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Machine ethics (or machine morality, computational morality, or computational ethics) is a part of the ethics of artificial intelligence concerned with adding or ensuring moral behaviors of man-made machines that use artificial intelligence, otherwise known as artificial intelligent agents. [1]
The problem of bias in machine learning is likely to become more significant as the technology spreads to critical areas like medicine and law, and as more people without a deep technical understanding are tasked with deploying it. [35] Some open-sourced tools are looking to bring more awareness to AI biases. [36]
Fairness in machine learning (ML) refers to the various attempts to correct algorithmic bias in automated decision processes based on ML models. Decisions made by such models after a learning process may be considered unfair if they were based on variables considered sensitive (e.g., gender, ethnicity, sexual orientation, or disability).
A machine learning model is a type of mathematical model that, ... Machine learning ethics is becoming a field of study and notably, becoming integrated within ...
A public administration approach sees a relationship between AI law and regulation, the ethics of AI, and 'AI society', defined as workforce substitution and transformation, social acceptance and trust in AI, and the transformation of human to machine interaction. [32]
Turing's "polite convention": If a machine behaves as intelligently as a human being, then it is as intelligent as a human being. [6] The Dartmouth proposal: "Every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it." [7]
The Machine Question: Critical Perspectives on AI, Robots, and Ethics is a 2012 nonfiction book by David J. Gunkel that discusses the evolution of the theory of human ethical responsibilities toward non-human things and to what extent intelligent, autonomous machines can be considered to have legitimate moral responsibilities and what legitimate claims to moral consideration they can hold.
One question in machine ethics is what alignment should accomplish: whether AI systems should follow the programmers' literal instructions, implicit intentions, revealed preferences, preferences the programmers would have if they were more informed or rational, or objective moral standards. [40]