The underuse of AI in the health sector: Opportunity costs, success stories, risks and recommendations.

Purpose: This contribution explores the underuse of artificial intelligence (AI) in the health sector, what this means for practice, and how much the underuse can cost. Attention is drawn to the relevance of an issue that the European Parliament has outlined as a "major threat" in 2020. At its heart is the risk that research and development on trusted AI systems for medicine and digital health will pile up in lab centers without generating further practical relevance. Our analysis highlights why researchers, practitioners and especially policymakers, should pay attention to this phenomenon. Methods: The paper examines the ways in which governments and public agencies are addressing the underuse of AI. As governments and international organizations often acknowledge the limitations of their own initiatives, the contribution explores the causes of the current issues and suggests ways to improve initiatives for digital health. Results: Recommendations address the development of standards, models of regulatory governance, assessment of the opportunity costs of underuse of technology, and the urgency of the problem. Conclusions: The exponential pace of AI advances and innovations makes the risks of underuse of AI increasingly threatening.

Explainable artificial intelligence (XAI): closing the gap between image analysis and navigation in complex invasive diagnostic procedures.

LITERATURE REVIEW: Cystoscopy is the gold standard for initial macroscopic assessments of the human urinary bladder to rule out (or diagnose) bladder cancer (BCa). Despite having guidelines, cystoscopic findings are diverse and often challenging to classify. The extent of the false negatives and false positives in cystoscopic diagnosis is currently unknown. We suspect that there is a certain degree of under-diagnosis (like the failure to detect malignant tumours) and over-diagnosis (e.g. sending the patient for unnecessary transurethral resection of bladder tumors with anesthesia) that put the patient at risk. CONCLUSIONS: XAI robot-assisted cystoscopes would help to overcome the risks/flaws of conventional cystoscopy. Cystoscopy is considered a less life-threatening starting point for automation than open surgical procedures. Semi-autonomous cystoscopy requires standards and cystoscopy is a good procedure to establish a model that can then be exported/copied to other procedures of endoscopy and surgery. Standards also define the automation levels-an issue for medical product law. These cystoscopy skills do not give full autonomy to the machine, and represent a surgical parallel to 'Autonomous Driving' (where a standard requires a human supervisor to remain in the 'vehicle'). Here in robotic cystoscopy, a human supervisor remains bedside in the 'operating room' as a 'human-in-the-loop' in order to safeguard patients. The urologists will be able to delegate personal- and time-consuming cystoscopy to a specialised nurse. The result of automated diagnostic cystoscopy is a short video (with pre-processed photos from the video), which are then reviewed by the urologists at a more convenient time.

Operational framework and training standard requirements for AI-empowered robotic surgery.

BACKGROUND: For autonomous robot-delivered surgeries to ever become a feasible option, we recommend the combination of human-centered artificial intelligence (AI) and transparent machine learning (ML), with integrated Gross anatomy models. This can be supplemented with medical imaging data of cadavers for performance evaluation. METHODS: We reviewed technological advances and state-of-the-art documented developments. We undertook a literature search on surgical robotics and skills, tracing agent studies, relevant frameworks, and standards for AI. This embraced transparency aspects of AI. CONCLUSION: We recommend "a procedure/skill template" for teaching AI that can be used by a surgeon. Similar existing methodologies show that when such a metric-based approach is used for training surgeons, cardiologists, and anesthetists, it results in a >40% error reduction in objectively assessed intraoperative procedures. The integration of Explainable AI and ML, and novel tissue characterization sensorics to tele-operated robotic-assisted procedures with medical imaged cadavers, provides robotic guidance and refines tissue classifications at a molecular level.

Chapitre 8. Hommes ou robots dans l'espace. Approches éthique et juridique.

Who of human or robot has its place in space? The robot, because it can replace human beings for exploration missions that are always particularly dangerous both for the health and the safety of astronauts. But human also tends to gain a place in space, when he can be assisted by the robot as a tool that facilitates his work, or when the machine can serve as a medium to extend humanity to the confines of the universe. All these hypotheses raise ethical and legal questions to which the article gives some solutions.

[Chapter 8. Humans or robots in space. Ethical and legal approaches.] / Chapitre 8. Hommes ou robots dans l'espace. Approches éthique et juridique.

Who of human or robot has its place in space? The robot, because it can replace human beings for exploration missions that are always particularly dangerous both for the health and the safety of astronauts. But human also tends to gain a place in space, when he can be assisted by the robot as a tool that facilitates his work, or when the machine can serve as a medium to extend humanity to the confines of the universe. All these hypotheses raise ethical and legal questions to which the article gives some solutions.

Legal, regulatory, and ethical frameworks for development of standards in artificial intelligence (AI) and autonomous robotic surgery.

BACKGROUND: This paper aims to move the debate forward regarding the potential for artificial intelligence (AI) and autonomous robotic surgery with a particular focus on ethics, regulation and legal aspects (such as civil law, international law, tort law, liability, medical malpractice, privacy and product/device legislation, among other aspects). METHODS: We conducted an intensive literature search on current or emerging AI and autonomous technologies (eg, vehicles), military and medical technologies (eg, surgical robots), relevant frameworks and standards, cyber security/safety- and legal-systems worldwide. We provide a discussion on unique challenges for robotic surgery faced by proposals made for AI more generally (eg, Explainable AI) and machine learning more specifically (eg, black box), as well as recommendations for developing and improving relevant frameworks or standards. CONCLUSION: We classify responsibility into the following: (1) Accountability; (2) Liability; and (3) Culpability. All three aspects were addressed when discussing responsibility for AI and autonomous surgical robots, be these civil or military patients (however, these aspects may require revision in cases where robots become citizens). The component which produces the least clarity is Culpability, since it is unthinkable in the current state of technology. We envision that in the near future a surgical robot can learn and perform routine operative tasks that can then be supervised by a human surgeon. This represents a surgical parallel to autonomously driven vehicles. Here a human remains in the 'driving seat' as a 'doctor-in-the-loop' thereby safeguarding patients undergoing operations that are supported by surgical machines with autonomous capabilities.

[Robotization of the human under the law]. / La robotisation de l'homme au regard du droit.

The robotization of the human implies a more or less intimate hybridization with the machine. When it participates in the repair of the human being, it generates a modification of the legal status of the robot that passes from the category of things to that of personn, which has remarkable effects in terms of civil liability. However, as the therapeutic aspect of hybridization disapears, not only does the robot move away from the category of personn, but the hybrid body raises many questions about fundamental rights.