Relative rationality: Is machine rationality subjective?
This is an incremental philosophical exploration of rationality in AI, relevant to researchers in AI ethics and decision theory.
The paper investigates whether machine rationality is subjective, concluding that it is, based on the inherent limitations of information and processing in real-world decision-making.
Rational decision making in its linguistic description means making logical decisions. In essence, a rational agent optimally processes all relevant information to achieve its goal. Rationality has two elements and these are the use of relevant information and the efficient processing of such information. In reality, relevant information is incomplete, imperfect and the processing engine, which is a brain for humans, is suboptimal. Humans are risk averse rather than utility maximizers. In the real world, problems are predominantly non-convex and this makes the idea of rational decision-making fundamentally unachievable and Herbert Simon called this bounded rationality. There is a trade-off between the amount of information used for decision-making and the complexity of the decision model used. This explores whether machine rationality is subjective and concludes that indeed it is.