Punishing Artificial Intelligence: Legal Fiction or Science Fiction

Whether causing flash crashes in financial markets, purchasing illegal drugs, or running over pedestrians, AI is increasingly engaging in activity that would be criminal for a natural person, or even an artificial person like a corporation. We argue that criminal law falls short in cases where an AI causes certain types of harm and there are no practically or legally identifiable upstream criminal actors. This Article explores potential solutions to this problem, focusing on holding AI directly criminally liable where it is acting autonomously and irreducibly. Conventional wisdom holds that punishing AI is incongruous with basic criminal law principles such as the capacity for culpability and the requirement of a guilty mind. Drawing on analogies to corporate and strict criminal liability, as well as familiar imputation principles, we show how a coherent theoretical case can be constructed for AI punishment. AI punishment could result in general deterrence and expressive benefits, and it need not run afoul of negative limitations such as punishing in excess of culpability. Ultimately, however, punishing AI is not justified, because it might entail significant costs and it would certainly require radical legal changes. Modest changes to existing criminal laws that target persons, together with potentially expanded civil liability, are a better solution to AI crime

Hallucinogens: mechanisms and medical complications

Thesis (M.A.)--Boston UniversityHallucinogens are drugs that alter consciousness by distorting primarily auditory and visual perception but they can affect any sensory system. Hallucinogens also affect judgment, orientation, memory, or emotion. Despite the profound alteration in perception, adverse effects are minimal and hallucinogens are not addictive. Hallucinogen use has its roots in shamanic practices of indigenous cultures and is even incorporated in today’s religions like the Native American Church. By putting a person in an altered state of consciousness, many religions believed that the user was able to see beyond the boundaries of reality and reach out to mythical beings. Hallucinogen use in scientific research was not popular until the 1950’s when Albert Hoffman discovered lysergic acid diethylamide (LSD). The discovery of drug encouraged further research into understanding its mechanisms and its relationship with mental diseases like schizophrenia. Unfortunately, the Comprehensive Drug Abuse Prevention and Control Act of 1970 significantly limited hallucinogenic research and human research for the last 42 years. However, animal research in the last 20 years has determined the importance of serotonergic mechanisms and more specifically the 5-HT2A receptors in mediating LSD’s hallucinogenic effects. Researchers continue to identify mechanisms of LSD action. In addition to serotonergic actions, LSD is active with dopaminergic and metabotropic glutamate receptors. PET scans and fMRI’s have also revealed the importance of the prefrontal cortical region and its interaction with other areas during a hallucinogenic state. The relationship between LSD and acute psychosis is also being explored via animal models. Although human clinical research is limited, recent research sees a much deeper relationship by linking LSD brain activity and neurotransmitter levels to psychotic behaviors. This further understanding of hallucinogens on a physiological and psychological level has led to possible psychotherapeutic areas of research in anxiety and substance abuse. This thesis describes a brief history of hallucinogenic research, the pharmacology and neuroanatomy of serotonergic hallucinogens, the acute and chronic adverse effects of serotonergic hallucinogens, the possible treatments for complications of hallucinogens, the epidemiology, the relationship between hallucinogens and schizophrenia, and possible therapeutic uses of serotonergic hallucinogens. With its minimal adverse effects in humans and its powerful influence on the human psyche, serotonergic hallucinogens are invaluable tools for understanding the human mind

Two-photon vibrational transitions in O2+{\rm O}_2^+ as probes of variation of the proton-to-electron mass ratio

Vibrational overtones in deeply bound molecules are sensitive probes for variation of the proton-to-electron mass ratio $\mu$. In nonpolar molecules, these overtones may be driven as two-photon transitions. Here, we present procedures for experiments with ${\rm O}_2^+$, including state-preparation through photoionization, a two-photon probe, and detection. We calculate transition dipole moments between all X\,^2\Pi_g vibrational levels and those of the A\,^2\Pi_u excited electronic state. Using these dipole moments, we calculate two-photon transition rates and AC-Stark-shift systematics for the overtones. We estimate other systematic effects and statistical precision. Two-photon vibrational transitions in ${\rm O}_2^+$ provide multiple routes to improved searches for $\mu$ variation.Comment: 19 pages, 3 figures, supplementary material (v2 fixes an ancillary-file upload issue

Mediating Influence of Physical Fitness on the Relationship between Academic Performance and Motor Proficiency

We explored the potential mediating influence of physical fitness on the relationship between academic performance and motor proficiency in children. 1864 students (F:926, M:938, age 11.91 (SD:0.34). Academic achievement was derived from an average of standardized tests of reading, writing, and math. The Bruininks-Oseretsky Test of Motor Performance (short-form) determined motor proficiency. Fitness (peak oxygen uptake) was established with the Léger 20-m Shuttle Run Test. OLS regression identified several significant predictors of academic performance. After controlling for age (p=0.0135), gender (p<0.0001), and parental education (p<0.0001), motor proficiency (p<0.0001), was significant. After adding physical fitness (p=0.0030) to the model the effect of motor proficiency remained significant however the point estimate was reduced from 0.0034 (p<0.0001) to 0.0026 (p<0.0001). These results suggest that physical fitness plays a mediating role on the relationship between academic performance and motor proficiency although both aerobic fitness and motor proficiency have independent roles

Integrated Navigation System: Not a Sum of Its Parts

Similar to the evolutionary process for living organisms, marine navigation systems are becoming increasingly complex and sophisticated. Both by design and function, shipboard and shore-based navigation systems are no longer individual equipment components operating independently. Instead, the trend is toward integration, data fusion and synergy. One example of this are new Performance Standards being considered by IMO to achieve a “harmonized” presentation of all navigation-related information on the display of an integrated navigation system (INS). Unlike a dedicated display for ECDIS or radar, the new INS displays will be a task-oriented composite presentations that enable the mariner to configure the display for an operational situation by selecting specific chart, radar, radar plotting aids (ARPA) and AIS information that is required for the task-at-hand. This paper gives a brief overview of the trend toward the development of INS. In addition to a brief summary of IMO performance standards for navigation equipment/systems, specific mention is made about a BSH (Germany) report on the “Functional Scope and Model of INS.” A discussion is provided about the challenges of providing navigation safety information that goes beyond traditional boundaries of products and services. Currently, many agencies continue to produce individual products and services on a component basis. Hydrographic offices grapple with trying to provide multiple products and services for paper charts, raster navigational charts (RNCs) and electronic navigational charts (ENCs) while a same time, Coast Guard and Maritime Safety agencies focus on improving Aids-to-Navigation (AtoN), Vessel Traffic Services (VTS), AIS networks -- and more recently, port security. In some respects, the continued concentration on separate products and services represents an organizational reluctance to change. This in turn, results in a fragmented, sub-optimal approach to the safety-of-navigation caused by the inability to provide mariners with “seamless” information at reasonable cost. In particular, hydrographic offices must be willing to recognize that chart information can no longer be considered to be separate, individual products. When it comes to the provision and use of chart-related information for use in an INS, the focus needs to shift to what information is actually desired, how it will be provided, what other information it will be used with, and whether it is truly up-todate

Physical and Technical Demands of Women’s Collegiate Soccer

The purpose of this dissertation was to explore the physical and technical demands of the women’s college soccer game through a case study approach. With advancements in technology, motion analysis has become commonplace in most professional environments. However, the literature on amateur soccer is quite scarce and warrants more attention. The aims of this dissertation were: 1) to describe the physical demands of each position for a women’s college soccer player as they relate to total distance covered, efforts, and distance covered in high-speed velocity bands, 2) explore the variation in physical performance during a competitive season, and 3) compare the physical and technical performance of college soccer players to see if there are correlates in performance between variables. Eleven female collegiate soccer players from a single National Collegiate Athletic Association (NCAA) institution were tracked with Global Position System devices during a competitive season. Physical variables and technical variables were analyzed to gain further insight into the specific events that occur during a women’s college soccer match. Significant differences exist between positions for total distance covered during a match, with the forward and central defensive midfielder position covering the greatest distance during a match on average. The central defender position covered a significantly less amount of distance during a match than the other five positional subcategories. Outside players (forward, outside midfielder, and fullback) covered the greatest distance at high-speed velocity bands and perform the highest volume of high-speed efforts. The only significantly different technical variable found was the pass completion percentage of the central defensive midfielder compared with other positions. The current investigation highlights the unique characteristics of female collegiate soccer players when separated and analyzed by the positional subcategories. With uniqueness present in a once thought to be homogenous population the demand for individualized training protocols becomes paramount to increase chance of optimal performance while simultaneously decreasing risk of injury

Large-Scale Optical Neural Networks based on Photoelectric Multiplication

Recent success in deep neural networks has generated strong interest in hardware accelerators to improve speed and energy consumption. This paper presents a new type of photonic accelerator based on coherent detection that is scalable to large ($N \gtrsim 10^6$) networks and can be operated at high (GHz) speeds and very low (sub-aJ) energies per multiply-and-accumulate (MAC), using the massive spatial multiplexing enabled by standard free-space optical components. In contrast to previous approaches, both weights and inputs are optically encoded so that the network can be reprogrammed and trained on the fly. Simulations of the network using models for digit- and image-classification reveal a "standard quantum limit" for optical neural networks, set by photodetector shot noise. This bound, which can be as low as 50 zJ/MAC, suggests performance below the thermodynamic (Landauer) limit for digital irreversible computation is theoretically possible in this device. The proposed accelerator can implement both fully-connected and convolutional networks. We also present a scheme for back-propagation and training that can be performed in the same hardware. This architecture will enable a new class of ultra-low-energy processors for deep learning.Comment: Text: 10 pages, 5 figures, 1 table. Supplementary: 8 pages, 5, figures, 2 table