Platforms, Power, and the Antitrust Challenge: A Modest Proposal to Narrow the U.S.-Europe Divide

Big platforms dominate the new economy landscape. Colloquially known as GAFA [Google, Amazon, Facebook, and Apple] or FAANG [Facebook, Amazon, Apple, Netflix, and Google], the high tech big data companies are charged with using the power of their platforms to squelch start-ups, appropriate rivals’ ideas, and take and commercialize the personal data of their users. Are the platforms violating the antitrust laws? Should they be broken up? Or are they the agents of progress in the new economy? On these points, the United States antitrust law and the European Union competition law may diverge. The Competition Directorate-General of the European Commission has brought proceedings against or is investigating Google, Amazon, Apple, and Facebook. Germany, under its own competition law, has condemned Facebook’s conduct. Meanwhile, in the United States, authorities are skeptical, but they have commenced investigations. This Article is a comparative analysis of U.S. and EU law regarding monopolization/abuse of dominance as background to understanding why EU law is aggressive and U.S. law may be meek in the treatment of the big tech platforms. First, it examines the factors that underlie the two perspectives. Second, it considers three cases or problems—Google/Comparative Shopping (EU), Facebook-Personal Data (Germany), and dominant platforms’ acquisitions of start-ups that are inchoate competitive threats, such as Facebook’s acquisitions of WhatsApp and Instagram. The Article considers what lessons the latest Supreme Court antitrust decision, Ohio v. American Express (AmEx), holds for the analysis of the big data antitrust issues. Third, it asks what U.S. antitrust law and enforcement should do. It concludes that U.S. antitrust law should reclaim its role as watchdog to stop abuses of economic power, and makes suggestions for U.S. antitrust law to meet the big-platform challenge in a modest but meaningful and practicable way. I. Introduction II. A Brief Comparison of U.S. and EU Law of Monopolization/Abuse of Dominance ... A. The United States ... B. Europe ... C. Presumptions and Divergences III. Implications for High Tech, Big Data IV. Three Examples of Alleged Platform Abuse ... A. Google/Comparative Shopping ... 1. EU Law ... 2. U.S. Law ... B. Facebook—Abuse of Data ... 1. German Law ... 2. U.S. Law ... C. Start-Ups: Nipping Competition in the Bud V. Proposals VI. Conclusio

Presidential Address: The Aquatic Plant Management Society and Our Future Sphere of Influence

Presidential address of Alison M. Fo

Converging Horror: analyzing the importance of Convergence Culture on a digital audience through an examination of the conventions and politics of the horror genre

This thesis draws attention to the genre of horror in new media through a close examination of various digital texts, arguing that these new texts, while built on traditional horror narratives used in cinema, are also examples of Convergence Culture, a mobile, multiplatform, participatory medium that engages professionals and amateur content creators. The thesis begins with a review of scholarly work about horror as a genre, continues with a close analysis of several digital horror texts and their online communities, and ends with the argument that these new texts are good examples of how horror has accommodated Convergence culture, morphing into a post-national space characterized by mobility, transnationalism and participation. And most importantly, this new iteration of horror continues the classical horror film tradition of mirroring inter-personal and cultural anxieties

The Dirichet-Multinomial model for multivariate randomized response data and small samples

In survey sampling the randomized response (RR) technique can be used to obtain truthful answers to sensitive questions. Although the individual answers are masked due to the RR technique, individual (sensitive) response rates can be estimated when observing multivariate response data. The beta-binomial model for binary RR data will be generalized to handle multivariate categorical RR data. The Dirichlet-multinomial model for categorical RR data is extended with a linear transformation of the masked individual categorical-response rates to correct for the RR design and to retrieve the sensitive categorical-response rates even for small data samples. This specification of the Dirichlet-multinomial model enables a straightforward empirical Bayes estimation of the model parameters. A constrained-Dirichlet prior will be introduced to identify homogeneity restrictions in response rates across persons and/or categories. The performance of the full Bayes parameter estimation method is verified using simulated data. The proposed model will be applied to the college alcohol problem scale study, where students were interviewed directly or interviewed via the randomized response technique about negative consequences from drinking. (Contains 5 tables.

Person-centred advocacy for people with dementia - a personal account

In the first of two articles on advocacy for people with dementia, Mike Fox and Lesley Wilson describe an advocacy project based in a residential home and consider the issues and themes that arose

Person-centred advocacy: Some ethical issues

In the second of two articles on advocacy for people with dementia Mike Fox with Lesley Wilson considers some of the ethical issues arising from advocacy work within a residential home that was due to close

PDDL2.1: An extension of PDDL for expressing temporal planning domains

In recent years research in the planning community has moved increasingly towards application of planners to realistic problems involving both time and many types of resources. For example, interest in planning demonstrated by the space research community has inspired work in observation scheduling, planetary rover ex ploration and spacecraft control domains. Other temporal and resource-intensive domains including logistics planning, plant control and manufacturing have also helped to focus the community on the modelling and reasoning issues that must be confronted to make planning technology meet the challenges of application. The International Planning Competitions have acted as an important motivating force behind the progress that has been made in planning since 1998. The third competition (held in 2002) set the planning community the challenge of handling time and numeric resources. This necessitated the development of a modelling language capable of expressing temporal and numeric properties of planning domains. In this paper we describe the language, PDDL2.1, that was used in the competition. We describe the syntax of the language, its formal semantics and the validation of concurrent plans. We observe that PDDL2.1 has considerable modelling power --- exceeding the capabilities of current planning technology --- and presents a number of important challenges to the research community

The Automatic Inference of State Invariants in TIM

As planning is applied to larger and richer domains the effort involved in constructing domain descriptions increases and becomes a significant burden on the human application designer. If general planners are to be applied successfully to large and complex domains it is necessary to provide the domain designer with some assistance in building correctly encoded domains. One way of doing this is to provide domain-independent techniques for extracting, from a domain description, knowledge that is implicit in that description and that can assist domain designers in debugging domain descriptions. This knowledge can also be exploited to improve the performance of planners: several researchers have explored the potential of state invariants in speeding up the performance of domain-independent planners. In this paper we describe a process by which state invariants can be extracted from the automatically inferred type structure of a domain. These techniques are being developed for exploitation by STAN, a Graphplan based planner that employs state analysis techniques to enhance its performance