Recommenders play a significant role in our daily lives, making decisions for users on a regular basis. Their widespread adoption necessitates a thorough examination of how users interact with recommenders and the algorithms that drive them. An important form of interaction in these systems are algorithmic affordances: means that provide users with perceptible control over the algorithm by, for instance, providing context (‘find a movie for this profile’), weighing criteria (‘most important is the main actor’), or evaluating results (‘loved this movie’). The assumption is that these algorithmic affordances impact interaction qualities such as transparency, trust, autonomy, and serendipity, and as a result, they impact the user experience. Currently, the precise nature of the relation between algorithmic affordances, their specific implementations in the interface, interaction qualities, and user experience remains unclear. Subjects that will be discussed during the workshop, therefore, include but are not limited to the impact of algorithmic affordances and their implementations on interaction qualities, balances between cognitive overload and transparency in recommender interfaces containing algorithmic affordances; and reasons why research into these types of interfaces sometimes fails to cross the research-practice gap and are not landing in the design practice. As a potential solution the workshop committee proposes a library of examples of algorithmic affordances design patterns and their implementations in recommender interfaces enriched with academic research concerning their impact. The final part of the workshop will be dedicated to formulating guiding principles for such a library.
LINK
Void street interfaces (VSIs) – building plinths with restricted visual interaction, accessibility, and public use – constitute an urban feature often associated with undermining the public domain, limiting free access and preventing interaction between social groups. Moreover, VSIs have been described as products of inequality designed to segregate and hinder integration between public and private urban spaces. This study assesses VSIs across six cities in Brazil, a country notable for its profound inequality and sociospatial fragmentation. The main aims of this research are: (i) to develop and test a predictive model for VSIs using socioeconomic indicators drawn from open-source ground-truth data; (ii) to identify the variance of VSI within selected case studies. In the development phase of the predictive model, data from the city of Recife are used to build the model. The testing phase involves the analysis of VSIs in the cities of Fortaleza, Salvador, Belo Horizonte, Curitiba and Porto Alegre. The model can potentially assist urban planners in better understanding and locating VSIs and mitigating undesirable outcomes.
MULTIFILE
This exploratory study investigates the rationale behind categorizing algorithmic controls, or algorithmic affordances, in the graphical user interfaces (GUIs) of recommender systems. Seven professionals from industry and academia took part in an open card sorting activity to analyze 45 cards with examples of algorithmic affordances in recommender systems’ GUIs. Their objective was to identify potential design patterns including features on which to base these patterns. Analyzing the group discussions revealed distinct thought processes and defining factors for design patterns that were shared by academic and industry partners. While the discussions were promising, they also demonstrated a varying degree of alignment between industry and academia when it came to labelling the identified categories. Since this workshop is part of the preparation for creating a design pattern library of algorithmic affordances, and since the library aims to be useful for both industry and research partners, further research into design patterns of algorithmic affordances, particularly in terms of labelling and description, is required in order to establish categories that resonate with all relevant parties
LINK
Algorithmic affordances are defined as user interaction mechanisms that allow users tangible control over AI algorithms, such as recommender systems. Designing such algorithmic affordances, including assessing their impact, is not straightforward and practitioners state that they lack resources to design adequately for interfaces of AI systems. This could be amended by creating a comprehensive pattern library of algorithmic affordances. This library should provide easy access to patterns, supported by live examples and research on their experiential impact and limitations of use. The Algorithmic Affordances in Recommender Interfaces workshop aimed to address key challenges related to building such a pattern library, including pattern identification features, a framework for systematic impact evaluation, and understanding the interaction between algorithmic affordances and their context of use, especially in education or with users with a low algorithmic literacy. Preliminary solutions were proposed for these challenges.
LINK
B4B is a multi-year, multi-stakeholder project focused on developing methods to harness big data from smart meters, building management systems and the Internet of Things devices, to reduce energy consumption, increase comfort, respond flexibly to user behaviour and local energy supply and demand, and save on installation maintenance costs. This will be done through the development of faster and more efficient Machine Learning and Artificial Intelligence models and algorithms. The project is geared to existing utility buildings such as commercial and institutional buildings.
DOCUMENT
DOCUMENT
Post-partum hemorrhaging is a medical emergency that occurs during childbirth and, in extreme cases, can be life-threatening. It is the number one cause of maternal mortality worldwide. High-quality training of medical staff can contribute to early diagnosis and work towards preventing escalation towards more serious cases. Healthcare education uses manikin-based simulators to train obstetricians for various childbirth scenarios before training on real patients. However, these medical simulators lack certain key features portraying important symptoms and are incapable of communicating with the trainees. The authors present a digital embodiment agent that can improve the current state of the art by providing a specification of the requirements as well as an extensive design and development approach. This digital embodiment allows educators to respond and role-play as the patient in real time and can easily be integrated with existing training procedures. This research was performed in collaboration with medical experts, making a new contribution to medical training by bringing digital humans and the representation of affective interfaces to the field of healthcare.
DOCUMENT
Speech interactions are often associated with virtual assistants and smart home devices, designed primarily for private contexts. A less developed domain is speech interfaces in public contexts. In a smart city development project, we explored the potential of distributed conversational speech interfaces in lampposts. Deploying a research-through-design method, we created a lo-fi prototype of the speech interface that test subjects could interact with during experiments in a lab setting. Our first exploratory prototype consisted of a loudspeaker that acted as the interface and preconceived dialogues designed to investigate the boundaries of desirable and acceptable experiences regarding issues such as privacy. Experiencing the interaction with this rudimentary prototype helped people envision potential use cases and reflect on privacy issues: the dialogues revealed subjective limits of what kind of (personal) information people were willing to share with the lamppost. They also elicited thoughts on possible consequences in the social context of citizens. LinkedIn: https://www.linkedin.com/in/atjylha/ https://www.linkedin.com/in/josvanleeuwen/
DOCUMENT
Beyond the potential of new layers of urban infrastructure - sensor-laden networks, big data, artificial intelligence - to optimize cities functionally, lay promising opportunities to also use these technologies for new forms of social interactions. In an ongoing smart city development project, we explore the potential of distributed conversational speech interfaces in the social context of local urban communities. LinkedIn: https://www.linkedin.com/in/atjylha/ https://www.linkedin.com/in/josvanleeuwen/
DOCUMENT
In an on-going smart city development project, we are exploring the potential of distributed conversational speech interfaces in the public context of a city. By using the well-known Wizard of Oz method in combination with a lo-fi prototype, we involve participants in co-design with the focus on potential use cases, social acceptability, and privacy aspects of interacting with a speech interface publicly. The work taps into the gap of design-oriented work in the domain of speech-based HCI. LinkedIn: https://www.linkedin.com/in/atjylha/ https://www.linkedin.com/in/josvanleeuwen/
DOCUMENT
