Personalizing human-agent interaction through cognitive models

Cognitive modeling of human behavior has advanced the understanding of underlying processes in several domains of psychology and cognitive science. In this article, we outline how we expect cognitive modeling to improve comprehension of individual cognitive processes in human-agent interaction and, particularly, human-robot interaction (HRI). We argue that cognitive models offer advantages compared to data-analytical models, specifically for research questions with expressed interest in theories of cognitive functions. However, the implementation of cognitive models is arguably more complex than common statistical procedures. Additionally, cognitive modeling paradigms typically have an explicit commitment to an underlying computational theory. We propose a conceptual framework for designing cognitive models that aims to identify whether the use of cognitive modeling is applicable to a given research question. The framework consists of five external and internal aspects related to the modeling process: research question, level of analysis, modeling paradigms, computational properties, and iterative model development. In addition to deriving our framework from a concise literature analysis, we discuss challenges and potentials of cognitive modeling. We expect cognitive models to leverage personalized human behavior prediction, agent behavior generation, and interaction pretraining as well as adaptation, which we outline with application examples from personalized HRI

Studying health-related internet and mobile device use using web logs and smartphone records

Many people use the internet to seek information that will help them understand their body and their health. Motivations for such behaviors are numerous. For example, users may wish to figure out a medical condition by searching for symptoms they experience. Similarly, they may seek more information on how to treat conditions they have been diagnosed with or seek resources on how to live a healthy life. With the ubiquitous availability of the internet, searching and finding relevant information is easier than ever before and a widespread phenomenon. To understand how people use the internet for health-related information, we use data from a sample of 1,959 internet users. A unique combination of data containing four months of users' browsing histories and mobile application use on computers and mobile devices allows us to study which health websites they visited, what information they searched for and which health applications they used. Survey data inform us about users' socio-demographic background, medical conditions and other health-related behaviors. Results show that women, young users, users with a university education and nonsmokers are most likely to use the internet and mobile applications for health-related purposes. On search engines, internet users most frequently search for pharmacies, symptoms of medical conditions and pain. Moreover, users seem most interested in information on how to live a healthy life, alternative medicine, mental health and women's health. With this study, we extend the field's understanding of who seeks and consumes health information online, what users look for as well as how individuals use mobile applications to monitor their health. Moreover, we contribute to methodological research by exploring new sources of data for understanding humans, their preferences and behaviors

Exogenous cognition and cognitive state theory: the plexus of consumer analytics and decision-making

We develop the concept of exogenous cognition (ExC) as a specific manifestation of an external cognitive system (ECS). Exogenous cognition describes the technological and algorithmic extension of (and annexation of) cognition in a consumption context. ExC provides a framework to enhance understanding of the impact of pervasive computing and smart technology on consumer decision-making and the behavioural impacts of consumer analytics. To this end, the paper provides commentary and structures to outline the impact of ExC and to elaborate the definition and reach of ExC. The logic of ExC culminates in a theory of cognitive states comprising of three potential decision states; endogenous cognition (EnC), symbiotic cognition (SymC) and surrogate cognition (SurC). These states are posited as transient (consumers might move between them during a purchase episode) and determined by individual propensities and situational antecedents. The paper latterly provides various potential empirical avenues and issues for consideration and debate

Countering Personalized Speech

Social media platforms use personalization algorithms to make content curation decisions for each end user. These personalized recommendation decisions are essentially speech conveying a platform\u27s predictions on content relevance for each end user. Yet, they are causing some of the worst problems on the internet. First, they facilitate the precipitous spread of mis- and disinformation by exploiting the very same biases and insecurities that drive end user engagement with such content. Second, they exacerbate social media addiction and related mental health harms by leveraging users\u27 affective needs to drive engagement to greater and greater heights. Lastly, they erode end user privacy and autonomy as both sources and incentives for data collection. As with any harmful speech, the solution is often counterspeech. Free speech jurisprudence considers counterspeech the most speech-protective weapon to combat false or harmful speech. Thus, to combat problematic recommendation decisions, social media platforms, policymakers, and other stakeholders should embolden end users to use counterspeech to reduce the harmful effects of platform personalization. One way to implement this solution is through end user personalization inputs. These inputs reflect end user expression about a platform\u27s recommendation decisions. However, industry-standard personalization inputs are failing to provide effective countermeasures against problematic recommendation decisions. On most, if not all, major social media platforms, the existing inputs confer limited ex post control over the platform\u27s recommendation decisions. In order for end user personalization to achieve the promise of counterspeech, I make several proposals along key regulatory modalities, including revising the architecture of personalization inputs to confer robust ex ante capabilities that filter by content type and characteristics

USERS’ PERCEPTIONS OF DATA OWNERSHIP, DATA STORAGE, AND THEIR LOCUS OF CONTROL OVER DATA GENERATED BY SMART PHONE APPLICATIONS

When users don’t understand how their data is stored, managed, and deleted in the cloud, it can leave that data vulnerable to hacking, privacy breaches, and other losses. How aware are users of what data they have in their cloud or other locations? This thesis examines how centralized remote storage affects participants’ knowledge of and ability to control and delete their phone app data using qualitative semi-structured interviews with 16 adults in the Washington, DC area. Results indicate that many users, especially Android users, don’t know what data they have backed up, and don’t feel they have control or understanding of their cloud account. Some participants thought they could better control their data if they learned more technical skills, but felt too intimidated to try. These results have implications for designing more usable cloud storage, recovery and deletion for mobile devices

Enhancing System Transparency, Trust, and Privacy with Internet Measurement

While on the Internet, users participate in many systems designed to protect their information’s security. Protection of the user’s information can depend on several technical properties, including transparency, trust, and privacy. Preserving these properties is challenging due to the scale and distributed nature of the Internet; no single actor has control over these features. Instead, the systems are designed to provide them, even in the face of attackers. However, it is possible to utilize Internet measurement to better defend transparency, trust, and privacy. Internet measurement allows observation of many behaviors of distributed, Internet-connected systems. These new observations can be used to better defend the system they measure. In this dissertation, I explore four contexts in which Internet measurement can be used to the aid of end-users in Internet-centric, adversarial settings. First, I improve transparency into Internet censorship practices by developing new Internet measurement techniques. Then, I use Internet measurement to enable the deployment of end-to-middle censorship circumvention techniques to a half-million users. Next, I evaluate transparency and improve trust in the Web public-key infrastructure by combining Internet measurement techniques and using them to augment core components of the Web public-key infrastructure. Finally, I evaluate browser extensions that provide privacy to users on the web, providing insight for designers and simple recommendations for end-users. By focusing on end-user concerns in widely deployed systems critical to end-user security and privacy, Internet measurement enables improvements to transparency, trust, and privacy.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163199/1/benvds_1.pd

What Opportunities For Storytelling Might Near-future Technologies Offer Creatives, And How Might Personal Data Affect This?

A common feature of storytelling, at least when it comes to a western, and classical perspective, is that of linearity. Stories often have a single path through them that the content of the story, the Fabula, is arranged along, with this arrangement of the content of the story, the Syuzhet, often being dictated by a single authorial voice. However, a rise in technology and an audience’s willingness to experience new storytelling methods has helped give rise to more experimentation, leading to the popularisation of audience-controlled linearity and interactive storytelling. There can be tension within this way of telling stories as it is commonly believed that in order to increase the interactive quality of a story you have to reduce the quality of the narrative, with some storytellers and researchers approaching narrative and interactivity as opposing forces. I believe that, by doing this, researchers and artists are accidentally limiting the scope of the combinations of Narrative and Interactivity they consider when researching these qualities of storytelling experiences. Narrative and Interactivity are neutral and complex features that can be mediated in different ways throughout a storytelling experience to create enjoyment in an audience, one of the main aims of most stories. Perhaps the multi-faceted nature of enjoyment has made reliably researching it seem difficult, futile, or even perhaps unscientific in the past, but using Roth’s (2015) battery of experimentally valid enjoyment questionnaires allows me to examine the enjoyment elicited in responses to an interactive narrative experience in an experimentally valid and appropriately detailed way. This means that I should be able to derive which quantities and qualities of interactivity and narrative create or hinder the creation of not just enjoyment in an audience, but specific facets and flavours of audience enjoyment. In order to test this hypothesis I had to build an interactive storytelling experience that could vary its amount of Narrative or Interactivity, and it became apparent while doing this that the system that runs this, a branching narrative that presented different video clips depending on audience responses, could also be used to run the research itself, not just deliver the narrative content of the research experience. Using this system, and taking inspiration from my experience with making interactive digital theatre and using magician’s crowd control techniques, such as the Equivoque Force or Barnum Statements, an automated researcher was created to help brief the participants, calibrate the audience behaviour data tracking system, and deliver quantitative and qualitative data collection procedures to the audience. This researcher felt lifelike without the use of complicated AI or machine learning by using a clever mix of simple narrative path systems and a careful anticipation of likely participant responses. The effectiveness of this sort of automated researcher was also investigated as part of this thesis. I found: • Various new methodologies that have wide uses for different researchers, including the automated research assistant and a way of analysing and comparing digital theatre experiences, called a Dramatography, as well as continued evidence for the use of a Performance Led Research and Rapid Iterative Prototyping a valuable methodology for examining these sorts of creative research questions. • In spite of the theory concerning the balance of Interactivity and Narrative, I found that a narratively rich and meaningfully interactive experience is achievable via a creative, low- resource methodology, that a minimal use of easy-to-measure audience behaviour data is required to create the feeling of meaningful interactivity and liveness, and that the type of audience behaviour data used to create that feeling didn’t have a significant effect on audience enjoyment. • That a majority of participants had positive things to say about the automated research assistant and found the experience of undergoing the research user-friendly in spite of the lack of a human researcher, meaning that a scalable and on-demand research methodology for both complex quantitative and qualitative data collection, with a recognisably human face, is possible