Opportunity and Opportunism in Artificial Intelligence-Powered Data Extraction: A Value-Centered Approach.

Radiologists' traditional role in the diagnostic process is to respond to specific clinical questions and reduce uncertainty enough to permit treatment decisions to be made. This charge is rapidly evolving due to forces such as artificial intelligence (AI), big data (opportunistic imaging, imaging prognostication), and advanced diagnostic technologies. A new modernistic paradigm is emerging whereby radiologists, in conjunction with computer algorithms, will be tasked with extracting as much information from imaging data as possible, often without a specific clinical question being posed and independent of any stated clinical need.

Fairness as an afterthought: An American perspective on fairness in model developer-clinician user collaborations.

Numerous ethics guidelines have been handed down over the last few years on the ethical applications of machine learning models. Virtually every one of them mentions the importance of "fairness" in the development and use of these models. Unfortunately, though, these ethics documents omit providing a consensually adopted definition or characterization of fairness.

AI pitfalls and what not to do: mitigating bias in AI.

Various forms of artificial intelligence (AI) applications are being deployed and used in many healthcare systems. As the use of these applications increases, we are learning the failures of these models and how they can perpetuate bias. With these new lessons, we need to prioritize bias evaluation and mitigation for radiology applications; all the while not ignoring the impact of changes in the larger enterprise AI deployment which may have downstream impact on performance of AI models.

Characteristics of Radiologists Serving as Medical Malpractice Expert Witnesses for Defense Versus Plaintiff.

Purpose: Previous studies have reported higher qualification characteristics for anesthesiologists, neurosurgeons, orthopedic surgeons, and otolaryngologists serving as defense (versus plaintiff) medical malpractice expert witnesses. We assessed such characteristics for radiologist expert witnesses.

Methods: Using the Westlaw legal research database, we identified radiologists serving as experts in all indexed medical malpractice cases between 2010 and 2019.

When Artificial Intelligence Models Surpass Physician Performance: Medical Malpractice Liability in an Era of Advanced Artificial Intelligence.

It seems inevitable that diagnostic and recommender artificial intelligence models will ultimately reach a point when they outperform human clinicians. Just as antibiotics displaced a host of medicinals for treating infections, the superior performance of such models will force their adoption. This article contemplates certain ethical and legal implications bearing on that adoption, especially because they involve a clinician's exposure to allegations of malpractice.

Congee for the Soul.

Provision of adequate nutrition to elderly patients who develop dysphagia after a stroke can be quite challenging, often leading to the placement of a percutaneous entero-gastrostomy (PEG) tube for nutritional support. This hypothetical case describes the additional challenge of cross-cultural belief that leads a daughter to provide oral feeding to her mother, an act that the medical team believes is dangerous and the daughter sees as salubrious. In this case, what is the proper balance between patient safety and deference to cultural traditions and norms? Where are the limits? Two commentaries offer insights for conflict resolution, including recommending that the medical team seek to understand the cultural motivations of the family, balancing safety and respect for cultural norms.

How Might Artificial Intelligence Applications Impact Risk Management?

Artificial intelligence (AI) applications have attracted considerable ethical attention for good reasons. Although AI models might advance human welfare in unprecedented ways, progress will not occur without substantial risks. This article considers 3 such risks: system malfunctions, privacy protections, and consent to data repurposing.

Sharing and Selling Images: Ethical and Regulatory Considerations for Radiologists.

Opportunities to share or sell images are common in radiology. But because these images typically originate as protected health information, their use admits a host of ethical and regulatory considerations. This article discusses four scenarios that reflect data sharing or selling arrangements in radiology, especially as they might occur in "big data" systems or applications.

Reasonable Persons, Autonomous Persons, and Lady Hale: Determining a Standard for Risk Disclosure.

Among various kinds of disclosures typically required in research as well as in clinical scenarios, risk information figures prominently. A key question is, what kinds of risk information would the reasonable person want to know? I will argue, however, that the reasonable person construct is and always has been incapable of settling this very question. After parsing the nebulous if not "contentless" character of the reasonable person, I will explain how Western courts have actually adjudicated cases of "negligent nondisclosure," that is, cases in which patient-plaintiffs allege that their informed consent rights were violated by the failure of their health providers to inform them of reasonably foreseeable risks that subsequently materialized.

Ethical considerations in artificial intelligence.

With artificial intelligence (AI) precipitously perched at the apex of the hype curve, the promise of transforming the disparate fields of healthcare, finance, journalism, and security and law enforcement, among others, is enormous. For healthcare - particularly radiology - AI is anticipated to facilitate improved diagnostics, workflow, and therapeutic planning and monitoring. And, while it is also causing some trepidation among radiologists regarding its uncertain impact on the demand and training of our current and future workforce, most of us welcome the potential to harness AI for transformative improvements in our ability to diagnose disease more accurately and earlier in the populations we serve.

Overriding advance directives: A 20-year legal and ethical overview.

Health professionals have been known to override patients' advance directives. The most ethically problematic instances involve a directive's explicitly forbidding the administration of some life-prolonging treatment like resuscitation or intubation with artificial ventilation. Sometimes the code team is unaware of the directive, but in other instances, the override is done knowingly and intentionally with clinicians later pleading that it was done "in the patient's best interests.

Welcoming the "Intel-ethicist".

In this issue of the Hastings Center Report, Mélanie Terrasse, Moti Gorin, and Dominic Sisti, urge ethicists to devote scholarly attention to a wave of troubling artificial intelligence applications affecting health consumers' rights and the quality of their care. I very much agree. We already have neuroethicists, business ethicists, and genetics ethicists; AI-related systems in health care present more than enough warrant to herald the appearance of a new ethics specialist-the "intel-ethicist," let's say.

Failures of foreseeability: Risk management considerations in reducing allegations of sexual violence in psychiatric units.

This article begins with a brief discussion of findings on causal factors leading to allegations of sexual violence in health care facilities and then offers the author's account of 4 such cases that he reviewed, 3 of which occurred in psychiatric units. These cases show remarkably similar variables, especially involving decisions to allow male and female patients to commingle, the inadequate physical layout of the units, poor or absent video surveillance, and staff unacquainted with institutional policies on patient safety or refusing to enforce relevant rules. These variables arguably amount to "failures of foreseeability" that reasonably cautious health care personnel should recognize as facilitating or enabling sexual violence.

Ethical considerations in stem cell research on neurologic and orthopedic conditions.

The range and gravity of ethical considerations in stem cell research are remarkable and, quite possibly, unprecedented. From the point of securing stem cells for implantation, through the translational and first-in-humans process, and then proceeding through clinical trials culminating in product or service line launch, the entire research trajectory is replete with risk, uncertainty, and problems overweighing foreseeable harms against hoped-for benefits. This article offers an overview of some of the most salient ethical challenges of stem cell research, including ones involving moral status, the intersection of research risks and informed consent processes, methodologic considerations in early phase 1 trials, the temptation to exaggerate the benefits of research discoveries, managing conflicts of interest, and the ethical obligation to conduct various monitoring practices throughout a trial, which could last years.

Alcohol and drug testing of health professionals following preventable adverse events: a bad idea.

Various kinds of alcohol and drug testing, such as preemployment, routine, and for-cause testing, are commonly performed by employers. While healthcare organizations usually require preemployment drug testing, they vary on whether personnel will be subjected to further testing. Recently, a call has gone out for postincident testing among physicians who are involved in serious, preventable events, especially ones leading to a patient's death.