Ethics at the human-machine interface: Brain-Computer Interfaces and Neuroethics

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Explores the ethical challenges of artificial intelligence, including explainability, security, singularity, and societal impact.

Explores the ethical challenges of AI, including data ethics, algorithm ethics, and societal impact.

Explores user management in digital humanities, focusing on modeling, motivation, and engagement, with insights from Twitter, Quora, and Wikipedia.

Presents the Master in Neuro-X program, emphasizing its interdisciplinary approach and career opportunities in neurotechnology.

Covers the ethical implications of artificial intelligence in technology, focusing on data, algorithms, design, sustainability, and accountability.

Explores social media analysis for emergency response and digital volunteerism tools.

Explores Brain-Machine Interfaces for motor control and communication using neural signals.

Delves into decolonising collections through AI-generated technoheritage and artistic explorations in synthetic image-making.

Covers the fundamentals of machine learning for physicists and chemists, focusing on image classification tasks using artificial intelligence.

Introduces translational neuroengineering, emphasizing the integration of neuroscience and technology for effective patient treatment.