  Information and communication technologies have accompanied our everyday life
for years. A steadily increasing number of computers, cameras, mobile devices,
etc. generate more and more data, but at the same time we realize that the data
can only partially be analyzed with classical approaches. The research and
development of methods based on artificial intelligence (AI) made enormous
progress in the area of interpretability of data in recent years. With growing
experience, both, the potential and limitations of these new technologies are
increasingly better understood. Typically, AI approaches start with the data
from which information and directions for action are derived. However, the
circumstances under which such data are collected and how they change over time
are rarely considered. A closer look at the sensors and their physical
properties within AI approaches will lead to more robust and widely applicable
algorithms. This holistic approach which considers entire signal chains from
the origin to a data product, "Sensor AI", is a highly relevant topic with
great potential. It will play a decisive role in autonomous driving as well as
in areas of automated production, predictive maintenance or space research. The
goal of this white paper is to establish "Sensor AI" as a dedicated research
topic. We want to exchange knowledge on the current state-of-the-art on Sensor
AI, to identify synergies among research groups and thus boost the
collaboration in this key technology for science and industry.
