AI people have spent a lot of time trying to get systems to reason about the real world. These studies are lumped into the categories of common-sense knowledge and naive physics. Both have not got so far because it's proven hard to encode all the factors that go into real world decisions. Current AI models are a partial take on a part of the real world, this is why you get poor recognition rates if you feed photos taken from odd angles or with unexpected objects in them into deep learned systems.

So the algorithmic objective decisions of current systems are actually partial and selective. We must be very careful not to attribute powers to them that they do not have. They can provide useful tools, but they are not the locus of decision making; that rests in the place that they were created, and may be distorted by either accident or design.