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Development in times of hype: How freelancers explore Generative AI?
No full textThe rise of generative AI has led many companies to hire freelancers to harness its potential. However, this technology presents unique challenges to developers who have not previously engaged with it. Freelancers may find these challenges daunting due to the absence of organizational support and their reliance on positive client feedback. In a study involving 52 freelance developers, we identified multiple challenges associated with developing solutions based on generative AI. Freelancers often struggle with aspects they perceive as unique to generative AI such as unpredictability of its output, the occurrence of hallucinations, and the inconsistent effort required due to trial-and-error prompting cycles. Further, the limitations of specific frameworks, such as token limits and long response times, add to the complexity. Hype-related issues, such as inflated client expectations and a rapidly evolving technological ecosystem, further exacerbate the difficulties. To address these issues, we propose Software Engineering for Generative AI (SE4GenAI) and Hype-Induced Software Engineering (HypeSE) as areas where the software engineering community can provide effective guidance. This support is essential for freelancers working with generative AI and other emerging technologies
Towards the Socio-Algorithmic Construction of Fairness: The Case of Automatic Price-Surging in Ride-Hailing
No full textAlgorithms take decisions that affect humans, and have been shown to perpetuate biases and discrimination. Decisions by algorithms are subject to different interpretations. Algorithms’ behaviors are basis for the construal of moral assessment and standards. Yet we lack an understanding of how algorithms impact on social construction processes, and vice versa. Without such understanding, social construction processes may be disrupted and, eventually, may impede moral progress in society. We analyze the public discourse that emerged after a significant (five-fold) price-surge following the Brooklyn Subway Shooting on April 12 2022, in New York City. There was much controversy around the two ride-hailing firms’ algorithms’ decisions. The discussions evolved around various notions of fairness and the algorithms’ decisions’ justifiability. Our results indicate that algorithms, even if not explicitly addressed in the discourse, strongly impact on constructing fairness assessments and notions. They initiate the exchange, form people’s expectations, evoke people’s solidarity with specific groups, and are a vehicle for moral crusading. However, they are also subject to adjustments based on social forces. We claim that the process of constructing notions of fairness is no longer just social; it has become a socio-algorithmic process. We propose a theory of socio-algorithmic construction as a mechanism for establishing notions of fairness and other ethical constructs
Strategie im Sahel: Deutschland sollte sich für eine pragmatischere Zusammenarbeit einsetzen
No full textAls einer der führenden internationalen Geldgeber in der Sahelregion steht Deutschland vor einem Wendepunkt. Die Staatsstreiche in Burkina Faso, Mali und Niger erschweren die Zusammenarbeit und machen strategische Anpassungen notwendig. Angesichts dessen muss sich die Bundesregierung dringend für ein pragmatischeres Vorgehen einsetzen, ohne die Putsche zu legitimieren. Dazu gehören konkrete Instrumente wie datengestützte Analysen des bisherigen Engagements, die Messbarkeit von (Miss-)Erfolgen und eine klare Prioritätensetzung
“WOOP is my safe haven”: A qualitative feasibility and acceptability study of the Wish Outcome Obstacle Plan (WOOP) intervention for spouses of people living with early‐stage dementia
No full textBildungsungleichheit wie in kaum einem anderen Land? Hartmut Essers Frontalangriff auf die Standardposition und das Integrationsmodell in der Bildungsforschung
No full textIntegrating Advanced Mobility Services in Federated Data Spaces: An Exploration of Organizational Roles
No full textFreigeschaltet, 30.06.2024
No full textThe advent of increasingly powerful language models has raised expectations for conversational interactions. However, controlling these models is a challenge, emphasizing the need to be able to investigate the feasibility and value of their application. We present PROMISE (Available at: https://github.com/zhaw-iwi/promise), a framework that facilitates the development of complex conversational interactions with information systems. Its use of state machine modeling concepts enables model-driven, dynamic prompt orchestration across hierarchically nested states and transitions. This improves the control of language models’ behavior and thus enables their effective and efficient use. We show the applications of PROMISE in health information systems and demonstrate its ability to handle complex interactions
