A more general Pandora rule?

This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.jet.2015.10.009In a model introduced by Weitzman an agent called Pandora opens boxes sequentially, in whatever order she likes, discovers prizes within, and optimally stops. Her aim is to maximize the expected value of the greatest discovered prize, minus the costs of opening the boxes. The solution, using the so-called Pandora rule, is attractive and has many applications. However, it does not address applications in which the payoff depends on all discovered prizes, rather than just the best of them, nor is it easy to say whether or not some generalized Pandora rule might do so. Here, we establish a sense in which it cannot. We discover that if a generalized Pandora rule is to be optimal for some more general utility, and all model parameters, then the problem can be solved via a second problem having Weitzman's form of utility

APIs and Your Privacy

Application programming interfaces, or APIs, have been the topic of much recent discussion. Newsworthy events, including those involving Facebook’s API and Cambridge Analytica obtaining information about millions of Facebook users, have highlighted the technical capabilities of APIs for prominent websites and mobile applications. At the same time, media coverage of ways that APIs have been misused has sparked concern for potential privacy invasions and other issues of public policy. This paper seeks to educate consumers on how APIs work and how they are used within popular websites and mobile apps to gather, share, and utilize data. APIs are used in mobile games, search engines, social media platforms, news and shopping websites, video and music streaming services, dating apps, and mobile payment systems. If a third-party company, like an app developer or advertiser, would like to gain access to your information through a website you visit or a mobile app or online service you use, what data might they obtain about you through APIs and how? This report analyzes 11 prominent online services to observe general trends and provide you an overview of the role APIs play in collecting and distributing information about consumers. For example, how might your data be gathered and shared when using your Facebook account login to sign up for Venmo or to access the Tinder dating app? How might advertisers use Pandora’s API when you are streaming music? After explaining what APIs are and how they work, this report categorizes and characterizes different kinds of APIs that companies offer to web and app developers. Services may offer content-focused APIs, feature APIs, unofficial APIs, and analytics APIs that developers of other apps and websites may access and use in different ways. Likewise, advertisers can use APIs to target a desired subset of a service’s users and possibly extract user data. This report explains how websites and apps can create user profiles based on your online behavior and generate revenue from advertiser-access to their APIs. The report concludes with observations on how various companies and platforms connecting through APIs may be able to learn information about you and aggregate it with your personal data from other sources when you are browsing the internet or using different apps on your smartphone or tablet. While the paper does not make policy recommendations, it demonstrates the importance of approaching consumer privacy from a broad perspective that includes first parties and third parties, and that considers the integral role of APIs in today’s online ecosystem

Money for Something: Music Licensing in the 21st Century

[Excerpt] The laws that determine who pays whom in the digital world were written, by and large, at a time when music was primarily performed via radio broadcasts or distributed through physical media (such as sheet music and phonograph records), and when each of these forms of music delivery represented a distinct channel with unique characteristics. With the emergence of the Internet, Congress updated some copyright laws in the 1990s. It applied one set of legal provisions to digital services it viewed as akin to radio broadcasts and another set to digital services it viewed as akin to physical media. Since that time consumers have increasingly been consuming music via digital services that incorporate attributes of both radio and physical media. However, companies that compete in enabling consumers to access music may face very different costs to license music, depending on the technology they use and the features they offer. These differences in technology and features also affect the amount of money received by songwriters, performers, music publishers, and record companies. U.S. copyright law allows performers and record labels to collectively designate an agent to receive payments and to negotiate the licensing fees that certain types of digital music services must pay to stream music to their customers. Groups representing public radio and educational stations reached voluntary agreements with the agent, SoundExchange, in 2015. Rates paid by parties that do not reach voluntary agreements with SoundExchange during a limited negotiation period are instead set by the Copyright Royalty Board (CRB), a panel of three judges appointed by the Librarian of Congress. On December 16, 2015, the CRB set rates for online music streaming services for the period 2016 through 2020. For nonsubscription services, the CRB reduced the per-stream rate it had set in the previous rate proceeding, but the costs paid by several “small” music streaming services are likely to increase. Advocates of the small streaming services have launched a petition asking Congress to either allow their previous agreements to continue indefinitely or discontinue the requirement that small streaming services pay royalties to performers and record labels. SoundExchange has objected that the rates set by the CRB do not provide adequate compensation to performers and record labels. Members have introduced several bills in the 114th Congress that would change the amounts various participants in the music industry pay or receive in royalties. These bills are controversial, as they could alter the cost structures and revenues of broadcast radio stations, songwriters, performers, and others at a time when the music industry’s overall revenues are not growing. At the same time, the U.S. Department of Justice (DOJ) is continuing a review of consent decrees it entered into with music publishers in the 1940s. The outcome could affect the extent to which songwriters can control the use of their works

“It’s Been a Hard Day’s Night” for Songwriters: Why the ASCAP and BMI Consent Decrees Must Undergo Reform

In order to guarantee reasonable fees for songwriters, composers, and publishers, the consent decrees must undergo critical reform to account for how music is licensed in new media. Part I of this Note will provide background on the mechanics of music licensing, both traditional and through modern mediums, in order to explain why the two largest PROs initially entered into governmental consent decrees. Part II will discuss recent judicial determinations of “reasonable” licensing rates for public performances in new media and demonstrate the discrepancy in compensation between songwriters and their sound recording counterparts, namely record companies and recording artists. Finally, Part III will argue that the solution to this problem is through consent decree reform. The decrees should be modified to allow songwriters to withdraw their digital rights in order to separately license songs in new media. A new PRO should then emerge in the market place to account solely for public performance rights in new media, leaving traditional licensing to the existing PROs. Additionally, the current judicial process for setting rates, known as the “rate court” system, should be replaced with expedited, binding arbitration. Making these important changes to the music-licensing system will work towards bridging the gap in compensation inequality between songwriters and recording artists

Towards Accountable AI: Hybrid Human-Machine Analyses for Characterizing System Failure

As machine learning systems move from computer-science laboratories into the open world, their accountability becomes a high priority problem. Accountability requires deep understanding of system behavior and its failures. Current evaluation methods such as single-score error metrics and confusion matrices provide aggregate views of system performance that hide important shortcomings. Understanding details about failures is important for identifying pathways for refinement, communicating the reliability of systems in different settings, and for specifying appropriate human oversight and engagement. Characterization of failures and shortcomings is particularly complex for systems composed of multiple machine learned components. For such systems, existing evaluation methods have limited expressiveness in describing and explaining the relationship among input content, the internal states of system components, and final output quality. We present Pandora, a set of hybrid human-machine methods and tools for describing and explaining system failures. Pandora leverages both human and system-generated observations to summarize conditions of system malfunction with respect to the input content and system architecture. We share results of a case study with a machine learning pipeline for image captioning that show how detailed performance views can be beneficial for analysis and debugging

The development of a rich multimedia training environment for crisis management: using emotional affect to enhance learning

PANDORA is an EU FP7-funded project developing a novel training and learning environment for Gold Commanders, individuals who carry executive responsibility for the services and facilities identified as strategically critical e.g. Police, Fire, in crisis management strategic planning situations. A key part of the work for this project is considering the emotional and behavioural state of the trainees, and the creation of more realistic, and thereby stressful, representations of multimedia information to impact on the decision-making of those trainees. Existing training models are predominantly paper-based, table-top exercises, which require an exercise of imagination on the part of the trainees to consider not only the various aspects of a crisis situation but also the impacts of interventions, and remediating actions in the event of the failure of an intervention. However, existing computing models and tools are focused on supporting tactical and operational activities in crisis management, not strategic. Therefore, the PANDORA system will provide a rich multimedia information environment, to provide trainees with the detailed information they require to develop strategic plans to deal with a crisis scenario, and will then provide information on the impacts of the implementation of those plans and provide the opportunity for the trainees to revise and remediate those plans. Since this activity is invariably multi-agency, the training environment must support group-based strategic planning activities and trainees will occupy specific roles within the crisis scenario. The system will also provide a range of non-playing characters (NPC) representing domain experts, high-level controllers (e.g. politicians, ministers), low-level controllers (tactical and operational commanders), and missing trainee roles, to ensure a fully populated scenario can be realised in each instantiation. Within the environment, the emotional and behavioural state of the trainees will be monitored, and interventions, in the form of environmental information controls and mechanisms impacting on the stress levels and decisionmaking capabilities of the trainees, will be used to personalise the training environment. This approach enables a richer and more realistic representation of the crisis scenario to be enacted, leading to better strategic plans and providing trainees with structured feedback on their performance under stress

Sensible Agnosticism: An Updated Approach to Domain-Name Trademark Infringement

The Internet era has brought a new battlefield to U.S.-trademark-law disputes: domain names. Trademark owners have vigorously challenged the registration of domain names that consist of-or merely include-their trademarked terms, suing these domain-name registrants in U.S. courts for trademark infringement. During the early years of the Internet, courts often found consumer confusion-and thus trademark infringement-in these cases. As Internet use has developed, however, many courts have not recognized the growing sophistication of online consumers. This Note proposes that U.S. courts adapt their analyses to recognize evolving consumer behavior and expectations. This updated analysis, based on a 2010 Ninth Circuit opinion, will promote trademark law\u27s historical focus on accuracy by encouraging courts to recognize the right of domain-name registrants to engage in accurate, nonconfusing speech

Mobile Privacy and Business-to-Platform Dependencies: An Analysis of SEC Disclosures

This Article systematically examines the dependence of mobile apps on mobile platforms for the collection and use of personal information through an analysis of Securities and Exchange Commission (SEC) filings of mobile app companies. The Article uses these disclosures to find systematic evidence of how app business models are shaped by the governance of user data by mobile platforms, in order to reflect on the role of platforms in privacy regulation more generally. The analysis of SEC filings documented in the Article produces new and unique insights into the data practices and data-related aspects of the business models of popular mobile apps and shows the value of SEC filings for privacy law and policy research more generally. The discussion of SEC filings and privacy builds on regulatory developments in SEC disclosures and cybersecurity of the last decade. The Article also connects to recent regulatory developments in the U.S. and Europe, including the General Data Protection Regulation, the proposals for a new ePrivacy Regulation and a Regulation of fairness in business-to-platform relations