When AIs Outperform Doctors: Confronting the Challenges of a Tort-Induced Over-Reliance on Machine Learning

Someday, perhaps soon, diagnostics generated by machine learning (ML) will have demonstrably better success rates than those generated by human doctors. What will the dominance of ML diagnostics mean for medical malpractice law, for the future of medical service provision, for the demand for certain kinds of doctors, and in the long run for the quality of medical diagnostics itself? This Article argues that once ML diagnosticians, such as those based on neural networks, are shown to be superior, existing medical malpractice law will require superior ML-generated medical diagnostics as the standard of care in clinical settings. Further, unless implemented carefully, a physician\u27s duty to use ML systems in medical diagnostics could, paradoxically, undermine the very safety standard that malpractice law set out to achieve. Although at first doctor + machine may be more effective than either alone because humans and ML systems might make very different kinds of mistakes, in time, as ML systems improve, effective ML could create overwhelming legal and ethical pressure to delegate the diagnostic process to the machine. Ultimately, a similar dynamic might extend to treatment also. If we reach the point where the bulk of clinical outcomes collected in databases are ML-generated diagnoses, this may result in future decisions that are not easily audited or understood by human doctors. Given the well-documented fact that treatment strategies are often not as effective when deployed in clinical practice compared to preliminary evaluation, the lack of transparency introduced by the ML algorithms could lead to a decrease in quality of care. This Article describes salient technical aspects of this scenario particularly as it relates to diagnosis and canvasses various possible technical and legal solutions that would allow us to avoid these unintended consequences of medical malpractice law. Ultimately, we suggest there is a strong case for altering existing medical liability rules to avoid a machine-only diagnostic regime. We argue that the appropriate revision to the standard of care requires maintaining meaningful participation in the loop by physicians the loop

CMOS Hyperbolic Sine ELIN filters for low/audio frequency biomedical applications

Hyperbolic-Sine (Sinh) filters form a subclass of Externally-Linear-Internally-Non- Linear (ELIN) systems. They can handle large-signals in a low power environment under half the capacitor area required by the more popular ELIN Log-domain filters. Their inherent class-AB nature stems from the odd property of the sinh function at the heart of their companding operation. Despite this early realisation, the Sinh filtering paradigm has not attracted the interest it deserves to date probably due to its mathematical and circuit-level complexity. This Thesis presents an overview of the CMOS weak inversion Sinh filtering paradigm and explains how biomedical systems of low- to audio-frequency range could benefit from it. Its dual scope is to: consolidate the theory behind the synthesis and design of high order Sinh continuous–time filters and more importantly to confirm their micro-power consumption and 100+ dB of DR through measured results presented for the first time. Novel high order Sinh topologies are designed by means of a systematic mathematical framework introduced. They employ a recently proposed CMOS Sinh integrator comprising only p-type devices in its translinear loops. The performance of the high order topologies is evaluated both solely and in comparison with their Log domain counterparts. A 5th order Sinh Chebyshev low pass filter is compared head-to-head with a corresponding and also novel Log domain class-AB topology, confirming that Sinh filters constitute a solution of equally high DR (100+ dB) with half the capacitor area at the expense of higher complexity and power consumption. The theoretical findings are validated by means of measured results from an 8th order notch filter for 50/60Hz noise fabricated in a 0.35μm CMOS technology. Measured results confirm a DR of 102dB, a moderate SNR of ~60dB and 74μW power consumption from 2V power supply

2008 UMaine News Press Releases

This is a catalog of press releases put out by the University of Maine Division of Marketing and Communications between January 7, 2008 and December 29, 2008

Comment concilier transition numérique et transition écologique?

Le numérique est l'une des forces majeures de transformation de nos sociétés, et l’un des principaux leviers de la croissance et de la compétitivité des entreprises au Québec. Or, l’empreinte environnementale du secteur est souvent sous-estimée par ses utilisateurs et les pouvoirs publics qui voient les applications numériques sous l’angle de la dématérialisation. En effet, malgré les gains d’efficacité énergétique de cette industrie, la multiplication des objets connectés et l’explosion des usages contribuent à la hausse des émissions de gaz à effet de serre et de la demande en ressources, au moment même où la lutte aux changements climatiques demanderait un effort considérable pour les faire diminuer. Le but de cet essai est d’évaluer les trajectoires d’évolution possibles au Québec pour concilier transition numérique et transition écologique à l’horizon 2040. Pour ce faire, une analyse prospective est réalisée à partir de la synthèse des principaux enjeux connexes aux deux transitions. Ces éléments sont décrits puis intégrés à une série d’hypothèses d’évolution au sein d’un tableau morphologique. De cette analyse systémique découlent quatre scénarios prospectifs contrastés pour le Québec en 2040. Ceux-ci explorent des avenirs radicalement différents et permettent d’illustrer l’étendue des évolutions possibles. À la lumière des enjeux identifiés et de leur manifestation à travers les scénarios prospectifs, des recommandations sont formulées pour amorcer la démarche d’une convergence entre les deux transitions au Québec. Notamment, cet essai propose de réutiliser les scénarios développés pour nourrir des arènes de discussion multidisciplinaires et multiacteurs afin d’identifier collectivement les trajectoires souhaitables et celles que l’on veut éviter. Il y est également suggéré d’accompagner les stratégies de transition d’indicateurs pour quantifier les besoins en énergie et en ressource, d’établir un cadre de contrôle des données personnelles et de prendre en compte le contexte québécois particulier