scholarly journals Classification of Causal Structure in Plecoglossus altivelis via Integrated Information Theory

2021 ◽  
Vol 61 (1) ◽  
pp. 027-029
Author(s):  
Takayuki NIIZATO
Keyword(s):  
Information Theory ◽  
Causal Structure ◽  
Plecoglossus Altivelis ◽  
Integrated Information Theory ◽  
Integrated Information

scholarly journals New Classification of Collective Animal Behaviour as an Autonomous System

2019 ◽  
Author(s):  
Takayuki Niizato ◽  
Kotaro Sakamoto ◽  
Yoh-ichi Mototake ◽  
Hisashi Murakami ◽  
Takenori Tomaru ◽  
...  
Keyword(s):  
Time Scale ◽  
Autonomous System ◽  
Brain Network ◽  
Collective Behaviour ◽  
New Classification ◽  
Plecoglossus Altivelis ◽  
Fish Schools ◽  
Integrated Information Theory ◽  
Integrated Information

Integrated information theory (IIT) was initially proposed to describe human consciousness in terms of intrinsic, causal brain-network structures. This theory has the potential to be useful for conceptualising complex living systems. In a previous study, we analysed collective behaviour in Plecoglossus altivelis and found that IIT 3.0 exhibits qualitative discontinuity between three and four fish. Other measures like mutual information did not have such characteristics. In this study, we followed up on our previous findings and examined timescale effects on integrated information of collective behaviour. We found that a long timescale (1 s) causes Boid-like local interactions to dominate over interactions with the whole, but only when the group size is five at a given time scale (i.e. around 0.2 s). Interestingly, the most suitable time scale is roughly equal to fish reaction time. We used these data to propose a new classification for fish schools, with each size group being a unique and autonomous system, despite small group sizes.

scholarly journals Awareness and integrated information theory identify plant meristems as sites of conscious activity

PROTOPLASMA ◽  
2021 ◽  
Author(s):  
Anthony Trewavas
Keyword(s):  
Information Theory ◽  
Nervous System ◽  
Complex Networks ◽  
Environmental Changes ◽  
Biological Function ◽  
Human Consciousness ◽  
Extrinsic Information ◽  
Integrated Information Theory ◽  
Conscious Activity ◽  
Integrated Information

AbstractLacking an anatomical brain/nervous system, it is assumed plants are not conscious. The biological function of consciousness is an input to behaviour; it is adaptive (subject to selection) and based on information. Complex language makes human consciousness unique. Consciousness is equated to awareness. All organisms are aware of their surroundings, modifying their behaviour to improve survival. Awareness requires assessment too. The mechanisms of animal assessment are neural while molecular and electrical in plants. Awareness of plants being also consciousness may resolve controversy. The integrated information theory (IIT), a leading theory of consciousness, is also blind to brains, nerves and synapses. The integrated information theory indicates plant awareness involves information of two kinds: (1) communicative, extrinsic information as a result of the perception of environmental changes and (2) integrated intrinsic information located in the shoot and root meristems and possibly cambium. The combination of information constructs an information nexus in the meristems leading to assessment and behaviour. The interpretation of integrated information in meristems probably involves the complex networks built around [Ca2+]i that also enable plant learning, memory and intelligent activities. A mature plant contains a large number of conjoined, conscious or aware, meristems possibly unique in the living kingdom.

How to Catch an AI Zombie

2020 ◽  
pp. 439-458
Author(s):  
Susan Schneider
Keyword(s):  
Information Theory ◽  
Natural Language ◽  
Real World ◽  
Phenomenal Consciousness ◽  
Artificial Consciousness ◽  
High Level ◽  
Integrated Information Theory ◽  
Integrated Information

How can we determine if AI is conscious? The chapter begins by illustrating that there are potentially very serious real-world costs to getting facts about AI consciousness wrong. It then proposes a provisional framework for investigating artificial consciousness that involves several tests or markers. One test is the AI Consciousness Test, which challenges an AI with a series of increasingly demanding natural-language interactions. Another test is based on the Integrated Information Theory, developed by Giulio Tononi and others, and considers whether a machine has a high level of “integrated information.” A third test is a Chip Test, where speculatively an individual’s brain is gradually replaced with durable microchips. If this individual being tested continues to report having phenomenal consciousness, the chapter argues that this could be a reason to believe that some machines could have consciousness.

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