Given the importance of artificial assistance systems, the project examines their incorporation into the training process, from the perspective of human learning (cognitive sciences), machine learning (computer sciences), and by analyzing trust in AI partners (philosophy).

Digital, tactile sensors are increasingly being coupled with artificial intelligence to support people in their daily and professional activities, e.g., in lane-keeping assistants in cars or robots that support precision operations. Given the importance of artificial assistance systems, the project, from the perspective of cognitive sciences, computer sciences, and philosophy, examines their incorporation into the training process, as cooperative learning will also encompass hybrid pairs of human and artificial learners.

Using a novel interdisciplinary approach, the project team is investigating hybrid learning between human and AI for increasingly innovative tactile augmentations and assistance. For this, three different but complementary perspectives are integrated:

 

  • the cognitive neuroscience of human, biological learning through seeing and touching,
  • the philosophy of self-confidence and trust in digital tactile assistants,
  • the informatics design of machine learning algorithms tailored to tactile learning with AI.
  • The project also includes citizen science components from medicine and driving practice that will contribute to transferring the results into concrete application.
Team
John Dorsch
John Dorsch
Isabelle Ripp
Isabelle Ripp
Maximilian Moll
Maximilian Moll