Inteligência natural baseada em significado vs inteligência artificial baseada em informação

quinta-feira, julho 30, 2009

Para ler e considerar cum granum salis:

Meaning-Based Natural Intelligence Vs. Information-Based Artificial Intelligence

Eshel Ben Jacob and Yoash Shapira
School of Physics and Astronomy
Raymond & Beverly Sackler Faculty of Exact Sciences
Tel Aviv University, 69978 Tel Aviv Israel


In this chapter, we reflect on the concept of Meaning-Based Natural Intelligence - a fundamental trait of Life shared by all organisms, from bacteria to humans, associated with: semantic and pragmatic communication, assignment and generation of meaning, formation of self-identity and of associated identity (i.e., of the group the individual belongs to), identification of natural intelligence, intentional behavior, decision-making and intentionally designed self-alterations. These features place the Meaning-Based natural Intelligence beyond the realm of Information-based Artificial Intelligence. Hence, organisms are beyond man-made pre-designed machinery and are distinguishable from non-living systems.

Our chain of reasoning begins with the simple distinction between intrinsic and extrinsic contextual causations for acquiring intelligence. The first, associated with natural intelligence, is required for the survival of the organism (the biotic system) that generates it.

In contrast, artificial intelligence is implemented externally to fulfill a purpose for the benefit of the organism that engineered the “Intelligent Machinery”. We explicitly propose that the ability to assign contextual meaning to externally gathered information is an essential requirement for survival, as it gives the organism the freedom of contextual decision-making.

By contextual, we mean relating to the external and internal states of the organism and the internally stored ontogenetic knowledge it has generated. We present the view that contextual interpretation of information and consequent decision-making are two fundamentals of natural intelligence that any living creature must have.

A distinction between extraction of information from data vs. extraction of meaning from information is drawn while trying to avoid the traps and pitfalls of the “meaning of meaning” and the “emergence of meaning” paradoxes. The assignment of meaning (internal interpretation) is associated with identifying correlations in the information according to the internal state of the organism, its external conditions and its purpose in gathering the information. Viewed this way, the assignment of meaning implies the existence of intrinsic meaning, against which the external information can be evaluated for extraction of meaning.

This leads to the recognition that the organism has self-identity. We present the view that the essential differences between natural intelligence and artificial intelligence are a testable reality, untested and ignored since it had been wrongly
perceived as inconsistent with the foundations of physics. We propose that the inconsistency arises within the current, gene-network picture of the Neo-Darwinian paradigm (that regards organisms as equivalent to a Turing machine) and not from in principle contradiction with physical reality. Once the ontological reality of organisms’ natural intelligence is verified, a paradigm shift should be considered, where inter- and intra-cellular communication and genome plasticity (based on junk DNA” and the abundance of transposable elements) play crucial roles. In this new paradigm, communication and gene plasticity might be able to sustain the organisms with regulated freedom of choice between different available responses.

There have been many attempts to attribute the cognitive abilities of organisms (e.g., consciousness) to underlying quantum-mechanical mechanisms, which can directly affect the ”mechanical” parts of the organism (i.e., atomic and molecular excitations) despite thermal noise. Here, organisms are viewed as continuously self-organizing open systems that store past information, external and internal. These features enable the macroscopic organisms to have features analogous to some features in quantum mechanical systems. Yet, they are essentially different and should not be mistaken to be a direct reflection of quantum effects.

On the conceptual level, the analogy is very useful as it can lead to some insights from the knowledge of quantum mechanics. We show, for example, how it enables to metaphorically bridge between the Aharonov-Vaidman and Aharonov-Albert-Vaidman concepts of Protective and Weak Measurements in quantum mechanics (no destruction of the quantum state) with Ben Jacob’s concept of Weak-Stress Measurements, (e.g., exposure to non-lethal levels of antibiotic) in the study of organisms. We also reflect on the metaphoric analogy between Aharonov-Anandan-Popescue-Vaidman Quantum Time-Translation Machine and the ability of an external observer to deduce on an organism’s decision-making vs. arbitrary fluctuations. Inspired by the concept of Quantum Non-Demolition measurements we propose to use biofluoremetry (the use of bio-compatible fluorescent molecules to study intracellular spatio-temporal organization and functional correlations) as a future methodology of Intracellular Non-Demolition Measurements. We propose that the latter, performed during Weak-Stress Measurements of the organism, can provide proper schemata to test the special features associated with natural intelligence.


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