Use the future to build the present
Deeper Machine Learning
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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:

1.1.1Deeper Machine Learning

Artificial intelligence algorithms have become ubiquitous in modern life thanks to successes in machine learning research. However, they have very limited flexibility, operating within narrowly defined parameters and unable to transfer knowledge across domains. They also require vast amounts of training data and enormous computational resources. But there are reasons to believe that they can be made more flexible in the foreseeable future.10

The dramatic progress of recent years has resulted largely from increases in data availability and processing power, rather than advances in the fundamental theoretical foundations of artificial intelligence. If these foundations can be developed through targeted research, we will gain an understanding of what is missing from the current paradigm, and how it can be improved and its applications expanded — safely, and with human needs at the focus.

A stronger theoretical basis may also help us solve problems created by the current nature of AI. The field of explainable AI is aiming to create a better understanding of how ML algorithms work, with increased reliability and transparency.11 This will have an important impact on applications, as it will then be possible to deploy AI techniques in sensitive domains where liability is paramount (for example, the health, financial, legal and engineering spheres).12

Future Horizons:

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5-yearhorizon

Machine learning expands its sphere of operations

Further exponential growth in computing power and access to data enables an increase in performance. The current trend of digitalisation, including the deployment of sensors and connected objects, provides increasing scope and scale of data sets to be used by machine learning algorithms. Research begins to establish ethical and regulatory frameworks.

10-yearhorizon

Algorithms begin to generalise

The ability to incorporate basic knowledge and deductive reasoning helps algorithms to interpret their surroundings and make generalisations. This boosts the fields of unsupervised learning (using little or no training data) and reinforcement learning, expanding the scope and relevance of ML. Algorithms are increasingly able to learn from fewer examples.

25-yearhorizon

Machine learning becomes a tool for specialised enquiry

Deep machine learning continues to inform and instantiate progress in complex and abstract scientific fields of inquiry, although issues of explainability change the nature of what it means to “understand” scientific issues.

Deeper Machine Learning - 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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