Antitrust by Algorithm

Technological innovation is changing private markets around the world. New advances in digital technology have created new opportunities for subtle and evasive forms of anticompetitive behavior by private firms. But some of these same technological advances could also help antitrust regulators improve their performance in detecting and responding to unlawful private conduct. We foresee that the growing digital complexity of the marketplace will necessitate that antitrust authorities increasingly rely on machine-learning algorithms to oversee market behavior. In making this transition, authorities will need to meet several key institutional challenges—building organizational capacity, avoiding legal pitfalls, and establishing public trust—to ensure successful implementation of antitrust by algorithm

Assessing Automated Administration

To fulfill their responsibilities, governments rely on administrators and employees who, simply because they are human, are prone to individual and group decision-making errors. These errors have at times produced both major tragedies and minor inefficiencies. One potential strategy for overcoming cognitive limitations and group fallibilities is to invest in artificial intelligence (AI) tools that allow for the automation of governmental tasks, thereby reducing reliance on human decision-making. Yet as much as AI tools show promise for improving public administration, automation itself can fail or can generate controversy. Public administrators face the question of when exactly they should use automation. This paper considers the justifications for governmental reliance on AI along with the legal concerns raised by such reliance. Comparing AI-driven automation with a status quo that relies on human decision-making, the paper provides public administrators with guidance for making decisions about AI use. After explaining why prevailing legal doctrines present no intrinsic obstacle to governmental use of AI, the paper presents considerations for administrators to use in choosing when and how to automate existing processes. It recommends that administrators ask whether their contemplated uses meet the preconditions for the deployment of AI tools and whether these tools are in fact likely to outperform the status quo. In moving forward, administrators should also consider the possibility that a contemplated AI use will generate public or legal controversy, and then plan accordingly. The promise and legality of automated administration ultimately depends on making responsible decisions about when and how to deploy this technology

Algorithm vs. Algorithm

Critics raise alarm bells about governmental use of digital algorithms, charging that they are too complex, inscrutable, and prone to bias. A realistic assessment of digital algorithms, though, must acknowledge that government is already driven by algorithms of arguably greater complexity and potential for abuse: the algorithms implicit in human decision-making. The human brain operates algorithmically through complex neural networks. And when humans make collective decisions, they operate via algorithms too—those reflected in legislative, judicial, and administrative processes. Yet these human algorithms undeniably fail and are far from transparent. On an individual level, human decision-making suffers from memory limitations, fatigue, cognitive biases, and racial prejudices, among other problems. On an organizational level, humans succumb to groupthink and free-riding, along with other collective dysfunctionalities. As a result, human decisions will in some cases prove far more problematic than their digital counterparts. Digital algorithms, such as machine learning, can improve governmental performance by facilitating outcomes that are more accurate, timely, and consistent. Still, when deciding whether to deploy digital algorithms to perform tasks currently completed by humans, public officials should proceed with care on a case-by-case basis. They should consider both whether a particular use would satisfy the basic preconditions for successful machine learning and whether it would in fact lead to demonstrable improvements over the status quo. The question about the future of public administration is not whether digital algorithms are perfect. Rather, it is a question about what will work better: human algorithms or digital ones

Thrifty Viability and Traditional Mortgage Lending: A Simultaneous Equations Analysis of the Risk-Return Trade-Off

A number of studies have argued that the thrift industry is not viable as it is presently structured and regulated because mortgage yields are inadequate to cover interest and operating costs. This hypothesis suggests that observed profitability is primarily the result of the tendency of the industry to "ride" the yield curve by borrowing short and lending long. To evaluate this argument, we construct a simultaneous-equations model of thrift risk (maturity gap positions) and return (net interest margin). We find support for the notion that the industry could not be reasonably profitable if it did not take on significant interest-rate risk. For instance, a zero gap position produces a return on assets of only 19 basis points and a return on equity of only 4%. We also estimate the amount of interest-rate risk the industry can employ to increase returns on equity and assets. Our estimates show that over 50% of thrift profits earned during this period are the result of negative gap positions and interest-rate speculation. As earlier research shows, changes in regulations affecting thrift asset and liability choices can be counterproductive.

Two Purified Domains of Telomerase Reverse Transcriptase Reconstitute Sequence-Specific Interactions with RNA

Telomerase reverse transcriptase (TERT) and telomerase RNA (TER) function together to create a uniquely specialized polymerase. Here we have described for the first time domains of bacterially expressed Tetrahymena TERT that interacted directly with TER in the absence of assembly chaperones. We used quantitative binding assays to define TER sequence requirements for recognition by the high affinity RNA binding domain and an independent N-terminal RNA interaction domain. The TERT RNA binding domain and N-terminal RNA interaction domain had distinct, nonoverlapping requirements for TER sequence and structure that together accounted for all of the sites of TER contact inferred for full-length TERT. The TER residues important for TERT binding are only a subset of the residues required for catalytic activity. Our findings demonstrate telomerase functional specialization by an elaborate ribonucleoprotein architecture physically separable from the active site

Exploring the relationship between HRM and firm performance: A meta-analysis of longitudinal studies

Existing literature on human resource management (HRM) practices and firm performance suggests that there is a positive association between the two variables. Most of the studies, however, are based on cross-sectional datasets and only few of them use panel or longitudinal datasets, which better allow the researchers to deal with problems of endogeneity. This paper draws on meta-analysis techniques to estimate the effect size of the relationship between high performance work practices (HPWPs) and firm performance measures based on the available longitudinal studies. We also examine whether the effect is greater for a combination of HPWPs than for individual HPWPs, and for operational performance than for financial performance. The results from statistical aggregation of eight longitudinal HRM-performance studies demonstrate an overall reported correlation of 0.287. Additionally we find that a set of integrated, mutually reinforcing HPWPs has a stronger impact on firm performance than do HRM practices individually and that, this effect is statistically invariant between operational performance and financial performance

Cross-Phosphorylation, Signaling and Proliferative Functions of the Tyro3 and Axl Receptors in Rat2 Cells

The dysregulation of receptor protein tyrosine kinase (RPTK) function can result in changes in cell proliferation, cell growth and metastasis leading to malignant transformation. Among RPTKs, the TAM receptor family composed of three members Tyro3, Axl, and Mer has been recognized to have a prominent role in cell transformation. In this study we analyzed the consequences of Tyro3 overexpression on cell proliferation, activation of signaling pathways and its functional interactions with Axl. Overexpression of Tyro3 in the Rat2 cell line that expresses Axl, but not Mer or Tyro3, resulted in a 5 fold increase in cell proliferation. This increase was partially blocked by inhibitors of the mitogen-activated protein kinase (MAPK) signaling pathway but not by inhibitors of the phosphatidylinositol 3-kinase (PI(3)K) signaling pathway. Consistent with these findings, an increase in ERK1/2 phosphorylation was detected with Tyro3 but not with Axl overexpression. In contrast, activation of Axl stimulated the PI(3)K pathway, which was mitigated by co-expression of Tyro3. The overexpression of Tyro3 enhanced Gas6-mediated Axl phosphorylation, which was not detected upon overexpression of a “kinase dead” form of Tyro3 (kdTyro3). In addition, the overexpression of Axl induced kdTyro3 phosphorylation. Co-immunoprecipitation experiments confirmed that the Axl and Tyro3 receptors are closely associated. These findings show that overexpression of Tyro3 in the presence of Axl promotes cell proliferation, and that co-expression of Axl and Tyro3 can affect the outcome of Gas6-initiated signaling. Furthermore, they demonstrate a functional interaction between the members of the TAM receptor family which can shed light on the molecular mechanisms underlying the functional consequences of TAM receptor activation in cell transformation, neural function, immune function, and reproductive function among others

Novel and Known Protein Tyrosine Kinases and Their Abnormal Expression in Human Melanoma

We have used the polymerase chain reaction and Northern blotting to identify protein tyrosine kinases that may play an an important role in the process of melanoma initiation and progression. Degenerate primers from the conserved catalytic domain of tyrosine kinase genes were used to amplify and clone partial cDNA sequences from a human melanoma cell line (DX3-LT5.1) and normal human melanocytes. When the melanoma reaction products were sequenced, 13 distinct clones were found, of which one is novel to date and has provisionally been named MEK (for melanocytic kinase). Of the remaining 12 known kinases, only two, ERB-B2 and IGFI-1-R, have previously been reported in pigment cells. Reaction products from melanocytes included only eight of these 13 sequences. To test for quantitative differences in tyrosine kinase expression between normal and malignant cells, a panel of eight melanoma lines and normal melanocytes was analyzed by Northern blotting. Two tyrosine kinases (JTK-14/TIE and TYRO-9) were detected in some melanomas but were not found in normal melanocytes, whereas others, including MEK, appeared to be overexpressed in some malignant lines. A minority of kinases showed either no change or a reduction in the level of mRNA. Expression of tyrosine kinases varied independently, and individual lines contained various combinations of these enzymes. Our findings are consistent with an increased overall expression of these putative growth factor receptors during melanoma development

Controlling chaos in area-preserving maps

We describe a method of control of chaos that occurs in area-preserving maps. This method is based on small modifications of the original map by addition of a small control term. We apply this control technique to the standard map and to the tokamap

Targeting Pyk2 to β1-Integrin–Containing Focal Contacts Rescues Fibronectin-Stimulated Signaling and Haptotactic Motility Defects of Focal Adhesion Kinase–Null Cells

Focal adhesion kinase–null (FAK−/−) fibroblasts exhibit morphological and motility defects that are reversed by focal adhesion kinase (FAK) reexpression. The FAK-related kinase, proline-rich tyrosine kinase 2 (Pyk2), is expressed in FAK−/− cells, yet it exhibits a perinuclear distribution and does not functionally substitute for FAK. Chimeric Pyk2/FAK proteins were created and expressed in FAK−/− cells to determine the impact of Pyk2 localization to focal contacts. Whereas an FAK/Pyk2 COOH-terminal (CT) domain chimera was perinuclear distributed, stable expression of a Pyk2 chimera with the FAK-CT domain (Pyk2/FAK-CT) localized to focal contact sites and enhanced fibronectin (FN)-stimulated haptotactic cell migration equal to FAK-reconstituted cells. Disruption of paxillin binding to the FAK-CT domain (S-1034) inhibited Pyk2/FAK-CT localization to focal contacts and its capacity to promote cell motility. Paxillin binding to the FAK-CT was necessary but not sufficient to mediate the indirect association of FAK or Pyk2/FAK-CT with a β1-integrin–containing complex. Both FAK and Pyk2/FAK-CT but not Pyk2/FAK-CT S-1034 reconstituted FAK−/− cells, exhibit elevated FN-stimulated extracellular signal–regulated kinase 2 (ERK2) and c-Jun NH2-terminal kinase (JNK) kinase activation. FN-stimulated FAK or Pyk2/FAK-CT activation enhanced both the extent and duration of FN-stimulated ERK2 activity which was necessary for cell motility. Transient overexpression of the FAK-CT but not FAK-CT S-1034 domain inhibited both FN-stimulated ERK2 and JNK activation as well as FN-stimulated motility of Pyk2/FAK-CT reconstituted cells. These gain-of-function studies show that the NH2-terminal and kinase domains of Pyk2 can functionally substitute for FAK in promoting FN-stimulated signaling and motility events when localized to β-integrin–containing focal contact sites via interactions mediated by the FAK-CT domain