Use the future to build the present
Hybrid Cognition
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1Quantum Revolution& Advanced AI2HumanAugmentation3Eco-Regeneration& Geo-Engineering4Science& Diplomacy1.11.21.31.42.12.22.32.43.13.23.33.43.54.14.24.34.44.5HIGHEST ANTICIPATIONPOTENTIALAdvancedArtificial IntelligenceQuantumTechnologiesBrain-inspiredComputingBiologicalComputingCognitiveEnhancementHuman Applications of Genetic EngineeringRadical HealthExtensionConsciousnessAugmentation DecarbonisationWorldSimulationFuture FoodSystemsSpaceResourcesOceanStewardshipComplex Systems forSocial EnhancementScience-basedDiplomacyInnovationsin EducationSustainableEconomicsCollaborativeScience Diplomacy
1Quantum Revolution& Advanced AI2HumanAugmentation3Eco-Regeneration& Geo-Engineering4Science& Diplomacy1.11.21.31.42.12.22.32.43.13.23.33.43.54.14.24.34.44.5HIGHEST ANTICIPATIONPOTENTIALAdvancedArtificial IntelligenceQuantumTechnologiesBrain-inspiredComputingBiologicalComputingCognitiveEnhancementHuman Applications of Genetic EngineeringRadical HealthExtensionConsciousnessAugmentation DecarbonisationWorldSimulationFuture FoodSystemsSpaceResourcesOceanStewardshipComplex Systems forSocial EnhancementScience-basedDiplomacyInnovationsin EducationSustainableEconomicsCollaborativeScience Diplomacy

Sub-Field:

2.1.3Hybrid Cognition

Among the most important drivers of cognitive enhancement will be advances in artificial intelligence. This will happen in two separate but related ways. First, machine learning algorithms will help academic researchers to sift quickly through large amounts of brain data. This will enable them to find relevant signals to help better understand principles of cognition and memory, and thus to develop better closed-loop devices.12 This approach has been used to decode primary visual cortical activity and reconstruct movie scenes as they are being viewed in real-time13, and to decode the content of dreams based on pre-recorded visual cortical activity patterns.14 It has yet to be applied to memory research, but potential applications include decoding memory encoding, retention, and retrieval. A separate line of research suggests that functional magnetic resonance imaging (fMRI) can be used to distinguish between true memories, false memories, and lies,15,16 and machine learning algorithms could potentially be applied to the analysis of such brain activity patterns.
The second advance will come through AI embedded in devices worn by consumers to extend their cognitive abilities. People already offload partial cognitive capacity to Google; this tendency will multiply as people wear more internet-connected and AI-enabled devices in their daily life. The scope of future applications is wide and includes downregulating undesirable brain states and tuning the brain for optimal task-specific performance.

Future Horizons:

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5-yearhorizon

AI stimulates discovery

Machine learning helps to find memory patterns in brain data coming out of clinical trials. This will stimulate discovery around early disease progression, or more controversially, decode in ever finer detail the content of our thoughts. It may even offer new insights around neuroscience and consciousness.

10-yearhorizon

Machine learning closes the loop

Closed-loop devices use machine learning algorithms to decode mental states and baseline brain activity and stimulate “on demand” without needing the intervention of a clinician. Machine learning also identifies brainwave patterns associated with useful stages of the sleep cycle. Closed-loop devices then amplify these oscillations to improve memory consolidation. Such devices are used to combat age-related cognitive decline, reducing the risk of developing Alzheimer’s Disease and other forms of dementia.

25-yearhorizon

AI integrated into memory and cognition

Closed-loop AI implants are widely adopted, and onboard AI seamlessly translates brain function and transforms cognition into commands, augmenting memory and cognition for increasing numbers of healthy people.

Hybrid Cognition - Anticipation Scores

How the experts see this field in terms of the expected time to maturity, transformational effect across science and industries, current state of awareness among stakeholders and its possible impact on people, society and the planet. See methodology for more information.

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