Artificial Intelligence and Technology in Teaching Negotiation

Artificial intelligence (AI), machine learning (ML), affective computing, and big‐data techniques are improving the ways that humans negotiate and learn to negotiate. These technologies, long deployed in industry and academic research, are now being adopted for educational use. We describe several systems that help human negotiators evaluate and learn from role‐play simulations as well as applications that help human instructors teach negotiators at the individual, team, and organizational levels. AI can enable the personalization of negotiation instruction, taking into consideration factors such as culture and bias. These tools will enable improvements not only in the teaching of negotiation, but also in teaching humans how to program and collaborate with technology‐based negotiation systems, including avatars and computer‐controlled negotiation agents. These advances will provide theoretical and practical insights, require serious consideration of ethical issues, and revolutionize the way we practice and teach negotiation.     

Muscle contraction during electro-muscular incapacitation: A comparison between square-wave pulses and the TASER(®) X26 Electronic control device

Abstract: Electronic control devices (including the Advanced TASER^® X26 model produced by TASER International) incapacitate individuals by causing muscle contractions. To provide information relevant to development of future potential devices, effects of monophasic square waves with different parameters were compared with those of the X26 electronic control device, using two animal models (frogs and swine). Pulse power, electrical pulse charge, pulse duration, and pulse repetition frequency affected muscle contraction. There was no difference in the charge required, between the square waveform and the X26 waveform, to cause approximately the same muscle‐contraction response (in terms of the strength‐duration curve). Thus, on the basis of these initial studies, the detailed shape of a waveform may not be important in terms of generating electro‐muscular incapacitation. More detailed studies, however, may be required to thoroughly test all potential waveforms to be considered for future use in ECDs.     

Factors Affecting Individuals' Decisions to Use Community Mediation

This article presents research related to community mediation, specifically the factors affecting individuals' choices to accept or decline participation in the mediation process. Alongside a growing literature that emphasizes the significant benefits of mediation, this empirical study finds that individuals involved in personal relationships are more likely than individuals involved in business relationships to choose mediation. This data also finds a nonlinear and significant relationship between the length of time a conflict has been going on and participants' choice to use mediation. Finally, this article finds a significant and nonlinear relationship between differences in perception about the length of a conflict and whether a case is scheduled for mediation. Policy recommendations include suggestions to increase the use of mediation by responding directly to the cases that do not seem as likely to be mediated.     

Differentiating cause-of-death terminology for deaths coded as sudden infant death syndrome, accidental suffocation, and unknown cause: an investigation using US death certificates, 2003-2004

We compared written text on infant death certificates for deaths coded as sudden infant death syndrome (R95), unknown cause (R99), and accidental suffocation (W75). Using US mortality files supplemented with the death certifiers' written text for all infant deaths with International Classification of Diseases (ICD)-10 assigned codes R95, R99, and W75, we formed cause-of-death subcategories from common themes identified from the written text. Among all infant deaths in 2003-2004, the underlying cause of death was listed as R99 for 2128 deaths, R95 for 4408 deaths, and W75 for 931 deaths. Among the postneonatal deaths, the differences in subcategories varied between assigned ICD-10 codes: for R99-coded deaths, 45.8% were categorized as "Unknown" and 48.6% as "Pending"; for R95-coded deaths, 67.7% were categorized as "sudden infant death syndrome (SIDS)"; and for W75-coded deaths, 76.4% were categorized as "Suffocation." Examination of the written text on the death certificates demonstrates variability in the assigned ICD-10 codes which could have an important effect on the estimates of SIDS cases in the United States.