Artificial intelligence (AI) systems have demonstrated impressive performance across a variety of clinical tasks. However, notoriously, sometimes these systems are “black boxes.” The initial response in the literature was a demand for “explainable AI.” However, recently, several authors have suggested that making AI more explainable or “interpretable” is likely to be at the cost of the accuracy of these systems and that prioritizing interpretability in medical AI may constitute a “lethal prejudice.” In this article, we defend the value of interpretability in the context of the use of AI in medicine. Clinicians may prefer interpretable systems over more accurate black boxes, which in turn is sufficient to give designers of AI reason to prefer more interpretable systems in order to ensure that AI is adopted and its benefits realized. Moreover, clinicians may be justified in this preference. Achieving the downstream benefits from AI is critically dependent on how the outputs of these systems are interpreted by physicians and patients. A preference for the use of highly accurate black box AI systems, over less accurate but more interpretable systems, may itself constitute a form of lethal prejudice that may diminish the benefits of AI to—and perhaps even harm—patients.

Intelligence, as measured by grades and/or standardized test scores, plays a principal role in the medical school admissions process in most nations. Yet while sufficient intelligence is necessary to practice medicine effectively, no evidence suggests that surplus intelligence beyond that threshold is correlated with providing higher quality medical care. This paper argues that using perceived measures of intelligence to distinguish between applicants, at levels that exceed the level of intelligence required to practice medicine, is both unfair to applicants and fails to serve the interests of patients.

When is it justified to use opaque artificial intelligence (AI) output in medical decision-making? Consideration of this question is of central importance for the responsible use of opaque machine learning (ML) models, which have been shown to produce accurate and reliable diagnoses, prognoses, and treatment suggestions in medicine. In this article, I discuss the merits of two answers to the question. According to the Explanation View, clinicians must have access to an explanation of why an output was produced. According to the Validation View, it is sufficient that the AI system has been validated using established standards for safety and reliability. I defend the Explanation View against two lines of criticism, and I argue that within the framework of evidence-based medicine mere validation seems insufficient for the use of AI output. I end by characterizing the epistemic responsibility of clinicians and point out how a mere AI output cannot in itself ground a practical conclusion about what to do.

Antinatalism assigns reproduction a negative value. There should be fewer or no births. Those who say that there should be fewer births have been called conditional antinatalists. A better name for their view would be selective pronatalism. Those who say that there should be no births face two challenges. They must define the scope of their no-birth policy. Does it apply only to human or sentient beings or can it also be extended to all organic life, perhaps even to machine consciousness? And whatever the scope, they have to justify the eventual extinction of humankind or other life forms, an inevitable consequence of unconditional antinatalism. Different axiologies and moral theories produce different responses to these challenges. It is argued that a two-value conflict-sensitive negative utilitarianism would produce a kind and reasonable justification for ending at least human and factory-animal reproduction. The conclusion is purely moral and supports only voluntary extinction for humankind.

Studies have shown that some covertly conscious brain-injured patients, who are behaviorally unresponsive, can reply to simple questions via neuronal responses. Given the possibility of such neuronal responses, Andrew Peterson et al. have argued that there is warrant for some covertly conscious patients being included in low-stakes medical decisions using neuronal responses, which could protect and enhance their autonomy. The justification for giving credence to alleged neuronal responses must be analyzed from various perspectives, including neurology, bioethics, law, and as we suggest, philosophy of mind. In this article, we analyze the warrant for giving credence to neuronal responses from two different views in philosophy of mind. We consider how nonreductive physicalism’s causal exclusion problem elicits doubt about interpreting neural activity as indicating a conscious response. By contrast, such an interpretation is supported by the mind-body powers model of neural correlates of consciousness inspired by hylomorphism.

Conscious but incapacitated patients need protection from both undertreatment and overtreatment, for they are exceptionally vulnerable, and dependent on others to act in their interests. In the United States, the law prioritizes autonomy over best interests in decision making. Yet U.S. courts, using both substituted judgment and best interests decision making standards, frequently prohibit the withdrawal of life-sustaining treatment from conscious but incapacitated patients, such as those in the minimally conscious state, even when ostensibly seeking to determine what patients would have wanted. In the United Kingdom, under the Mental Capacity Act of 2005, courts decide on the best interests of incapacitated patients by, in part, taking into account the past wishes and values of the patient. This paper examines and compares those ethicolegal approaches to decision making on behalf of conscious but incapacitated patients. We argue for a limited interpretation of best interests such that the standard is properly used only when the preferences of a conscious, but incapacitated patient are unknown and unknowable. When patient preferences and values are known or can be reasonably inferred, using a holistic, all-things-considered substituted judgment standard respects patient autonomy.

Neurorights are widely discussed as a means of protecting phenomena like cognitive liberty and freedom of thought. This article is especially interested in example cases where these protections are sought in light of fast-paced developments in neurotechnologies that appear capable of reading the mind in some significant sense. While it is prudent to take care and seek to protect the mind from prying, questions remain over the kinds of claims that prompt concerns over mind reading. The nature of these claims should influence how exactly rights may or may not offer justifiable solutions. Overall, the exploration of neurotechnological mind reading questions here will come in terms of philosophical accounts of mental content and neuroreductionism. The contribution will be to present a contextualization of questions arising from ‘mind-reading’ neurotechnology, and appraisal of if or how neurorights respond to them.

This is a personal narrative of my stroke and recovery experience, and the medical, psychological, and social circumstances surrounding it.