Abstract Machine learning has become the state-of-the-art technique for many tasks
including computer vision, natural language processing, speech processing tasks, etc …

Many organizations have published principles intended to guide the ethical development
and deployment of AI systems; however, their abstract nature makes them difficult to …

We present DRESS a large vision language model (LVLM) that innovatively exploits Natural
Language feedback (NLF) from Large Language Models to enhance its alignment and …

Using our moral and technical imaginations to create responsible innovations: theory,
method, and applications for value sensitive design. Implantable medical devices and …

Along with potential benefits to healthcare delivery, machine learning healthcare
applications (ML-HCAs) raise a number of ethical concerns. Ethical evaluations of ML-HCAs …

As issues of technology ethics become more pervasive in the media and public discussions,
there is increasing interest in what role ethics should play in computing education. Not only …

User engagement with data privacy and security through consent banners has become a
ubiquitous part of interacting with internet services. While previous work has addressed …

As a descriptor, artificial intelligence (AI) is polysemous and problematic. Like the muddled
“big data” before it, this term du jour tends to be invoked broadly and haphazardly, by …

This article presents the findings of a systematic qualitative analysis of research in the ethics
of digital trace data use in learning and education. From the resulting analysis of 77 peer …

Recently, the AI/ML research community has indicated an urgent need to establish
Responsible AI (RAI) values and practices as part of the AI/ML lifecycle. Several …