3,796 research outputs found

    An Unreasonable Ban on Reasonable Competition: The Legal Professionā€™s Protectionist Stance Against Noncompete Agreements Binding In-House Counsel

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    In the vast majority of jurisdictions in the United States, a business may protect its confidential information and customer goodwill by conditioning employment on an employeeā€™s acceptance of a covenant not to compete. These covenants are beneficial to the marketplace because they allow employers to provide employees with necessary skills, knowledge, and proprietary information without any fear of misappropriation. Accordingly, noncompete agreements are upheld by courts so long as they pass a fact-specific ā€œreasonablenessā€ test. Notwithstanding the widespread acceptance of reasonable noncompete agreements for all other professionalsā€”including doctors and corporate executivesā€”forty-eight states, following the American Bar Associationā€™s lead, prohibit all noncompete agreements among lawyers. This prohibition is purportedly designed to protect both an attorneyā€™s professional autonomy and a clientā€™s right to choose his counsel. Despite legal commentatorsā€™ criticism of the prohibition, several state bar associations have recently extended it beyond the traditional law-firm context to agreements between companies and their in-house counsel. This expansion has transformed a questionable policy of professional self-regulation into an unjustifiable infringement on the legitimate interests of corporate employers. In addition to providing an analysis of the history and ethical norms that justify rejection of the banā€™s application to in-house counsel, this Note argues that bar committees that issue opinions supporting the banā€™s extension may be susceptible to antitrust liability under the Supreme Courtā€™s new Dental Board standard pertaining to state-action immunity

    A Utility-Theoretic Approach to Privacy in Online Services

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    Online offerings such as web search, news portals, and e-commerce applications face the challenge of providing high-quality service to a large, heterogeneous user base. Recent efforts have highlighted the potential to improve performance by introducing methods to personalize services based on special knowledge about users and their context. For example, a user's demographics, location, and past search and browsing may be useful in enhancing the results offered in response to web search queries. However, reasonable concerns about privacy by both users, providers, and government agencies acting on behalf of citizens, may limit access by services to such information. We introduce and explore an economics of privacy in personalization, where people can opt to share personal information, in a standing or on-demand manner, in return for expected enhancements in the quality of an online service. We focus on the example of web search and formulate realistic objective functions for search efficacy and privacy. We demonstrate how we can find a provably near-optimal optimization of the utility-privacy tradeoff in an efficient manner. We evaluate our methodology on data drawn from a log of the search activity of volunteer participants. We separately assess usersā€™ preferences about privacy and utility via a large-scale survey, aimed at eliciting preferences about peoplesā€™ willingness to trade the sharing of personal data in returns for gains in search efficiency. We show that a significant level of personalization can be achieved using a relatively small amount of information about users
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