Artificial Consciousness: Misconception(s) of a Self-Fulfilling Prophecy Nobody Wants DOI Open Access
Birgitta Dresp

Qeios, Год журнала: 2023, Номер unknown

Опубликована: Ноя. 29, 2023

The rise of Artificial Intelligence (AI) has produced prophets and prophecies announcing that the age artificial consciousness is near. Not only does mere idea any machine could ever possess full potential human suggest AI replace role God in future, it also puts into question fundamental right to freedom dignity. Yet, light all we currently know about brain evolution adaptive neural dynamics underlying consciousness, an appears misconceived. This article highlights some major reasons why prophecy a successful emulation by ignores most data processes learning memory as developmental origins consciousness. analysis provided leads conclude epigenetically determined unique property mind, shaped experience, capable representing real non-real world states creatively projecting these representations future. development circuitry enables this expression highly context-dependent, multiple self-organizing functional interactions at different levels integration displaying from-local-to global organization. Human subject changes time are essentially unpredictable. If cracking computational code were possible, resulting algorithms would have be able generate temporal activity patterns simulating long-distance signal reverberation brain, de-correlation spatial contents from their signatures brain. In scientific evidence for complex between implicit (non-conscious) explicit (conscious) learning, memory, construction conscious such making processing explicit. Algorithms progressive less arbitrary selection continuously developing network structure functionally identical synapses higher cognitive integration. capacities experience. consolidation or extinction driven external event probabilities according principles Hebbian learning. constantly fed generating stable despite incommensurable amount variability input data, across individuals, life-long experience data. require probabilistic computations emulating individual No likely potential.

Язык: Английский

Spatiotemporal Modeling of Grip Forces Captures Proficiency in Manual Robot Control DOI Creative Commons
Rongrong Liu, John M. Wandeto, Florent Nageotte

и другие.

Bioengineering, Год журнала: 2023, Номер 10(1), С. 59 - 59

Опубликована: Янв. 3, 2023

This paper builds on our previous work by exploiting Artificial Intelligence to predict individual grip force variability in manual robot control. Grip forces were recorded from various loci the dominant and non hands of individuals means wearable wireless sensor technology. Statistical analyses bring fore skill specific temporal variations thousands a complete novice highly proficient expert A brain inspired neural network model that uses output metric Self Organizing Map with unsupervised winner take all learning was run both each user. The expresses difference between an input representation its at any given moment time t reliably captures differences performance terms variability.Functionally motivated spatiotemporal analysis average forces, computed for windows constant size restricted amount task-relevant sensors (preferred) hand, reveal finger-specific synergies reflecting robotic task skill. lead way towards monitoring real permit tracking evolution trainees, or identify proficiency levels human interaction environmental contexts high sensory uncertainty. Parsimonious (AI) assistance will contribute outcome new types surgery, particular single-port approaches such as NOTES (Natural Orifice Transluminal Endoscopic Surgery) SILS (Single Incision Laparoscopic Surgery).

Язык: Английский

Процитировано

8

The Grossberg Code: Universal Neural Network Signatures of Perceptual Experience DOI Creative Commons
Birgitta Dresp

Information, Год журнала: 2023, Номер 14(2), С. 82 - 82

Опубликована: Фев. 1, 2023

Two universal functional principles of Grossberg’s Adaptive Resonance Theory decipher the brain code all biological learning and adaptive intelligence. Low-level representations multisensory stimuli in their immediate environmental context are formed on basis bottom-up activation under control top-down matching rules that integrate high-level, long-term traces contextual configuration. These coding lead to establishment lasting signatures perceptual experience living species, from aplysiae primates. They re-visited this concept paper examples drawn original some most recent related empirical findings modulation brain, highlighting potential pioneering insights groundbreaking theoretical work for intelligent solutions domain developmental cognitive robotics.

Язык: Английский

Процитировано

6

Sensory Factors Influence Dynamic and Static Bi-Manual Finger Grip Strength in a Real-World Task Context DOI Creative Commons
Birgitta Dresp, Rongrong Liu, Michel de Mathelin

и другие.

Applied Sciences, Год журнала: 2024, Номер 14(9), С. 3548 - 3548

Опубликована: Апрель 23, 2024

Individual grip strength provides a functional window into somatosensory processes and their effects on motor behaviour in healthy, impaired, ageing individuals. Variations during hand–tool interaction are therefore exploited variety of experimental tasks to study the pathology or ageing-related changes sensory, motor, cognitive ability. However, many different factors may influence individual systematically given task context without being explicitly identified controlled for. Grip vary as function location measurement device (sensor) fingers/hand, shape, weight size object(s) gripped, type investigated (static versus dynamic grip), hand (dominant non-dominant) used for gripping. This tests additional such sight, sound, interactions with/between any other complex context. A wearable biosensor system, designed measuring variations operators gripping cylindrical objects bi-manually, was used. force signals were recorded from all sensors (glove) including three directly task-relevant bi-manually with dominant non-dominant hands. Five young male participants tested movement, sight strength. The had pick up two identical weight, then hold them still grip) move upwards downwards (dynamic ten seconds while listening soft hard music, eyes open blindfolded. Significant sensor location, hand, sound bi-manual found. Stronger produced by when moving handles comparison static condition, depending, expected, whether measured hand. Significantly weaker blindfolded (sight condition), grips significantly stronger exposure harder music (sound factor). It is concluded that influenced sensory between for, pointing towards need identifying controlling potential sources variation contexts.

Язык: Английский

Процитировано

0

Measures of Maximal Tactile Pressures during a Sustained Grasp Task Using a TactArray Device Have Satisfactory Reliability and Concurrent Validity in People with Stroke DOI Creative Commons
Urvashy Gopaul, Derek R. Laver, Leeanne M. Carey

и другие.

Sensors, Год журнала: 2023, Номер 23(6), С. 3291 - 3291

Опубликована: Март 20, 2023

Sensor-based devices can record pressure or force over time during grasping and therefore offer a more comprehensive approach to quantifying grip strength sustained contractions. The objectives of this study were investigate the reliability concurrent validity measures maximal tactile pressures forces grasp task using TactArray device in people with stroke. Participants stroke (n = 11) performed three trials 8 s. Both hands tested within- between-day sessions, without vision. Measures measured for complete (8 s) duration plateau phase (5 s). Tactile are reported highest value among trials, mean two trials. Reliability was determined changes mean, coefficients variation, intraclass correlation (ICCs). Pearson used evaluate validity. This found that assessed by means good, variation good acceptable, ICCs very average s affected hand vision within-day sessions sessions. In less hand, variations 5 s, respectively, Maximal had moderate correlations strength. demonstrates satisfactory

Язык: Английский

Процитировано

1

Artificial Consciousness: Misconception(s) of a Self-Fulfilling Prophecy Nobody Wants DOI Open Access
Birgitta Dresp

Qeios, Год журнала: 2023, Номер unknown

Опубликована: Дек. 16, 2023

The rise of Artificial Intelligence (AI) has produced prophets and prophecies announcing that the age artificial consciousness is near. Not only does mere idea any machine could ever possess full potential human suggest AI replace role God in future, it also puts into question fundamental right to freedom dignity. This position paper takes stand that, light all we currently know about brain evolution never-stopping formation adaptive neural circuitry for learning, memory, decision making and, ultimately, fully conscious reasoning creativity species, an appears misconceived. highlights some major reasons why. While awareness external stimuli processes such as perception, recognition, operational problem solving under direct control functionally specific networks associated with sensory cognitive functions across animal a unique property mind. Potentiated by evolution, come be when humans became able represent, reflect on, Self relation past, present project these representations possible worlds drawing other forms conceptual creative expression. Epigenetically determined, shaped experience, capable representing real non-real world states, enabled context-dependent circuits have evolved on grounds self-organizing functional interactions at different levels integration from-local-to global design. latter being continuous, limits are unpredictable. If cracking computational code were possible, resulting algorithms would generate temporal activity patterns simulating long-distance signal reverberation de-correlation spatial contents from their signatures. In scientific evidence complex between implicit (non-conscious) explicit (conscious) construction representation, processing explicit. Algorithms progressive, less arbitrary selection continuously developing network structure akin brain, synapses higher integration. capacities signatures phenomenal consciousness. biological consolidation or extinction driven event probabilities according principles Hebbian learning. Consciousness constantly fed generating stable despite incommensurable amount variability input data, time individuals, life-long experience data. require probabilistic computations emulating dynamics learning memory enable intelligence creativity. No likely potential.

Язык: Английский

Процитировано

1

Artificial Consciousness: Misconception(s) of a Self-Fulfilling Prophecy Nobody Wants DOI Open Access
Birgitta Dresp

Qeios, Год журнала: 2023, Номер unknown

Опубликована: Ноя. 29, 2023

The rise of Artificial Intelligence (AI) has produced prophets and prophecies announcing that the age artificial consciousness is near. Not only does mere idea any machine could ever possess full potential human suggest AI replace role God in future, it also puts into question fundamental right to freedom dignity. Yet, light all we currently know about brain evolution adaptive neural dynamics underlying consciousness, an appears misconceived. This article highlights some major reasons why prophecy a successful emulation by ignores most data processes learning memory as developmental origins consciousness. analysis provided leads conclude epigenetically determined unique property mind, shaped experience, capable representing real non-real world states creatively projecting these representations future. development circuitry enables this expression highly context-dependent, multiple self-organizing functional interactions at different levels integration displaying from-local-to global organization. Human subject changes time are essentially unpredictable. If cracking computational code were possible, resulting algorithms would have be able generate temporal activity patterns simulating long-distance signal reverberation brain, de-correlation spatial contents from their signatures brain. In scientific evidence for complex between implicit (non-conscious) explicit (conscious) learning, memory, construction conscious such making processing explicit. Algorithms progressive less arbitrary selection continuously developing network structure functionally identical synapses higher cognitive integration. capacities experience. consolidation or extinction driven external event probabilities according principles Hebbian learning. constantly fed generating stable despite incommensurable amount variability input data, across individuals, life-long experience data. require probabilistic computations emulating individual No likely potential.

Язык: Английский

Процитировано

0