Artificial Intelligence (AI) is a modern technology system which is getting a robust buzz around the globe for its top-notch functionality in improving efficiency and performance at work. Generative AI is the sector with excessive use and adaptability, leading to the development of AI-powered tools for increased productivity.
Though the technology itself is an excellent support to the human workforce, the fear it has created among professionals and content creators is alarming. With the multifaceted use of AI and its tools, it may offer several loopholes to the entire industry. Some AI chatbots have been used for web scraping to get copyrighted content, raising a level of concern for authors and content creators.
It ignited a massive protest against AI in various parts of the world, including India. The Indian tech experts named AI as racist, sexist, and casteist after the communal riots in the Indian capital, Delhi, last year. The use of AI in the facial recognition system during the investigation of the riot led to the arrests of minorities and marginalised groups in India. Consequently, AI embraced the blame for the arrests of these groups, as reflected in the countrywide protest.
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Is AI Bad News for India?
The background and working of AI is a required task to understand before you answer the credibility of AI in any part of the world. As a modern technology with top-notch potential, AI is a revolutionary innovation in the tech landscape. It has human-like intellect to decide and communicate with human personalities, thanks to Machine Learning (ML) algorithms and other technologies.
These algorithms make the AI model, which analyses data patterns and provides an outcome with swiftness, accuracy, and precision. The problem people have with AI is its ML algorithms, which train on the available data to make futuristic decisions based on the patterns and trends in the data.
AI and generative AI have applications in almost every industry, including medicine, drug development, automation, education, Customer Relationship Management (CRM), and so on. It converges to the data used in developing AI and ML algorithms, which needs to be coherent, accurate, and unbiased. Biassed data will lead to an AI system working for the wrong cause, as happened in India.
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AI-Powered Facial Recognition Technology in India

India has introduced facial recognition technology to the investigation of the culprits and perpetrators of the ethnic riot that happened in Delhi’s Jahangirpuri in 2022. Since India is a highly crowded country in the Asian continent, it is home to several ethnic and religious groups, with the Hindus being the majority.
After the violent riot, police identified and arrested dozens of people as directly or indirectly involved in the peace-challenging incident. Among the accused people, the majority belonged to the Muslims and the Dalits. A Dalit is a historically marginalised group of Hindus with the lowest rank in the Hindu caste system.
Since the facial recognition system employed by Indian police was AI-powered, human rights activists and tech experts considered this act unethical and discriminated against minorities in India. It is due to the fact that minorities are usually labelled as alarming in India, and the AI model trained with biassed data will result in such consequences, necessitating the need for transparent and responsible AI development.
AI and Data Diversity
The incident in India opened the portal for discussion about bringing ethical guidelines to the development of AI as it may bring harm to the existing social groups due to a lack of data diversity. The facial recognition technology used by the Indian police is among the many AI applications with a database fueled by discrimination against marginalised groups of society.
Shivangi Narayan, a member of the Algorithmic Governance Research Network, raised his voice against AI risks. AI poses several risks to the future of humanity if it continues without bringing data diversity to its models, as forecasted by the Godfather of AI, Geoffrey Hinton. Click here to learn more about Hinton’s five scary warnings about AI risks.
Data diversity refers to broader data research and surveys when training the AI models, bringing excellent results in every industry, such as drug development, investigation, legal system, and so on. Data diversity in AI models will eliminate the sufferings of minorities, Dalits, trans people, and oppressed populations. Only this step will conclude in fulfilling the true purpose of AI, which is boosting efficiency and productivity.
Regulations Regarding AI Worldwide

Since the inception of AI, it has exposed the conventional world to several challenges and problems, including privacy concerns, security, and discrimination. A survey in the U.S. reflects that around 74 per cent of adults have data privacy concerns due to AI. Globally, governments are trying to deal with these issues, and they have compelled AI companies to comply with their AI guidelines.
It is worth noting that AI generates results based on its algorithm, and human developers and engineers write algorithms. Thus, the problem is not with the AI system but with those high-caste programmers and developers fueling such acts of unfairness and discrimination. Given such scenarios, governments and global organisations must bring these concerns to the table.
The Federal Communications Commission (FCC) has proposed regulatory reforms for the fair use of the Internet and AI. As technology is the driving force of modern operations, its development and deployment must be neutral and unbiased to ensure everyone’s involvement. Read further about the proposed rules by the FCC here.
A Reform in Existing AI Model Pratices are Needed
Human rights activists in India have protested against AI and its biassed algorithms amid the arrests of many minor groups during the police investigation of communal clashes in Delhi since the arrests were made after the employment of facial recognition technology, which used AI to analyse the data.
Protesters have labelled AI as racist, sexist, and casteist for its discriminating information about marginalised groups in India. It led to an immense need to reform the existing AI models. Protesters demand the government to introduce ethical guidelines for the fair and secure use of AI.
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