Can Artificial Intelligences Suffer from Mental Illness? A Philosophical Matter to Consider

[Comments on Relationships with Artificial Emotional Intelligence - from "Here and Now" to "There and Then"]

The structure of relationships in the past, the present and the future is shaped by the idea of humanism. Based on this construct, the article illuminates various aspects and configurations of humanism on a timeline from "here and now" to "there and then". The current reality of care goes hand in hand with an emotional alienation of relationships. Advances in technology and reductionist neurobiological ideas can make it difficult to look at a person's mental illness as a whole. Any (communication) technology that has been developed in the past or will be developed in the future will sooner or later find its way into psychiatry and psychotherapy and change relationships. Transhumanism runs the risk that people will become alienated from each other and their species. Neural networks are algorithms that work regardless of the hardware used, be it based on organic carbon units such as humans or non-organic silicon units such as the computer/cyborg. There will be different ways to achieve super intelligence. Intelligence is a "must" and consciousness is a "can". If there is a change from a homocentric to a data-centered world view and the power of humans is transferred to the algorithms, humans could lose their economic value and the humanistic goals of health and happiness would be lost.

Correcting the Brain? The Convergence of Neuroscience, Neurotechnology, Psychiatry, and Artificial Intelligence

The incorporation of neural-based technologies into psychiatry offers novel means to use neural data in patient assessment and clinical diagnosis. However, an over-optimistic technologisation of neuroscientifically-informed psychiatry risks the conflation of technological and psychological norms. Neurotechnologies promise fast, efficient, broad psychiatric insights not readily available through conventional observation of patients. Recording and processing brain signals provides information from 'beneath the skull' that can be interpreted as an account of neural processing and that can provide a basis to evaluate general behaviour and functioning. But it ought not to be forgotten that the use of such technologies is part of a human practice of neuroscience informed psychiatry. This paper notes some challenges in the integration of neural technologies into psychiatry and suggests vigilance particularly in respect to normative challenges. In this way, psychiatry can avoid a drift toward reductive technological approaches, while nonetheless benefitting from promising advances in neuroscience and technology.

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.

Addressing the ethical issues raised by synthetic human entities with embryo-like features

The "14-day rule" for embryo research stipulates that experiments with intact human embryos must not allow them to develop beyond 14 days or the appearance of the primitive streak. However, recent experiments showing that suitably cultured human pluripotent stem cells can self-organize and recapitulate embryonic features have highlighted difficulties with the 14-day rule and led to calls for its reassessment. Here we argue that these and related experiments raise more foundational issues that cannot be fixed by adjusting the 14-day rule, because the framework underlying the rule cannot adequately describe the ways by which synthetic human entities with embryo-like features (SHEEFs) might develop morally concerning features through altered forms of development. We propose that limits on research with SHEEFs be based as directly as possible on the generation of such features, and recommend that the research and bioethics communities lead a wide-ranging inquiry aimed at mapping out solutions to the ethical problems raised by them.