Search results
Results from the WOW.Com Content Network
The ethics of artificial intelligence covers a broad range of topics within the field that are considered to have particular ethical stakes. [1] This includes algorithmic biases, fairness, automated decision-making, accountability, privacy, and regulation.
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 philosophy of artificial intelligence is a branch of the philosophy of mind and the philosophy of computer science [1] that explores artificial intelligence and its implications for knowledge and understanding of intelligence, ethics, consciousness, epistemology, and free will.
A related field is the ethics of artificial intelligence, which addresses such problems as the existence of moral personhood of AIs, the possibility of moral obligations to AIs (for instance, the right of a possibly sentient computer system to not be turned off), and the question of making AIs that behave ethically towards humans and others.
Artificial Intelligence: Artificial Intelligence seems to be the one of the most talked of challenges when it comes ethics. In order to avoid these ethical challenges some solutions have been established; first and for most it should be developed for the common good and benefit of humanity. [27]
Robot ethics, sometimes known as "roboethics", concerns ethical problems that occur with robots, such as whether robots pose a threat to humans in the long or short run, whether some uses of robots are problematic (such as in healthcare or as 'killer robots' in war), and how robots should be designed such that they act 'ethically' (this last concern is also called machine ethics).
The ethics of artificial intelligence covers a broad range of topics within the field that are considered to have particular ethical stakes. [138] This includes algorithmic biases , fairness , automated decision-making , accountability , privacy , and regulation .
Artificial intelligence in education (AiEd) is another vague term, [4] and an interdisciplinary collection of fields which are bundled together, [5] inter alia anthropomorphism, generative artificial intelligence, data-driven decision-making, ai ethics, classroom surveillance, data-privacy and Ai Literacy. [6]