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Major online platforms today are multi-stakeholder in nature and they cater to the interests of various stakeholders. Examples include e-commerce platforms with sellers of goods and services and buyers who pay for them, hotel booking platforms with hosts and guests, media-streaming platforms artists or content creators and viewers, and many more. The focus here is on the information access services (like search and recommendation) deployed on these platforms. While traditionally these services were designed in consumer-centric ways, they are found to be unfair to providers. Since the providers depend on these platforms for their livelihood, fairness for providers is an important and necessary design element in many scenarios. This chapter summarizes the domain and discusses various prior works on provider fairness in such multi-stakeholder platforms after a brief review of major works on algorithmic fairness in machine learning. Many recent works show that provider fairness can cause loss of utility and unfairness for consumers. Following this, a number of works have proposed fairness notions for both providers and consumers in different settings, and studied multi-stakeholder fairness to balance various fairness and utility goals or constraints. This chapter reviews some major works on multi-stakeholder fairness in the following three aspects: the problem setting, fairness notions, and proposed approaches. It also discusses how most of the works on multi-stakeholder fairness have considered settings with only two stakeholders, gives some examples on other platforms with more than two stakeholders, and how they are fundamentally different in terms of the utility structure for the stakeholders.

Abstract:
Irregularly sampled time series data with missing values is a observed in many fields like healthcare, astronomy, and climate science. Interpolation of these types of time series is crucial for tasks such as root cause analysis and medical diagnosis, as well as for smoothing out irregular or noisy data. To address this challenge, we present a novel encoder-decoder architecture called "Tripletformer" for probabilistic interpolation of irregularly sampled time series with missing values. This attention-based model operates on sets of observations, where each element is composed of a triple of time, channel, and value. The encoder and decoder of the Tripletformer are designed with attention layers and fully connected layers, enabling the model to effectively process the presented set elements.
We evaluate the Tripletformer against a range of baselines on multiple real-world and synthetic datasets and show that it produces more accurate and certain interpolations. Results indicate an improvement in negative loglikelihood error by up to 32% on real-world datasets and 85% on synthetic datasets when using the Tripletformer compared to the next best model.

Background

Although psychoeducation is generally recommended for the treatment of adult attention-deficit hyperactivity disorder (ADHD), participation in clinical psychoeducation groups is impeded by waiting times and the constrained number of patients who can simultaneously attend a group. Digital psychoeducation attempts are promising, but the rapidly expanding number of apps lack evidence and are mostly limited to only a few implemented interactive elements.

Aims

To determine the potential of digital, self-guided psychoeducation for adult ADHD, a newly developed interactive chatbot was compared with a previously validated, conventional psychoeducation app.

Method

Forty adults with ADHD were randomised, of whom 17 participants in each group completed self-guided psychoeducation based on either a chatbot or conventional psychoeducation app between October 2020 and July 2021. ADHD core symptoms were assessed before and after the 3-week interventions, using both the blinded observer-rated Integrated Diagnosis of ADHD in Adulthood interview and the self-rated ADHD Self-Assessment Scale (ADHS-SB).

Results

Observer- and patient-rated ADHD symptoms were significantly reduced from pre- to post-intervention (observer-rated: mean difference −6.18, 95% CI −8.06 to −4.29; patient-rated: mean difference −2.82, 95% CI −4.98 to −0.67). However, there were no group × intervention interaction effects that would indicate a stronger therapeutic benefit of one of the interventions. Likewise, administered psychoeducational knowledge quizzes did not show differences between the groups. No adverse events were reported.

Conclusions

Self-guided psychoeducation based on a chatbot or a conventional app appears similarly effective and safe for improving ADHD core symptoms. Future research should compare additional control interventions and examine patient-related outcomes and usability preferences in detail.

Growing popularity of wearable haptic devices encouraged researchers to implement on-body interfaces that appropriate different form factors and interaction techniques. Among vibrotactile wearable interfaces, neck-worn devices gathered limited attention in HCI. While the “necklace area” offers wide opportunities for subtle haptic interaction, we lack knowledge of its tactile acuity to design interactive systems effectively. In this work, we present a prototype of HaptiNecklace - a vibrotactile necklace designed to study tactile acuity of sternoclavicular area. In the experimental study with N=19 participants, we compared recognition accuracy and cognitive load between different numbers of vibrotactile motors attached to the prototype in two scenarios – static and mobile. The results show that directional patterns ensure better recognition than single-point vibrations in both mobile and static context. Moreover, introducing mobile scenario does not influence recognition accuracy but highly increases cognitive load. In this work, we provide practical hints to designing vibrotactile necklaces.

Im einführenden Kapitel bilanziert Martin Kuhlmann Kernerkenntnisse der arbeitssoziologischen Digitalisierungsforschung.

Er geht dabei insbesondere auf folgende Kernerkenntnisse ein:

1.) Digitalisierung ist gestaltbar und muss auch gestaltet werden. Es gibt keinen Technikdeterminismus.

2.) Digitalisierung ist pfadabhängig.

3.) Es gibt nicht "die" Digitalisierung mitihren spezifischen Formen und Wirkungen, sondern vielmehr eine "strukturierte Vielfalt" entlang benennbarere Faktoren (u. .a. Spezifika & Anforderungen der Tätigkeit, Wettbewerbs- und Marktbedingungen, Akteur*innen mir ihren Interessen & Machtverhältnissen..)