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Machine Unlearning UPSC NOTE

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  What is Machine Unlearning (MUL)? MUL refers to the process of removing the influence of specific training data points on an already trai...

 What is Machine Unlearning (MUL)?

  • MUL refers to the process of removing the influence of specific training data points on an already trained machine learning model

  • First mooted by Cao and Yang in ‘Towards Making Systems Forget with Machine Unlearning’

  • It is the antithesis of ML

  • An algorithm is added to the AI model for the purpose of identifying and deleting false, incorrect, discriminatory, outdated, and sensitive information

Solution or not

  • The concept builds on the challenge of removing information due to the constant churning of data by the Large Language Models (LLMs)

  • But it gets difficult to keep track of the data as it can be utilised for multiple objectives, creating a complex web of algorithms, also known as data lineage

  • It adversely affect its quality, leading to manipulation, adversarial outputs, and difficulty in locating and removing sensitive information

  • Moreover, as there is no sandbox approach for choosing and processing data in these models, 

    • there is also a proven possibility of hackers inserting manipulated data to produce biased results (data poisoning).

  • One might argue for simply deleting the entire data set, i.e. data pruning, and re-training the entire AI model. 

  • However, it will lead to inflated computational costs and undue delays for the data fiduciaries 

    • Simultaneously carrying the risk of losing substantial accuracy

How MUL model can be implemented to effectively 

  • 3 approaches : private, public, and international

  • In the private approach, data fiduciaries will be primarily responsible for testing MUL algorithms, 

    • which can then be applied across their training models for efficient deletion based on specific requirements

  • In the public approach, the government has the responsibility to prepare the statutory blueprint, either through soft-law or hard-law approaches, 

    • to obligate data fiduciaries to fulfil their legal obligations

  • The international approach emphasises the role of nation states in coming together and preparing a framework to be adopted uniformly at a domestic level

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Learnerz IAS | Concept oriented UPSC Classes in Malayalam: Machine Unlearning UPSC NOTE
Machine Unlearning UPSC NOTE
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Learnerz IAS | Concept oriented UPSC Classes in Malayalam
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