Scaling Machine Learning Systems using Domain Adaptation

Machine-learned components, particularly those trained using deep learning methods, are becoming integral parts of modern intelligent systems, with applications including computer vision, speech processing, natural language processing and human activity recognition. As these machine learning (ML) systems scale to real-world settings, they will encounter scenarios where the distribution of the data in the real-world (i.e., the target domain) is different from the data on which they were trained (i.e., the source domain). This phenomenon, known as domain shift, can significantly degrade the performance of ML systems in new deployment scenarios. In this thesis, we study the impact of domain shift caused by variations in system hardware, software and user preferences on the performance of ML systems. After quantifying the performance degradation of ML models in target domains due to the various types of domain shift, we propose unsupervised domain adaptation (uDA) algorithms that leverage unlabeled data collected in the target domain to improve the performance of the ML model. At its core, this thesis argues for the need to develop uDA solutions while adhering to practical scenarios in which ML systems will scale. More specifically, we consider four scenarios: (i) opaque ML systems, wherein parameters of the source prediction model are not made accessible in the target domain, (ii) transparent ML systems, wherein source model parameters are accessible and can be modified in the target domain, (iii) ML systems where source and target domains do not have identical label spaces, and (iv) distributed ML systems, wherein the source and target domains are geographically distributed, their datasets are private and cannot be exchanged using adaptation. We study the unique challenges and constraints of each scenario and propose novel uDA algorithms that outperform state-of-the-art baselines

Evaluating Machine Intelligence with Question Answering

Humans ask questions to learn about the world and to test knowledge understanding. The ability to ask questions combines aspects of intelligence unique to humans: language understanding, knowledge representation, and reasoning. Thus, building systems capable of intelligent question answering (QA) is a grand goal of natural language processing (NLP). To measure progress in NLP, we create "exams" for computer systems and compare their effectiveness against a reference point---often based on humans. How precisely we measure progress depends on whether we are building computer systems that optimize human satisfaction in information-seeking tasks or that measure progress towards intelligent QA. In the first part of this dissertation, we explore each goal in turn, how they differ, and describe their relationship to QA formats. As an example of an information-seeking evaluation, we introduce a new dialog QA task paired with a new evaluation method. Afterward, we turn our attention to using QA to evaluate machine intelligence. A good evaluation should be able to discriminate between lesser and more capable QA models. This dissertation explores three ways to improve the discriminative power of QA evaluations: (1) dynamic weighting of test questions, (2) a format that by construction tests multiple levels of knowledge, and (3) evaluation data that is created through human-computer collaboration. By dynamically weighting test questions, we challenge a foundational assumption of the de facto standard in QA evaluation---the leaderboard. Namely, we contend that contrary to nearly all QA and NLP evaluations which implicitly assign equal weights to examples by averaging scores, that examples are not equally useful for estimating machine (or human) QA ability. As any student may tell you, not all questions on an exam are equally difficult and in the worst-case questions are unsolvable. Drawing on decades of research in educational testing, we propose adopting an alternative evaluation methodology---Item Response Theory---that is widely used to score human exams (e.g., the SAT). By dynamically weighting questions, we show that this improves the reliability of leaderboards in discriminating between models of differing QA ability while also being helpful in the construction of new evaluation datasets. Having improved the scoring of models, we next turn to improving the format and data in QA evaluations. Our idea is simple. In most QA tasks (e.g., Jeopardy!), each question tests a single level of knowledge; in our task (the trivia game Quizbowl), we test multiple levels of knowledge with each question. Since each question tests multiple levels of knowledge, this decreases the likelihood that we learn nothing about the difference between two models (i.e., they are both correct or both wrong), which substantially increases discriminative power. Despite the improved format, we next show that while our QA models defeat accomplished trivia players, that they are overly reliant on brittle pattern matching, which indicates a failure to intelligently answer questions. To mitigate this problem, we introduce a new framework for building evaluation data where humans and machines cooperatively craft trivia questions that are difficult to answer through clever pattern matching tricks alone---while being no harder for humans. We conclude by sketching a broader vision for QA evaluation that combines the three components of evaluation we improve---scoring, format, and data---to create living evaluations and re-imagine the role of leaderboards

A persuasive approach to designing interactive tools around the promises and perils of social platforms

Every day, people interact with various social platforms. Diverse forms of social platforms opened up a plethora of data to study information dissemination and understanding crowd behavior in finer details. However, there is a flip side to this. People do not only get benefited by using social platforms; rather these platforms can also be exploited for spreading organized disinformation and unintended misinformation to a large audience. These social platforms, with access to the history of users' socio-political biases, can emerge as tools to shape mass opinion. Such a broad spectrum of diversity raises questions about how we can identify the promises and perils of social platforms and how we can design user-centric tools around them. Efficient identification of such promises and perils of social computing systems will require a convergence of social science, behavioral psychology, and persuasion theory with computing. My research shows ways to this convergence. In my dissertation, I have taken a theoretical approach to explain the existing structures of social platforms. My findings helped me to develop interactive tools for masses leveraging socio-political and psychological cues from the crowd. My work is empirical in nature, for which I drew intuitions from theories in social science and used a combination of qualitative and quantitative data analysis techniques to extract insights on users' behavior. My research leads to practical systems for human-centric applications and to this end, I chose a specific type of social platform: crowdfunding platform. Specifically, this dissertation makes three contributions. First, it investigates how different forms of crowdfunding platforms become promising resources in our daily life. To this end, I present two work. The first work demonstrates how scientific crowdfunding platforms assist young researchers to seek funding for their research projects through expert endorsements. The second work focuses on the novice entrepreneurs and explains how enterprise crowdfunding platforms assist novices to gather funding from the crowd for their creative ideas and how persuasive promotional videos are essential for those campaigns to be successful. The findings of this work led to the next part of this dissertation where I designed and built VidLyz, an interactive online tool, that can explain the significance and implication of persuasion factors to novice entrepreneurs who have no formal training in advertising and media studies. A follow-up user study showed that VidLyz can effectively guide novices step-by-step to make a concrete plan for their campaign videos. Finally, I take a step further and investigates the flip side of social platforms: how social platforms can increase onion polarization on traditionally stigmatized topics such as equal rights for LGBTIQ people. I show that even after getting exposed to content both in favor of and against equal rights for LGBTIQ people simultaneously, users develop a more polarized opinion on the stigmatized issue after the exposure. In the last part, this dissertation shows promising ways to mitigate the effect of attitude polarization and in-group sensitization with the help of behavioral priming techniques. The findings of this dissertation present structured ways of uncovering the promises and perils of social platforms and shows how these aspects can be leveraged to build interactive socio-technical systems. Overall, it may be fair to see this dissertation as a step forward to design socio-technical systems based on the knowledge learned from the interaction of the users of social platforms

Systems Engineering Approaches to Minimize the Viral Spread of Social Media Challenges

Recently, adolescents’ and young adults’ use of social media has significantly increased. While this new landscape of cyberspace offers young internet users many benefits, it also exposes them to numerous risks. One such phenomenon receiving limited research attention is the advent and propagation of viral social media challenges. Several of these challenges entail self-harming behavior, which combined with their viral nature, poses physical and psychological risks for the participants and the viewers. One example of these viral social media challenges that could potentially be propagated through social media is the Blue Whale Challenge (BWC). In the initial study we investigate how people portray the BWC on social media and the potential harm this may pose to vulnerable populations. We first used a thematic content analysis approach, coding 60 publicly posted YouTube videos, 1,112 comments on those videos, and 150 Twitter posts that explicitly referenced BWC. We then deductively coded the YouTube videos based on the Suicide Prevention Resource Center (SPRC) Messaging guidelines. We found that social media users post about BWC to raise awareness and discourage participating, express sorrow for the participants, criticize the participants, or describe a relevant experience. Moreover, we found most of the videos on YouTube violate at least 50% of the SPRC safe and effective messaging guidelines. These posts might have the problematic effect of normalizing the BWC through repeated exposure, modeling, and reinforcement of self-harming and suicidal behavior, especially among vulnerable populations, such as adolescents. A second study conducted a systematic content analysis of 180 YouTube videos (~813 minutes total length), 3,607 comments on those YouTube videos, and 450 Twitter posts to explore the portrayal and social media users’ perception of three viral social media-based challenges (i.e., BWC, Tide Pod Challenge (TPC), and Amyotrophic Lateral Sclerosis (ALS) Ice Bucket Challenge (IBC)). We identified five common themes across the challenges, including: education and awareness, criticizing the participants and blaming the victims, detailed information about the participants, giving viewers a tutorial on how to participate, and understanding seemingly senseless online behavior. We found that the purpose of posting about an online challenge varies based on the inherent risk involved in the challenge itself. However, analysis of the YouTube comments showed that previous experience and exposure to online challenges appear to affect the perception of other challenges in the future. The third study investigated the beliefs that lead adolescents and young adults to participate in these activities by analyzing the ALS IBC to represent challenges with minimally harmful behaviors intended to support philanthropic endeavors and the Cinnamon Challenge (CC), to represent those involving harmful behaviors that may culminate in injury. We conducted a retrospective quantitative study with a total of 471 participants between the ages of 13 and 35 who either had participated in the ALS IBC or the CC or had never participated in any online challenge. We used binomial logistic regression models to classify those who participated in ALS IBC or CC versus those who didn’t with the beliefs from the Integrated Behavioral Model (IBM) as predictors. Our findings showed that both CC and ALS IBC participants had significantly greater positive emotional responses, value for the outcomes of the challenge, and expectation of the public to participate in the challenge in comparison to individuals who never participated in any challenge. In addition, only CC participants perceived positive public opinion about the challenge and perceived the challenge to be easy with no harmful consequences, in comparison to individuals who never participated in any challenge. The findings from this study were used to develop interventions based on knowledge of how the specific items making up each construct apply specifically to social media challenges. In the last study, we showed how agent-based modeling (ABM) might be used to investigate the effect of educational intervention programs to reduce social media challenges participation at multiple levels- family, school, and community. In addition, we showed how the effect of these educational based interventions can be compared to social media-based policy interventions. Our model takes into account the “word of mouth” effect of these interventions which could either decrease participation in social media challenge further than expected or unintentionally cause others to participate

Barack Obama's Post-American Foreign Policy

This book is available as open access through the Bloomsbury Open Access programme and is available on www.bloomsburycollections.com. After one of the most controversial and divisive periods in the history of American foreign policy under President George W. Bush, the Obama administration was expected to make changes for the better in US relations with the wider world. Now, international problems confronting Obama appear more intractable, and there seems to be a marked continuity in policies between Obama and his predecessor. Robert Singh argues that Obama's approach of 'strategic engagement' was appropriate for a new era of constrained internationalism, but it has yielded modest results. Obama's search for the pragmatic middle has cost him political support at home and abroad, whilst failing to make decisive gains. Singh suggests by calibrating his foreign policies to the emergence of a 'post-American'world, the president has yet to preside over a renaissance of US global leadership. Ironically,Obama's policies have instead hastened the arrival of a post-American world

Forward to the Past? New/Old Theatres of Russia’s International Projection

Russia seems to be back in many “old” theatres where the Soviet Union was actively engaged. More than a quarter of a century after the fall of the USSR, it is clear that Russia’s President Vladimir Putin has made restoring Russia’s great power status a primary goal of his twenty years in power. Political and historical links dating back to the Cold War have been capitalised upon to build fresh partnerships and cement or re-establish Russia’s influence in Africa, Latin America and the Middle East. Just as the Soviet Union supported Western communist parties and ran disinformation campaigns, today’s Russia is accused of meddling with the electoral processes of several Western countries. What are the elements of continuity and change when comparing Russia’s foreign policy with the Soviet Union’s?This ISPI Report tackles the political, historical, military and economic dimensions of Russia’s return to old Soviet theatres of influence. In particular, it delves into their implications for the development of the multipolar world order long-advocated by Moscow

Negotiating intervention by invitation: how the Colombians shaped US participation in the genesis of Plan Colombia

The aim of this dissertation is to investigate the genesis of Plan Colombia, the aid programme that transferred US$1.3 billion to Colombia during fiscal year 2000/2001 alone. It was found that President Andres Pastrana invited the intervention of the US in many aspects of Colombia’s internal affairs, from his peace process with guerrilla insurgents to his project to reassert the authority of the state over Colombia’s ‘internal periphery’. A complex, three-way negotiation between the two core Executives and the US Congress ensued, which yielded a more limited intervention than the Colombians desired. It was also found that, the vast power asymmetry notwithstanding, it was the small state that took the initiative and managed to exert influence over the great power. These findings conclusively refute the paradigmatic presumption in the IR literature that Plan Colombia was hegemonically imposed. To the contrary, the protracted (two years long) negotiation of terms showed the ‘hegemon’ decidedly reluctant to be drawn too far into its internal affairs of its ‘victim’. Plan Colombia follows a characteristic pattern in US foreign relations, which has been noted before; a unique form of ‘imperialism’ whereby subject states actually invite the intervention of the great power, in some cases even to the point of occupation. Unlike the approach typical of the IR field, which is predominantly a priori in method, the treatment herein is essentially inductive. For my fieldwork I interviewed the gamut of elite participants in the making of the Plan, from ex-President Pastrana himself to Thomas Pickering, the third-ranking officer in the US State Department. Letting the facts from all sources speak for themselves, I have arrived at counterintuitive results of interest to theorists and practitioners of international relations

Technologies of Suspicion and the Ethics of Obligation in Political Asylum

Across the globe, migration has been met with intensifying modes of criminalization and securitization, and claims for political asylum are increasingly met with suspicion. Asylum seekers have become the focus of global debates surrounding humanitarian obligations, on the one hand, and concerns surrounding national security and border control, on the other. In Technologies of Suspicion and the Ethics of Obligation in Political Asylum, contributors provide fine-tuned analyses of political asylum systems and the adjudication of asylum claims across a range of sociocultural and geopolitical contexts. The contributors to this timely volume, drawing on a variety of theoretical perspectives, offer critical insights into the processes by which tensions between humanitarianism and security are negotiated at the local level, often with negative consequences for asylum seekers. By investigating how a politics of suspicion within asylum systems is enacted in everyday practices and interactions, the authors illustrate how asylum seekers are often produced as suspicious subjects by the very systems to which they appeal for protection. Contributors: Ilil Benjamin, Carol Bohmer, Nadia El-Shaarawi, Bridget M. Haas, John Beard Haviland, Marco Jacquemet, Benjamin N. Lawrance, Rachel Lewis, Sara McKinnon, Amy Shuman, Charles Wattershttps://ohioopen.library.ohio.edu/oupress/1015/thumbnail.jp

Technologies of Suspicion and the Ethics of Obligation in Political Asylum

Across the globe, migration has been met with intensifying modes of criminalization and securitization, and claims for political asylum are increasingly met with suspicion. Asylum seekers have become the focus of global debates surrounding humanitarian obligations, on the one hand, and concerns surrounding national security and border control, on the other. In Technologies of Suspicion and the Ethics of Obligation in Political Asylum, contributors provide fine-tuned analyses of political asylum systems and the adjudication of asylum claims across a range of sociocultural and geopolitical contexts. The contributors to this timely volume, drawing on a variety of theoretical perspectives, offer critical insights into the processes by which tensions between humanitarianism and security are negotiated at the local level, often with negative consequences for asylum seekers. By investigating how a politics of suspicion within asylum systems is enacted in everyday practices and interactions, the authors illustrate how asylum seekers are often produced as suspicious subjects by the very systems to which they appeal for protection. Contributors: Ilil Benjamin, Carol Bohmer, Nadia El-Shaarawi, Bridget M. Haas, John Beard Haviland, Marco Jacquemet, Benjamin N. Lawrance, Rachel Lewis, Sara McKinnon, Amy Shuman, Charles Watter