Eye tracking insights into physician behaviour with safe and unsafe explainable AI recommendations [PDF]
We studied clinical AI-supported decision-making as an example of a high-stakes setting in which explainable AI (XAI) has been proposed as useful (by theoretically providing physicians with context for the AI suggestion and thereby helping them to reject
Myura Nagendran +4 more
doaj +2 more sources
Ethical integration of patient-reported outcomes and digital biomarkers in AI healthcare models: an expert consensus framework [PDF]
BackgroundAlongside expected benefits, several ethical concerns arise from Artificial Intelligence (AI) based models. From the design to the implementation and subsequent evaluation, it is crucial to map potential ethical concerns regarding the use of AI
Joana Seringa +3 more
doaj +2 more sources
Use of AI within COA linguistic validation and eCOA migration processes: analysis and good practice recommendations [PDF]
Background While there has been much discussion around the use of Artificial Intelligence (AI) for multilingual translations in other areas, recommendations pertaining specifically to the use of AI in the context of Clinical Outcome Assessment (COA ...
Shawn McKown +14 more
doaj +2 more sources
This article reports on how international organisations could appropriate the deliberative approach in their efforts to ethically regulate AI by presenting the meta-project.
Pauline Noiseau +6 more
doaj +1 more source
Conversational recommendation: A grand AI challenge
AbstractAnimated avatars, which look and talk like humans, are iconic visions of the future of AI‐powered systems. Through many sci‐fi movies, we are acquainted with the idea of speaking to such virtual personalities as if they were humans. Today, we talk more and more to machines like Apple's Siri, for example, to ask them for the weather forecast ...
Dietmar Jannach, Li Chen
openaire +3 more sources
Recommendations for ethical and responsible use of artificial intelligence in digital agriculture
Artificial intelligence (AI) applications are an integral and emerging component of digital agriculture. AI can help ensure sustainable production in agriculture by enhancing agricultural operations and decision-making.
Rozita Dara +2 more
doaj +1 more source
U.S. AI Workforce: Policy Recommendations [PDF]
This policy brief addresses the need for a clearly defined artificial intelligence education and workforce policy by providing recommendations designed to grow, sustain, and diversify the U.S. AI workforce. The authors employ a comprehensive definition of the AI workforce—technical and nontechnical occupations—and provide data-driven policy goals ...
Diana Gehlhaus +3 more
openaire +1 more source
Humans inherit artificial intelligence biases
Artificial intelligence recommendations are sometimes erroneous and biased. In our research, we hypothesized that people who perform a (simulated) medical diagnostic task assisted by a biased AI system will reproduce the model's bias in their own ...
Lucía Vicente, Helena Matute
doaj +1 more source
Mitigating the impact of biased artificial intelligence in emergency decision-making
Adam et al. evaluate the impact of biased AI recommendations on emergency decisions made by respondents to mental health crises. They find that descriptive rather than prescriptive recommendations made by the AI decision support system are more likely to
Hammaad Adam +4 more
doaj +1 more source
Semantic data ingestion for intelligent, value-driven big data analytics [PDF]
In this position paper we describe a conceptual model for intelligent Big Data analytics based on both semantic and machine learning AI techniques (called AI ensembles).
Attard, Judie +2 more
core +1 more source

