  Experts in Artificial Intelligence (AI) development predict that advances in
the development of intelligent systems and agents will reshape vital areas in
our society. Nevertheless, if such an advance is not made prudently and
critically, reflexively, it can result in negative outcomes for humanity. For
this reason, several researchers in the area have developed a robust,
beneficial, and safe concept of AI for the preservation of humanity and the
environment. Currently, several of the open problems in the field of AI
research arise from the difficulty of avoiding unwanted behaviors of
intelligent agents and systems, and at the same time specifying what we really
want such systems to do, especially when we look for the possibility of
intelligent agents acting in several domains over the long term. It is of
utmost importance that artificial intelligent agents have their values aligned
with human values, given the fact that we cannot expect an AI to develop human
moral values simply because of its intelligence, as discussed in the
Orthogonality Thesis. Perhaps this difficulty comes from the way we are
addressing the problem of expressing objectives, values, and ends, using
representational cognitive methods. A solution to this problem would be the
dynamic approach proposed by Dreyfus, whose phenomenological philosophy shows
that the human experience of being-in-the-world in several aspects is not well
represented by the symbolic or connectionist cognitive method, especially in
regards to the question of learning values. A possible approach to this problem
would be to use theoretical models such as SED (situated embodied dynamics) to
address the values learning problem in AI.
