首页|Recent Findings from University of Bayreuth Provides New Insights into Artificia l Intelligence (How Artificial Intelligence Challenges Tailorable Technology Des ign)
Recent Findings from University of Bayreuth Provides New Insights into Artificia l Intelligence (How Artificial Intelligence Challenges Tailorable Technology Des ign)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-A new study on Artificial Intelligence is now available. According to news reporting from Bayreuth, Germany, by NewsRx journalists, research stated, "Artificial intelligence (AI) has significantly a dvanced healthcare and created unprecedented opportunities to enhance patient-ce nteredness and empowerment. This progress promotes individualized medicine, wher e treatment and care are tailored to each patient's unique needs and characteris tics." Financial supporters for this research include Universitt Bayreuth (3145), Ethic s Committee of the University of Bayreuth. The news correspondents obtained a quote from the research from the University o f Bayreuth, "The Theory of Tailorable Technology Design has considerable potenti al to contribute to individualized medicine as it focuses on information systems (IS) that users can modify and redesign in the context of use. While the theory accounts for both the designer and user perspectives in the lifecycle of an IS, it does not reflect the inductive learning and autonomy of AI throughout the ta iloring process. Therefore, this study posits the conjecture that current knowle dge about tailorable technology design does not effectively account for IS that incorporate AI. To investigate this conjecture and challenge the Theory of Tailo rable Technology Design, a revelatory design study of an AI-enabled individual I S in the domain of bladder monitoring is conducted. Based on the empirical evide nce from the design study, the primary contribution of this work lies in three p ropositions for the design of tailorable technology, culminating in a Revised Th eory of Tailorable Technology Design. As the outcome of the design study, the se condary contribution of this work is concrete design knowledge for AI-enabled in dividualized bladder monitoring systems that empower patients with neurogenic lo wer urinary tract dysfunction (NLUTD)."
BayreuthGermanyEuropeArtificial In telligenceEmerging TechnologiesMachine LearningTechnologyUniversity of B ayreuth
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