Intelligence — Part IV

Artificial intelligence

Scholars studying artificial intelligence have proposed definitions of intelligence that include the intelligence demonstrated by machines. Some of these definitions are meant to be general enough to encompass human and other animal intelligence as well. An intelligent agent can be defined as a system that perceives its environment and takes actions which maximize its chances of success. Kaplan and Haenlein define artificial intelligence as «a system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation». Progress in artificial intelligence can be demonstrated in benchmarks ranging from games to practical tasks such as protein folding. Existing AI lags humans in terms of general intelligence, which is sometimes defined as the «capacity to learn how to carry out a huge range of tasks.

Singularitarian Eliezer Yudkowsky provides a loose qualitative definition of intelligence as «that sort of smartish stuff coming out of brains, which can play chess, and price bonds, and persuade people to buy bonds, and invent guns, and figure out gravity by looking at wandering lights in the sky; and which, if a machine intelligence had it in large quantities, might let it invent molecular nanotechnology; and so on». Mathematician Olle Häggström defines intelligence in terms of «optimization power», an agent’s capacity for efficient cross-domain optimization of the world according to the agent’s preferences, or more simply the ability to «steer the future into regions of possibility ranked high in a preference ordering». In this optimization framework, Deep Blue has the power to «steer a chessboard’s future into a subspace of possibility which it labels as ‘winning’, despite attempts by Garry Kasparov to steer the future elsewhere.» Hutter and Legg, after surveying the literature, define intelligence as «an agent’s ability to achieve goals in a wide range of environments». While cognitive ability is sometimes measured as a one-dimensional parameter, it could also be represented as a «hypersurface in a multidimensional space» to compare systems that are good at different intellectual tasks. Some skeptics believe that there is no meaningful way to define intelligence, aside from «just pointing to ourselves»

Plant intelligence

It has been argued that plants should also be classified as intelligent based on their ability to sense and model external and internal environments and adjust their morphology, physiology and phenotype accordingly to ensure self-preservation and reproduction.

A counter argument is that intelligence is commonly understood to involve the creation and use of persistent memories as opposed to computation that does not involve learning. If this is accepted as definitive of intelligence, then it includes the artificial intelligence of robots capable of «machine learning», but excludes those purely autonomic sense-reaction responses that can be observed in many plants. Plants are not limited to automated sensory-motor responses, however, they are capable of discriminating positive and negative experiences and of «learning» (registering memories) from their past experiences. They are also capable of communication, accurately computing their circumstances, using sophisticated cost–benefit analysis and taking tightly controlled actions to mitigate and control the diverse environmental stressors.