Concept

Ethics of artificial intelligence

Related publications (63)

Explainability as fig leaf? An exploration of experts’ ethical expectations towards machine learning in psychiatry

The increasing implementation of programs supported by machine learning in medical contexts will affect psychiatry. It is crucial to accompany this development with careful ethical considerations informed by empirical research involving experts from the fi ...

2023

DRONE GAME THAT HIGHLIGHTS ETHICAL AND SUSTAINABILITY IMPLICATIONS OF DESIGN DECISIONS

Siara Ruth Isaac, Barbara Bruno, Gianni Lodetti

This paper reports on the development of a brief scenario-based challenge to prompt engineering students’ reflection about the broader impacts of their design decisions, and thereby increase their ethical sensitivity and motivation. The game scenario asks ...

CDIO conference proceedings2023

Probabilistic methods for neural combinatorial optimization

Nikolaos Karalias

The monumental progress in the development of machine learning models has led to a plethora of applications with transformative effects in engineering and science. This has also turned the attention of the research community towards the pursuit of construc ...

EPFL2023

Large-scale detection of marine debris in coastal areas with Sentinel-2

Devis Tuia, Marc Conrad Russwurm

Detecting and quantifying marine pollution and macroplastics is an increasingly pressing ecological issue that directly impacts ecology and human health. Here, remote sensing can provide reliable estimates of plastic pollution by regularly monitoring and d ...

2023

Comparison of regression techniques for generating surrogate models to predict the thermodynamic behavior of biomass gasification systems

François Maréchal, Daniel Alexander Florez Orrego, Meire Ellen Gorete Ribeiro Domingos, Julia Granacher

Biomass resources can play an important role in the energy transition, being a dynamic feedstock that can be transformed either into solid, liquid or gaseous fuels. Biomass gasification is a versatile way to convert waste into energy. In this work, the mod ...

2023

Comparison of regression techniques for generating surrogate models to predict the thermodynamic behavior of biomass gasification systems

François Maréchal, Daniel Alexander Florez Orrego, Meire Ellen Gorete Ribeiro Domingos, Julia Granacher

Biomass resources can play an important role in the energy transition, being a dynamic feedstock that can be transformed either into solid, liquid or gaseous fuels. The biomass gasification is a versatile way to convert wastes into energy. In this work, th ...

Elsevier2023

Yes but.. Can ChatGPT Identify Entities in Historical Documents?

Emanuela Boros, Ahmed Hamdi

Large language models (LLMs) have been leveraged for several years now, obtaining state-of-the-art performance in recognizing entities from modern documents. For the last few months, the conversational agent ChatGPT has "prompted" a lot of interest in the ...

New York2023

VP-STO: Via-point-based Stochastic Trajectory Optimization for Reactive Robot Behavior

Sylvain Calinon, Julius Maximilian Jankowski

Achieving reactive robot behavior in complex dynamic environments is still challenging as it relies on being able to solve trajectory optimization problems quickly enough, such that we can replan the future motion at frequencies which are sufficiently high ...

IEEE2023

The Digital Ethics Canvas: A Guide For Ethical Risk Assessment And Mitigation In The Digital Domain

Patrick Jermann, Cécile Hardebolle, Vivek Ramachandran, Vladimir Macko, Adrian Christian Holzer

Ethical concerns in the digital domain are growing with the extremely fast evolution of technology and the increasing scale at which software is deployed, potentially affecting our societies globally. It is crucial that engineers evaluate more systematical ...

2023

An exact mapping from ReLU networks to spiking neural networks

Wulfram Gerstner, Stanislaw Andrzej Wozniak, Ana Stanojevic, Giovanni Cherubini, Angeliki Pantazi

Deep spiking neural networks (SNNs) offer the promise of low-power artificial intelligence. However, training deep SNNs from scratch or converting deep artificial neural networks to SNNs without loss of performance has been a challenge. Here we propose an ...

2023

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