case: intralogistics using swarms. We show that we are able to identify metrics of large effect size for various faults, demonstrating the potency of metrics selected in this way with a simple fault detection model


  • Stochastic behaviours for retrieval of storage items using simulated robot swarms
  • Link:
  • If you’re interested in finding out more about: robot swarm simulations, particularly applications for retrieval and delivery of items.
  • Abstract : Robot swarms have the potential to be used as an out-of-the-box solution for storage and retrieval that is low cost, scalable to the needs of the task, and would require minimal set up and training for the users. Swarms are adaptable, robust and scalable with a relatively low computational cost which makes them appropriate for this purpose. This project simulated a robot swarm with simple sensors and stochastic movement, collecting boxes from storage to deliver them to the user. We show in simulation that stochastic strategies based on random walk and probabilistic sampling of local boxes could give rise to competitive solutions to retrieve boxes and deliver them unordered, or following a predetermined order, within a storage scenario. The performance of the task is drastically improved using an additional simple bias rule which uses compass measurements and does not reduce the minimalism of the control. It is shown that swarm technology could provide an out-of-the-box system for storage and retrieval using only information local to each robot and with distributed control.


Soft Robotics

  • Recycled Materials for Trustworthy Soft Robots
  • Link:
  • If you’re interested in finding out more about: the recycling of soft robotic materials, reducing the amount of new material needed, lowering production costs, and reducing harmful waste.
  • Abstract: The ethical sourcing and disposal of materials has become ubiquitous and necessary across society. However, this trend towards increased sustainability has yet to find parallels in robotics research. Within the field of soft robotics, large quantities of silicones, rubbers and other elastomers are used to construct the various soft bodies and actuators. As the field grows, this will have a large negative impact on the environment. In this work we propose the effective recycling of elastomeric materials, thereby reducing the amount of new material needed, lowering costs and reducing the amount of harmful waste. We present a non-chemical process of elastomer recycle-and-reuse, where elastomeric material from old and broken soft actuators is ground into granules ranging from ≤1 mm in diameter to 3 mm in diameter and used to create new soft actuators without loss of function. Characterisation tests show that although ultimate yield strain and stress reduce with the percentage of recycled material, the silicone composites exhibit very comparable elastic properties to the pristine silicone. This suggests an effective recycling pipeline where materials are recycled into different, lower-risk, applications at each iteration. We demonstrate the effectiveness of this process in a high strain recycled bladder actuator and a soft gripper.


  • Towards a Soft Exosuit for Hypogravity Adaptation: Design and Control of Lightweight Bubble Artificial Muscles
  • Link:
  • If you’re interested in finding out more about: how soft robotic exosuits can help maintain physical fitness and health in space exploration.
  • Abstract: Lower body soft exosuits have been shown to improve the capabilities of humans in a wide range of applications, from rehabilitation to worker enhancement. Their light weight and ability to be easily sewn into fabrics make them attractive for both terrestrial and space exploration applications. One unaddressed challenge in space exploration is the prevalence of low (hypo) gravity conditions, which can have a serious deleterious effect on the human body. To address this challenge we propose the hypogravity exosuit (or HEXsuit), which can help maintain the physical fitness and health of inter-planetary travellers. A core component of the HEXsuit is compliant, comfortable and efficient soft robotic artificial muscles. A recently proposed pneumatic actuator, the Bubble Artificial Muscle (BAM), is particularly suited for integration into hypogravity exosuits. In this work we explore the design and control of lightweight BAM actuators. Characterisation results show that a thin actuator is capable of high contraction, while a thicker actuator can be used for high load applications. Two control modes were implemented: displacement control and force control. Both controllers achieve low steady state error and show high accuracy. The displacement controller is also shown to be capable of maintaining the required displacement while actively changing external loads, a typical use case within the proposed hypogravity HEXsuit. Soft Robotics, Bubble Artificial Muscles, pneumatic, artificial muscle, exoskeleton, exosuit, space exploration


  • A Contact-triggered Adaptive Soft Suction Cup
  • Link:
  • If you’re interested in finding out more about: a gripper that has the ability to adapt to objects with complex and irregular shapes.
  • Abstract: Suction adhesion is widely used by natural organisms for gripping irregular objects (e.g., rocks), but their artificial counterparts show less adaptation in the same situation. In addition, they can require complex sensing and control systems to function. In this paper, we present a contact-triggered suction cup with the ability to adapt to objects with complex and irregular shapes. The gripper has two states to adhere and release the object and the transformation from release to adhesion is passively triggered by the contact force, making it an autonomous gripper and removing the need for complex driven system. Once the suction cup experiences a contact force above a set threshold, it will automatically capture the contacting object. Only the resetting transformation from adhesion to release is actuated by a vacuum pump. The maximal suction force up to 15.1 N is generated on the non-flat surface with the suction cup diameter of 30 mm. The performance of this gripper is demonstrated on a 7 DoF robot arm which successfully picked up a variety of irregular objects. We believe that this contact-triggered gripper provides a new solution for low cost, energy-effective and adaptive soft gripping.


Uncrewed Air Vehicles

  • Wind tunnel testing of an avian-inspired morphing wing with distributed pressure sensing
  • If you’re interested in finding out more about: testing the benefits of combining bio-inspired flight technologies in a wind-tunnel model.
  • Abstract: Small fixed wing uncrewed air vehicles (UAVs) are often required to fly at low speeds and high angles of attack, particularly when operating in urban environments. This study focuses on the potential of combining two bio-inspired flight technologies to improve maneuverability under these conditions. The outstanding flight agility of birds is believed to be enabled by the capability to sense the airflow over their wings and morph their wing surfaces accordingly. To test the benefits of combining these abilities a wind tunnel model able to perform an avian-inspired wing sweep motion incorporating two arrays of pressure sensors was developed. Aerodynamic load results highlight strong changes to the pitching moment produced by the change in wing sweep angle. This suggests that wing sweep can be an alternative or complementary mechanism for pitch attitude control, improving control authority at high angles of attack. On the other hand, pressure sensing data shows the ability of these sensors to detect the fine details of the onset of aerodynamic stall. The combination of these two novel technologies is suggested as a potential method to improve UAV pitch control when flying at low speeds, when the aircraft is most susceptible to environmental disturbances.


  • Sim-to-Real Transfer for Fixed-Wing Uncrewed Aerial Vehicle
  • Link:
  • If you’re interested in finding out more about: how training of uncrewed air vehicles can mitigate the gap between simulated and real environments.
  • Abstract: Deep reinforcement learning has great potential to automatically generate flight controllers for uncrewed aerial vehicles (UAVs), however these controllers often fail to perform as expected in real world environments due to differences between the simulation environment and reality. This letter experimentally investigated how this reality gap effect could be mitigated, focusing on fixed-wing UAV pitch control in wind tunnel tests. Three different training approaches were conducted: a baseline approach that used simple linear dynamics, a high-fidelity modeling approach, and a domain randomization approach. It was found that the base line controller was susceptible to the reality gap, while the other two approaches successfully transferred to real tests. To further examine the controllers’ capabilities to generalize, a variety of configuration changes were experimentally implemented on the UAV, such as increased inertia, extended elevator area, and aileron offset. While the high-fidelity controller failed to cope with these changes, the controller with domain randomization maintained its performance. These results highlight the importance of selecting appropriate sim-to-real transfer approaches and how domain randomization is applicable to fixed-wing UAV control with uncertainty in real environments.







Showcase our use case: London here we come

Can you pick up an origami crane with a crane machine? Would you trust a robot swarm to deliver your valuables? Visitors to the Trustworthy Autonomous Systems showcase next week will get to interact with our robot swarm and have a go at on our crane machine alongside hearing about our research in regulatory and ethical considerations of both these, and aerial robotic, systems. Our multi-disciplinary team will get to share their work on these systems with policy-makers, funders and members of the Autonomous Systems and robotic community, as well as interested members of the public.

Our Professor of swarm robotics, Sabine Hauert, will also speak in a plenary to further elaborate on the outputs our team has achieved over the course of the project- as sadly it ends at the end of April. We’re all really excited to hear what everyone else has done from across the TAS Hub and the rest of the nodes, when we gather at the IET in Savoy Place, London, next Tuesday 5 and Wednesday 6 March, and explore future collaborations and areas of interest.

We’ll post on X (Twitter) throughout the event, and if you’re there please come and say hi. We’ll also post a blog soon about what we learned and who we met- so please do check back for that and a report on our participation in the Festival of Tomorrow (with our competition winners).

What is a robot and what can they do?

2024 has only just begun, but our TAS researchers are looking forward to getting out and about and meeting people…….so we are happy to announce that next week we are collaborating with the Festival of Tomorrow in Swindon. Come have a chat at the MacArthur Glen Designer outlet on Wednesday 14 or ask us questions as you try out a demo at the finale event at the Deanery secondary school on Friday 16 and Saturday 17.

We’ll be challenging your idea of what a robot is and what it can do, by showing you how a robot swarm navigates its environment, comparing your drone flying skills to machine learning, and exploring how soft grippers can be used to pick up fragile objects. At the finale, our researchers will also be featured in the panel ‘Here come the robots’ and you’ll be able to see entries in our ‘Design a robot’ competition, which we ran with Swindon school students.

AI has been all over the news this last year, and it’s no longer unusual to interact with an autonomous system in your everyday life- from Siri and Alexa, to driverless bus trials in Scotland, to shopping and movie recommendations. Our project brings together roboticists, engineers, computer scientists working alongside social scientists and philosophers to explore the implications for society of these systems, so that they’re designed and used responsibly. We would love to share our knowledge and enthusiasm about our work and get your feedback on it- and answer any burning question you have, including on careers.

We’ll be at the finale across both days, for more information and to book your tickets (most of which are free), please visit their website.   

How do you specify for an autonomous system to be trustworthy?

That is the question asked in our new research article “On Specifying for Trustworthiness”, published today in the Communications of the ACM journal. This article represents the collaborative thinking of multi-disciplinary researchers from across all six TAS nodes and hub, that emerged from a workshop held at the 2021 TAS All hands meeting. Their goal was to investigate this question, by considering how these systems operate differently within varying contexts, and to begin the journey of creating a roadmap towards top-down specifications for trustworthy autonomous systems. 

Autonomous systems are considered trustworthy when the design, engineering, and operation of these systems generates positive outcomes and mitigates potentially harmful outcomes. There are various techniques for demonstrating the trustworthiness of systems however, common to all techniques is the need to formulate specifications. A specification is a detailed formulation that provides “a definitive description of a system for the purpose of developing or validating the system” but writing them for autonomous systems to capture ‘trust’ is challenging. This is also compounded by the inherent uncertainty of the environment in which they operate. 

Framed around 10 intellectual challenges, the authors examined four different domains of autonomous  systems: when there’s a single autonomous agent (for example, automated driving, UAVs), when there’s a group of autonomous agents (for example, swarms), when there’s an autonomous agent assisting a human (for example, AI in healthcare, human–robot interaction) or when there is a group of autonomous agents collaborating with humans (for example, emergency situations, disaster relief). 

Please do watch our video below or read the paper here to find out more. We’re really pleased to be part of this important and timely research area, recognised by our acceptance into this journal which has an impact Factor of 22.7 in 2023.

All authors from University of Bristol are fully or part funded via the UKRI’s Trustworthy Autonomous Systems Node in Functionality under grant number EP/V026518/1.

Focus groups: have your say

We are looking for participants for online focus groups as part of our SWARM project, taking place in early 2024. We’re looking to get a range of perspectives about the future use of nanoswarms in cancer treatment. This project is investigating the ethics and regulations of their first in-human clinical trial. The aim is to explore how nanoswarm medicine should be regulated once this technology is available for clinical trials.

Would you like to participate?

Focus groups will be taking place in early 2024. We are looking for:

  • Oncology healthcare professionals
  • Cancer patients
  • Regulatory or policymakers in drug delivery/oncology
  • Nanomedicine researcher or developers
  • Other stakeholders including patient support and information groups, patient advisory committees, public health practitioners, professional associations for healthcare professionals, hospitals, cancer charities and family members/caregivers.

Volunteers must be over the age of 18 years old to take part. Please find more information on our website here, including a series of videos explaining the study and concepts associated with it, including “What is a nanonswarm?” below:

To take part in the focus groups please complete this Expression of Interest Form. If you have any questions please email

Are we creating a robot uprising? Shoppers tell us what they think of TAS

Our TAS team were so excited to be one of only four research projects selected to participate in Futures Festival at Cabot Circus shopping centre in Bristol on 16th September. Despite the rain, seven of our team, representing most of the aspects of project, spent a Saturday afternoon talking to many Bristolians and Bristol visitors about what TAS is trying to do, and their response to it. Visitors got to participate in some word clouds, have a go at robot-based activities and get involved in the conversation around the increased use of autonomous systems, AI and robots in our everyday lives. We were very pleased that so many people paused their shopping and other activities to come and chat with us, and we spoke to over 50 adults and children across the 4 hours.

We showed them our new project illustration:


We asked three questions that were displayed on a TV screen to engage visitors and to inspire interesting conversation: What word comes to mind when you hear “trust”?, What excites you the most about living in a world of autonomous systems? and What’s your biggest fear about living in a world of autonomous systems? After they had finished talking to us and having a go at the activities we also asked some of the visitors if they would trust a drone to deliver a secret letter and if they had learned anything from talking to us:


The children and teenage visitors especially liked the robotic activities: they could test the image identification software on a drone, try and paint a picture using a robot swarm, and move objects using a soft robot.

We had a great day and we’re really grateful to everyone who stopped on the day to talk to us. Thanks to the Futures team for arranging it. We’ll be at the Festival of Tomorrow in Swindon in February 2024 to show even more of the project- follow our page or on X (Twitter) to hear more.

Robots coming to a shopping centre near you….

Join us tomorrow (Saturday) for the Futures family fair at Cabot Circus shopping centre in Bristol. We’ll be there talking about TAS, and showcasing our work on soft, swarm and aerial robotics, as well as the social and ethical implications of autonomous systems. You can have a go at using a soft gripper to spell your name; find the picture in the swarm with our robot tiles, and see how our drone image identification system deals with bananas and corn on the cob. We want to hear what you think too- we’re better researchers when we talk about it with a wide variety of people. What does trust mean to you? What’s exciting about imagining a future of autonomous systems? What makes you nervous or afraid of it? We want to have that dialogue, and get feedback on this topical and novel area.

Find us in the main vestibule area on the ground floor near House of Fraser. We’re there from midday until 4pm, so don’t miss the team- there will be 5-7 of us throughout the afternoon, as well as other researchers from across the university, presenting their areas of expertise.

Clinicians and AI use: where is the professional guidance?

In a new paper published in BMJ’s Journal of Medical Ethics, the TAS functionality nodes’ Jonathan Ives, John Downer and Helen Smith explore the increased use of AI in healthcare and medical settings, and the lack of professional guidance around it.

Although AI has great potential to help improve medical care and alleviate the burden on healthcare workers, the authors argue that as there is no precedent for when AI or AI-influenced medical workers make a mistake, regulation should be developed as a priority to outline the rights and expectations of those working closely with it.

There have recently been reports from National Health Service AI Lab & Health Education England which focus on healthcare workers’ understanding and confidence in AI clinical decision support systems, and are concerned with developing trust in, and the trustworthiness of these systems. However while they offer guidance to aid developers and purchasers of such systems, they offer little specific guidance for the clinical users who will be required to use them in patient care.

The clinicians who will have to decide whether or not to enact an AI’s recommendations are subject to the requirements of their professional regulatory bodies in a way that AIs (or AI developers) are not. This means that clinicians carry responsibility for not only their own actions, but also the effect of the AI that they use to inform their practice.

The paper argues that clinical, professional and reputational safety will be risked if this deficit of professional guidance for clinicians, and that this should be introduced urgently alongside the existing training for clinical users.

The authors end with a call to action for clinical regulators: to unite to draft guidance for users of AI in clinical decision-making that helps manage clinical, professional and reputational risks.

More information

Read the full paper:

Read a blog about the paper on BMJ


All authors are fully or part funded via the UKRI’s Trustworthy Autonomous Systems Node in Functionality under grant number EP/V026518/1.

Helen Smith is additionally supported by the Elizabeth Blackwell Institute, University of Bristol via the Wellcome Trust Institutional Strategic Support Fund.

Jonathan Ives is in part supported by the NIHR Biomedical Research Centre at University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol. The views expressed in this publication are those of the authors and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health and Social Care.


TAS community gathers for our first International Symposium

Over three days in July, just outside Edinburgh, researchers working on autonomous systems gathered for the first International Symposium on Trustworthy Autonomous Systems at Heriot-Watt University. Although the TAS project has been running for a few years, the pandemic prevented the TAS Hub and nodes from gathering the community to share their research into trustworthiness and autonomous systems. The talks and panels consisted of a diverse range of engineers, computer scientists and social scientists, including plenaries by Professors Sharon Strover and Gina Neff.


Our functionality node presented four posters and two papers, over the course of the conference. Dr Sabine Hauert didn’t let unreliable public transport prevent her from giving a talk on “Trustworthy Swarms”, a collaboration of researchers across our node. We also presented a scoping review, with work from Dr Helen Smith, Dr Jonathan Ives, and our previous colleague Dr Ariana Manzini, on “Ethics of trust/worthiness in Autonomous Systems”.


The first day of the conference focussed on early career researchers, and a number of Early Career Researcher awards were presented to them at the nearby National Robotarium, in categories including Policy and Knowledge Transfer. We were delighted that Dr Helen Smith won one of the awards for Responsible Research and Innovation, which included a £4,000 grant towards her research. We look forward to sharing where this leads.


After we’d been joined by our international colleagues, the nodes then had a further day at the All Hands Meeting, to share what we’d done over the previous 12 months. We heard from every node, plans for UKRI’s new Responsible AI initiative, and one of the panels involved Professor Dame Wendy Hall.

Thank you to the organisers and everyone who came along to make it such a useful, interesting and friendly event.

All images credited to photographer Ryan Warburton.