Machines Make Mistakes Too: Planning for AI Liability in Contracting

Recent advances in artificial intelligence have set off a frenzy of commercial activity, with companies fearful that they may fall behind if they are unable to quickly incorporate the new technology into their products or their internal processes. At the same time, numerous scholars from the machine learning community have warned of the fundamental risks that uninhibited use of artificial intelligence poses to society. The question is not whether artificial intelligence will cause harm, but when, and how. The certainty of future harm necessitates that legal scholars and practitioners examine the liability implications of artificial intelligence. While this topic has been given increasing focus in the literature, such discussion is lacking in two key ways. First, there has been little attempt to consolidate the literature on the range of legal theories that might apply to harm resulting from the use of artificial intelligence. Second, the literature has failed to address the role that contracting may play in reducing uncertainty around liability and overriding common law approaches. This paper addresses both gaps in the literature and provides legal practitioners with an overview of key considerations related to liability allocation when contracting for artificial intelligence technology. Part I of the paper begins by briefly discussing the risks inherent in the use of artificial intelligence, including in particular risks resulting from a lack of transparency and explainability, and the harms that might result. Part II of the paper distills past legal scholarship on the legal theories that might apply when harm results from the use of artificial intelligence. The theories analyzed include vicarious liability, products liability and negligence. Relevant distinctions between artificial intelligence and software are discussed as they relate to the application of products liability and negligence theories in particular. Part II closes by highlighting that the current uncertainty in the legal landscape for artificial intelligence liability incentivizes contracting parties to address liability directly within their contracts. Part III of the paper then proceeds to provide an overview of important considerations for contracting parties when using contractual apportionment of liability to reduce uncertainty around harm resulting from the use of artificial intelligence. These considerations are organized by contracting phase and by relevant contracting section

Foreword

In their seminal 1890 article, The Right to Privacy, Samuel Warren and Louis Brandeis observed: Recent inventions and business methods call attention to the next step which must be taken for the protection of the person, and for securing to the individual what Judge Cooley calls the right “to be left alone.” Instantaneous photographs and newspaper enterprise have invaded the sacred precincts of private and domestic life; and numerous mechanical devices threaten to make good the prediction that “what is whispered in the closet shall be proclaimed from the housetops.” What is remarkable about this comment is that it could be applied with equal force to today’s world. Although the technologies are different—instant photographs and sensational tabloids have been replaced by Google Glass and tracking technologies—the impulse to “to be let alone” and the fear that “what is whispered in the closet shall be proclaimed from the housetops” remains relevant to today’s privacy concerns. In fact, perhaps the only constant in the modern era has been almost breathless sense of change, a sense that new and unpredictable developments are just around the corner, and that today’s way of dealing with things may not be up to tomorrow’s task. Nowhere is this more evidence than in the area of information and privacy, where technological changes have facilitated an exponential increase in our ability to communicate and to know. According to Eric Schmidt, the former CEO of Google, approximately five exabytes of information were created between the dawn of civilization and the year 2003. Today, the same amount of information is created in less that two days. Most of this data, according to Schmidt, is user generated—Facebook pages, text messages, blogs, etc. As our social relations are increasingly recorded and collected, the risk that information that we think we are “whispering in the closet” is in fact being “proclaimed from the rooftops” have only increased

Collage Vol. I

JUDY COCHRAN: Editorial MICHAEL TANGEMAN: Haikus 2-5 ELISE ALBRECHT, CURTIS PLOWGIAN: French Calligrams 6 JASON VARDEN: Waiting 7 ALEXANDER GREEN: Photo 8 EDUARDO JARAMILLO: Formas violentas 9-11 GABRIELE DILLMANN: Photo 12 MICHAEL GOLDSBERG: Funf fur Ashley 13 MEGAN CARLSON: Fur Jared (German) 14 MAGGIE GLOVER: For Jared 14-15 CHRIS FAUR: Painting 16 LINDSEY ESHELMAN: Stuhl (The Chair) 17 HALLE THOMPSON, GWENN DOBOS: Les Bouches 18 JILL BOO: Lacheln (A Smile) 19 ALEXANDER GREEN: Photo 20 JULIA GRAWEMEYER: Villanelle 21, Expressions francaises (French Figures) 22-23, Pour me rappeler (So that I\u27d remember) 24 MICHEL CLIQUET: Photo 25 CHARLES O\u27KEEFE: Photos 26-28 LINE LERYCKE: Photos 29-32 MICHEL CLIQUET: Pierre docile (Docile Stone) 29-32 LOGAN FAVIA: Ataraxia 33 AVRITA SINGH: Absence 34 RACHEL GROTHEER: Compassion 35, Ligne (Line) 36, Nuit, douce nuit (Night, gentle night) 37, Rouge (Red) 38, Bonjour Bleu (Hello Blue) 39, Ligne courbe (Curved Line) 40 AMELIA DUNLAP: Compassion 41-42 KYLE SIMPSON: Separation 43 ALEXANDER GREEN: Photo 44 GWENN DOBOS: Ataraxia 45 SARAH SLOTKIN: Separation 46 CURTIS PLOWGIAN: Absence 47 ELISA VER MERRIS: Photo 48, Attachement (Attachment) 49 JENNIFER JOHNSON: Attachement (Attachment)50 ANNA KELLY: Compassion 51 RICHARD BANAHAN: Photo 52, Mon grand-pere et moit (My grandfather and me) 53 MEREDITH KATZ: Separation 54 BRENDA HEATER: Compassion 55 ZACHARY WALSH: Ataraxia 56 MICHEL CLIQUET: Photos 57-5

DU Undergraduate Showcase: Research, Scholarship, and Creative Works: Abstracts

Abstracts from the DU Undergraduate Showcase

Opioid suppression of conditioned anticipatory brain responses to breathlessness

Opioid painkillers are a promising treatment for chronic breathlessness, but are associated with potentially fatal side effects. In the treatment of breathlessness, their mechanisms of action are unclear. A better understanding might help to identify safer alternatives. Learned associations between previously neutral stimuli (e.g. stairs) and repeated breathlessness induce an anticipatory threat response that may worsen breathlessness, contributing to the downward spiral of decline seen in clinical populations. As opioids are known to influence associative learning, we hypothesized that they may interfere with the brain processes underlying a conditioned anticipatory response to breathlessness in relevant brain areas, including the amygdala and the hippocampus. Healthy volunteers viewed visual cues (neutral stimuli) immediately before induction of experimental breathlessness with inspiratory resistive loading. Thus, an association was formed between the cue and breathlessness. Subsequently, this paradigm was repeated in two identical neuroimaging sessions with intravenous infusions of either low-dose remifentanil (0.7ng/ml target controlled infusion) or saline (randomised). During saline infusion, breathlessness anticipation activated the right anterior insula and the adjacent operculum. Breathlessness was associated with activity in a network including the insula, operculum, dorsolateral prefrontal cortex, anterior cingulate cortex and the primary sensory and motor cortices. Remifentanil reduced breathlessness unpleasantness but not breathlessness intensity. Remifentanil depressed anticipatory activity in the amygdala and the hippocampus that correlated with reductions in breathlessness unpleasantness. During breathlessness, remifentanil decreased activity in the anterior insula, anterior cingulate cortex and sensory motor cortices. Remifentanil-induced reduction in breathlessness unpleasantness was associated with increased activity in the rostral anterior cingulate cortex and nucleus accumbens, components of the endogenous opioid system known to decrease the perception of aversive stimuli. These findings suggest that in addition to effects on brainstem respiratory control, opioids palliate breathlessness through an interplay of altered associative learning mechanisms. These mechanisms provide potential targets for novel ways to develop and assess treatments for chronic breathlessness

Self-Regulation of Amygdala Activation Using Real-Time fMRI Neurofeedback

Real-time functional magnetic resonance imaging (rtfMRI) with neurofeedback allows investigation of human brain neuroplastic changes that arise as subjects learn to modulate neurophysiological function using real-time feedback regarding their own hemodynamic responses to stimuli. We investigated the feasibility of training healthy humans to self-regulate the hemodynamic activity of the amygdala, which plays major roles in emotional processing. Participants in the experimental group were provided with ongoing information about the blood oxygen level dependent (BOLD) activity in the left amygdala (LA) and were instructed to raise the BOLD rtfMRI signal by contemplating positive autobiographical memories. A control group was assigned the same task but was instead provided with sham feedback from the left horizontal segment of the intraparietal sulcus (HIPS) region. In the LA, we found a significant BOLD signal increase due to rtfMRI neurofeedback training in the experimental group versus the control group. This effect persisted during the Transfer run without neurofeedback. For the individual subjects in the experimental group the training effect on the LA BOLD activity correlated inversely with scores on the Difficulty Identifying Feelings subscale of the Toronto Alexithymia Scale. The whole brain data analysis revealed significant differences for Happy Memories versus Rest condition between the experimental and control groups. Functional connectivity analysis of the amygdala network revealed significant widespread correlations in a fronto-temporo-limbic network. Additionally, we identified six regions — right medial frontal polar cortex, bilateral dorsomedial prefrontal cortex, left anterior cingulate cortex, and bilateral superior frontal gyrus — where the functional connectivity with the LA increased significantly across the rtfMRI neurofeedback runs and the Transfer run. The findings demonstrate that healthy subjects can learn to regulate their amygdala activation using rtfMRI neurofeedback, suggesting possible applications of rtfMRI neurofeedback training in the treatment of patients with neuropsychiatric disorders

A dose- rather than delivery profile-dependent mechanism regulates the "muscle-full" effect in response to oral essential amino acid intake in young men

Background: The anabolic response of skeletal muscle to essential amino acids (EAAs) is dose dependent, maximal at modest doses, and short lived, even with continued EAA availability, a phenomenon termed “muscle-full.” However, the effect of EAA ingestion profile on muscle metabolism remains undefined.Objective: We determined the effect of Bolus vs. Spread EAA feeding in young men and hypothesized that muscle-full is regulated by a dose-, not delivery profile–, dependent mechanism.Methods: We provided 16 young healthy men with 15 g mixed-EAA, either as a single dose (“Bolus”; n = 8) or in 4 fractions at 45-min intervals (“Spread”; n = 8). Plasma insulin and EAA concentrations were assayed by ELISA and ion-exchange chromatography, respectively. Limb blood flow by was determined by Doppler ultrasound, muscle microvascular flow by Sonovue (Bracco) contrast-enhanced ultrasound, and phosphorylation of mammalian target of rapamycin complex 1 substrates by immunoblotting. Intermittent muscle biopsies were taken to quantify myofibrillar-bound 13C6-phenylalanine to determine muscle protein synthesis (MPS).Results: Bolus feeding achieved rapid insulinemia (13.6 μIU · mL−1, 25 min after commencement of feeding), aminoacidemia (∼2500 μM at 45 min), and capillary recruitment (+45% at 45 min), whereas Spread feeding achieved attenuated insulin responses, gradual low-amplitude aminoacidemia (peak: ∼1500 μM at 135 min), and no detectable capillary recruitment (all P < 0.01 vs. Bolus). Despite these differences, identical anabolic responses were observed; fasting fractional synthetic rates of 0.054% · h−1 (Bolus) and 0.066% · h−1 (Spread) increased to 0.095% and 0.104% · h−1 (no difference in increment or final values between regimens). With both Spread and Bolus feeding strategies, a latency of at least 90 min was observed before an upswing in MPS was evident. Similarly with both feeding strategies, MPS returned to fasting rates by 180 min despite elevated circulating EAAs.Conclusion: These data do not support EAA delivery profile as an important determinant of anabolism in young men at rest, nor rapid aminoacidemia/leucinemia as being a key factor in maximizing MPS. This trial was registered at clinicaltrials.gov as NCT01735539

Relationship-scale Conservation

Conservation can occur anywhere regardless of scale, political jurisdiction, or landownership. We present a framework to help managers at protected areas practice conservation at the scale of relationships. We focus on relationships between stakeholders and protected areas and between managers and other stakeholders. We provide a synthesis of key natural resources literature and present a case example to support our premise and recommendations. The purpose is 4-fold: 1) discuss challenges and threats to conservation and protected areas; 2) outline a relationship-scale approach to address conservation threats; 3) describe the tools and techniques that can be used to implement this approach; and 4) present a case example from rural Alaska, USA, to illustrate relationship-scale conservation. Our case example illustrates how aspects of this approach to conservation were applied to address a wildlife population decline. Tools needed to implement relationship-scale conservation include 1) collecting and documenting narratives of place; 2) measuring and monitoring trust and commitment; and 3) identifying and mitigating threats. We recommend that planners and managers, working with their research partners, redefine and refocus their goals and objectives to include these practices. Doing so will enable them to gain substantial applied knowledge about their stakeholders and foster and maintain place relationships as desired outcomes of conservation. The ultimate outcome is a better prognosis for long-term global survival of protected areas and biodiversity. Published 2014. This article is a U.S. Government work and is in the public domain in the USA

Pathway-based predictive approaches for non-animal assessment of acute inhalation toxicity

New approaches are needed to assess the effects of inhaled substances on human health. These approaches will be based on mechanisms of toxicity, an understanding of dosimetry, and the use of in silico modeling and in vitro test methods. In order to accelerate wider implementation of such approaches, development of adverse outcome pathways (AOPs) can help identify and address gaps in our understanding of relevant parameters for model input and mechanisms, and optimize non-animal approaches that can be used to investigate key events of toxicity. This paper describes the AOPs and the toolbox of in vitro and in silico models that can be used to assess the key events leading to toxicity following inhalation exposure. Because the optimal testing strategy will vary depending on the substance of interest, here we present a decision tree approach to identify an appropriate non-animal integrated testing strategy that incorporates consideration of a substance's physicochemical properties, relevant mechanisms of toxicity, and available in silico models and in vitro test methods. This decision tree can facilitate standardization of the testing approaches. Case study examples are presented to provide a basis for proof-of-concept testing to illustrate the utility of non-animal approaches to inform hazard identification and risk assessment of humans exposed to inhaled substances