We will argue that clarifying the “moral core” of consent offers a common metric by which we can evaluate how well different legal frameworks are able to protect the central moral rights and interests at stake. We begin by revisiting how legal frameworks for digital consent developed in order to see where there may be common moral ground and where these different cultures diverge on the issue of protection of personal information. We then turn to ethics to clarify the central (...) interests and rights at stake in morally transformative consent, in order to provide a common basis for evaluating the different legal frameworks. Ultimately, we seek the moral core of digital consent in order to reimagine its role in international conflicts. (shrink)

Today, artificial intelligence, especially machine learning, is structurally dependent on human participation. Technologies such as Deep Learning (DL) leverage networked media infrastructures and human-machine interaction designs to harness users to provide training and verification data. The emergence of DL is therefore based on a fundamental socio-technological transformation of the relationship between humans and machines. Rather than simulating human intelligence, DL-based AIs capture human cognitive abilities, so they are hybrid human-machine apparatuses. From a perspective of media philosophy and social-theoretical critique, I (...) differentiate five types of “media technologies of capture” in AI apparatuses and analyze them as forms of power relations between humans and machines. Finally, I argue that the current hype about AI implies a relational and distributed understanding of (human/artificial) intelligence, which I categorize under the term “cybernetic AI”. This form of AI manifests in socio-technological apparatuses that involve new modes of subjectivation, social control and discrimination of users. (shrink)