AI reshaping merit and the idea of meritocracy- Recalibrating merit in the age of Artificial Intelligence

Source: The post AI reshaping merit and the idea of meritocracy has been created, based on the article “Recalibrating merit in the age of Artificial Intelligence” published in “The Hindu” on 19th February 2024.

UPSC Syllabus Topic: GS paper 3- Science and technology- developing new technology.

News: The article discusses how meritocracy, where people succeed based on ability and effort, is changing. It explores different views on meritocracy’s impact, focusing on its problems and potential reforms. It also examines how AI complicates meritocracy by affecting jobs and increasing inequality.

What is meritocracy?

Meritocracy is a system where people’s success is based on their abilities and effort, not their background.

Critics of Meritocracy:

Michael Young, a British sociologist, foresaw a divided society based on intelligence and effort.

Michael Sandel, a political philosopher, argued it creates entitlement and resentment, harming social unity.

Post-structuralists believe ‘merit’ is biased and reinforces inequalities.

Adrian Wooldridge, a journalist and author, points out that it can become hereditary, limiting social mobility.

Merit of Meritocracy:

Initially, it promoted progress and social mobility.

Wooldridge believes in its fairness but suggests reforms like improved education access for the underprivileged.

How will AI be reshaping merit and the idea of meritocracy?

Redefining Human Merit: AI introduces non-human capabilities surpassing human intelligence in tasks and creativity, as shown by OpenAI’s Sora, making traditional metrics of merit less relevant.

Technology Access as Merit: Individuals with AI tools have an advantage, shifting merit to technology access rather than personal abilities.

Perpetuating Biases: AI, trained on historical data, can reinforce existing biases in hiring and other fields, disadvantaging marginalized groups.

Job Displacement: AI’s advanced capabilities, like early cancer detection as mentioned in a Nature Medicine paper, can replace skilled jobs, impacting both high and low-wage sectors.

Polarization of Workforce: AI pushes jobs towards high-skill, high-wage roles or low-skill, low-wage roles, increasing socioeconomic disparities.

Opaque Decision-making: The unclear nature of AI decision-making processes makes it hard to understand and challenge merit evaluations, undermining meritocracy’s transparency.

Way forward

To move forward, we need to redefine merit in the AI era, ensuring fair access to technology and education. Addressing AI’s biases and promoting transparency in AI decision-making are crucial. We should also focus on balancing workforce opportunities, supporting both high-skill and accessible low-skill jobs to mitigate socioeconomic disparities.

Question for practice:

Examine how AI is reshaping the concept of meritocracy and what are its potential implications?