Swooping down on algorithms

Synopsis: China’s draft rules on regulating recommendation algorithms address pressing issues. Lessons for India.

Introduction

China has pursued aggressive measures in its tech sector in the past few months. A host of legislative instruments are in the process of being adopted, including the Personal Information Protection Law, the Cybersecurity Law, and the draft Internet Information Service Algorithm Recommendation Management Provisions.

The Management Provisions, released by the Cyberspace Administration of China, are possibly the most interesting and groundbreaking interventions among the new set of legislative instruments.

What are China’s management provisions?

The draft Internet Information Service Algorithm Recommendation Management Provisions lay down the processes and mandates for the regulation of recommendation algorithms.

Provisions attempt to address the concerns of individuals and society such as user autonomy, economic harms, discrimination, and the prevalence of false information.

The draft says users should be allowed to audit and change the user tags employed by the algorithms to filter content to be presented to them.

Through this, the draft aims to limit classifications that the user finds objectionable, thereby allowing the user to choose what to be presented with. This also has ripple effects in platformised gig work, where the gig worker can understand the basis of gigs presented to her.

What are recommendation algorithms?

Recommendation algorithms are widely employed in e-commerce platforms, social media feeds and gig work platforms.

How do recommendation algorithms work?

Such an algorithm helps a user navigate information overload and presents content that it deems more relevant to the user.

These algorithms learn from user demographics, behavioral patterns, location of the user, the interests of other users accessing similar content, etc., to deliver content.

What are some negative implications of such algorithms?

Such recommendation algorithms limit user autonomy, as the user has little opportunity to choose what content to be presented with.

Algorithms tend to have certain inherent biases which are learned from their modelling or the data they encounter. This often leads to discriminatory practices against users.

What lessons can India take from this?

Regulating algorithms is unavoidable and necessary. The world is lagging in such initiatives and China is hoping to emerge as a leader. The regulatory mechanism institutionalises algorithmic audits and supervision, a probable first in the world.

It is high time for India to invest better and speed up legislative action on the regulation of data, and initiate a conversation around the regulation of algorithms. India should strive to achieve this without copying China.

India must act fast to resolve the legal and social ills of algorithmic decision-making.

Policymakers should ensure that freedoms, rights and social security, and not rhetoric, inform policy changes.

What is the way forward?

Algorithms are as fundamental to the modern economy as engines to the industrial economy. A one-size-fits-all algorithm regulation fails to take into account the dynamic nature of markets.

An ideal regime should have goals-based legislation that can lay down the regulatory norms for algorithms. Such legislation must aim to lay down normative standards that algorithmic decision-making must adhere to.

This should be complemented by sectoral regulation that accounts for the complexities of markets.

Source: This post is based on the article “Swooping down on algorithms” published in The Hindu on 22nd Sep 2021.