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Reciprocal human machine learning

Index Reciprocal human machine learning

Reciprocal Human Machine Learning (RHML) is an interdisciplinary approach to designing human-AI interaction systems. [1]

Table of Contents

  1. 6 relations: Computer security, Human-in-the-loop, Logistics, Machine learning, Open science, Production (economics).

Computer security

Computer security (also cybersecurity, digital security, or information technology (IT) security) is the protection of computer systems and networks from threats that may result in unauthorized information disclosure, theft of (or damage to) hardware, software, or data, as well as from the disruption or misdirection of the services they provide.

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Human-in-the-loop

Human-in-the-loop (HITL) is used in multiple contexts. Reciprocal human machine learning and Human-in-the-loop are Machine learning.

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Logistics

Logistics is the part of supply chain management that deals with the efficient forward and reverse flow of goods, services, and related information from the point of origin to the point of consumption according to the needs of customers.

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Machine learning

Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data and thus perform tasks without explicit instructions.

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Open science

Open science is the movement to make scientific research (including publications, data, physical samples, and software) and its dissemination accessible to all levels of society, amateur or professional.

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Production (economics)

Production is the process of combining various inputs, both material (such as metal, wood, glass, or plastics) and immaterial (such as plans, or knowledge) in order to create output.

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References

[1] https://en.wikipedia.org/wiki/Reciprocal_human_machine_learning