AI should be used to protect from 'toxicity' of social media: Chandrashekhar

Union minister of State for Information Technology Rajiv Chandrashekhar has said that the toxicity seen in social media and the tendency to weaponize it should be controlled and steps should be taken to make artificial intelligence (AI) a representative of goodness, security and trust.

Addressing the plenary session of the 'AI Security Conference' organized in Buckinghamshire, adjacent to London, Chandrashekhar said that the government is promoting innovative technology as a force to accelerate economic growth.

Describing AI as a 'dynamic enabler' for India's already growing digital economy, he said now is the time to increase accountability for technology platforms. He said, “Governments have seen over the last 10-15 years that by allowing innovation to go beyond regulation, we allow toxicity, misinformation and weaponization. Today in the internet era this is visible on social media. We can agree that we should not think about such a situation for AI in the future.

Referring to India's efforts towards a digital economy, Chandrashekhar said, "We definitely want AI and the broader internet and technology to reflect goodness, security and trust. For this, social media platforms and innovators will have to show comprehensive accountability towards users under the law.

Artificial intelligence is a field, which combines computer science and robust datasets, to enable problem-solving. It also encompasses sub-fields of machine learning and deep learning, which are frequently mentioned in conjunction with artificial intelligence. These disciplines are comprised of AI algorithms which seek to create expert systems which make predictions or classifications based on input data.

Over the years, artificial intelligence has gone through many cycles of hype, but even to skeptics, the release of OpenAI’s ChatGPT seems to mark a turning point. The last time generative AI loomed this large, the breakthroughs were in computer vision, but now the leap forward is in natural language processing. And it’s not just language: Generative models can also learn the grammar of software code, molecules, natural images, and a variety of other data types.