AI is transforming Indian call centers. What does it mean for workers?

GURGAON, India — For three years, Kartikeya Kumar hesitated before picking up the phone, anticipating another difficult conversation with another frustrated customer.
The call center agent, now 29, had tried everything to eliminate what a colleague called the 'Indian-ism' in his accent. He mimicked the dialogue from Marvel movies and belted out songs by Metallica and Pink Floyd. Relief finally arrived in the form of artificial intelligence.

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Your AI use could have a hidden environmental cost

Sign up for CNN's Life, But Greener newsletter. Our limited newsletter series guides you on how to minimize your personal role in the climate crisis — and reduce your eco-anxiety. Whether it's answering work emails or drafting wedding vows, generative artificial intelligence tools have become a trusty copilot in many people's lives. But a growing body of research shows that for every problem AI solves, hidden environmental costs are racking up. Each word in an AI prompt is broken down into clusters of numbers called 'token IDs' and sent to massive data centers — some larger than football fields — powered by coal or natural gas plants. There, stacks of large computers generate responses through dozens of rapid calculations. The whole process can take up to 10 times more energy to complete than a regular Google search, according to a frequently cited estimation by the Electric Power Research Institute. So, for each prompt you give AI, what's the damage? To find out, researchers in Germany tested 14 large language model (LLM) AI systems by asking them both free-response and multiple-choice questions. Complex questions produced up to six times more carbon dioxide emissions than questions with concise answers. In addition, 'smarter' LLMs with more reasoning abilities produced up to 50 times more carbon emissions than simpler systems to answer the same question, the study reported. 'This shows us the tradeoff between energy consumption and the accuracy of model performance,' said Maximilian Dauner, a doctoral student at Hochschule München University of Applied Sciences and first author of the Frontiers in Communication study published Wednesday. Typically, these smarter, more energy intensive LLMs have tens of billions more parameters — the biases used for processing token IDs — than smaller, more concise models. 'You can think of it like a neural network in the brain. The more neuron connections, the more thinking you can do to answer a question,' Dauner said. Complex questions require more energy in part because of the lengthy explanations many AI models are trained to provide, Dauner said. If you ask an AI chatbot to solve an algebra question for you, it may take you through the steps it took to find the answer, he said. 'AI expends a lot of energy being polite, especially if the user is polite, saying 'please' and 'thank you,'' Dauner explained. 'But this just makes their responses even longer, expending more energy to generate each word.' For this reason, Dauner suggests users be more straightforward when communicating with AI models. Specify the length of the answer you want and limit it to one or two sentences, or say you don't need an explanation at all. Most important, Dauner's study highlights that not all AI models are created equally, said Sasha Luccioni, the climate lead at AI company Hugging Face, in an email. Users looking to reduce their carbon footprint can be more intentional about which model they chose for which task. 'Task-specific models are often much smaller and more efficient, and just as good at any context-specific task,' Luccioni explained. If you are a software engineer who solves complex coding problems every day, an AI model suited for coding may be necessary. But for the average high school student who wants help with homework, relying on powerful AI tools is like using a nuclear-powered digital calculator. Even within the same AI company, different model offerings can vary in their reasoning power, so research what capabilities best suit your needs, Dauner said. When possible, Luccioni recommends going back to basic sources — online encyclopedias and phone calculators — to accomplish simple tasks. Putting a number on the environmental impact of AI has proved challenging. The study noted that energy consumption can vary based on the user's proximity to local energy grids and the hardware used to run AI partly why the researchers chose to represent carbon emissions within a range, Dauner said. Furthermore, many AI companies don't share information about their energy consumption — or details like server size or optimization techniques that could help researchers estimate energy consumption, said Shaolei Ren, an associate professor of electrical and computer engineering at the University of California, Riverside who studies AI's water consumption. 'You can't really say AI consumes this much energy or water on average — that's just not meaningful. We need to look at each individual model and then (examine what it uses) for each task,' Ren said. One way AI companies could be more transparent is by disclosing the amount of carbon emissions associated with each prompt, Dauner suggested. 'Generally, if people were more informed about the average (environmental) cost of generating a response, people would maybe start thinking, 'Is it really necessary to turn myself into an action figure just because I'm bored?' Or 'do I have to tell ChatGPT jokes because I have nothing to do?'' Dauner said. Additionally, as more companies push to add generative AI tools to their systems, people may not have much choice how or when they use the technology, Luccioni said. 'We don't need generative AI in web search. Nobody asked for AI chatbots in (messaging apps) or on social media,' Luccioni said. 'This race to stuff them into every single existing technology is truly infuriating, since it comes with real consequences to our planet.' With less available information about AI's resource usage, consumers have less choice, Ren said, adding that regulatory pressures for more transparency are unlikely to the United States anytime soon. Instead, the best hope for more energy-efficient AI may lie in the cost efficacy of using less energy. 'Overall, I'm still positive about (the future). There are many software engineers working hard to improve resource efficiency,' Ren said. 'Other industries consume a lot of energy too, but it's not a reason to suggest AI's environmental impact is not a problem. We should definitely pay attention.'

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OpenAI's Sam Altman Shocked ‘People Have a High Degree of Trust in ChatGPT' Because ‘It Should Be the Tech That You Don't Trust'

OpenAI CEO Sam Altman made remarks on the first episode of OpenAI's new podcast regarding the degree of trust people have in ChatGPT. Altman observed, 'People have a very high degree of trust in ChatGPT, which is interesting, because AI hallucinates. It should be the tech that you don't trust that much.' This candid admission comes at a time when AI's capabilities are still in their infancy. Billions of people around the world are now using artificial intelligence (AI), but as Altman says, it's not super reliable. Make Over a 2.4% One-Month Yield Shorting Nvidia Out-of-the-Money Puts Is Quantum Computing (QUBT) Stock a Buy on This Bold Technological Breakthrough? Is AMD Stock a Buy, Sell, or Hold on Untether AI Acquisition? Our exclusive Barchart Brief newsletter is your FREE midday guide to what's moving stocks, sectors, and investor sentiment - delivered right when you need the info most. Subscribe today! ChatGPT and similar large language models (LLMs) are known to 'hallucinate,' or generate plausible-sounding but incorrect or fabricated information. Despite this, millions of users rely on these tools for everything from research and work to personal advice and parenting guidance. Altman himself described using ChatGPT extensively for parenting questions during his son's early months, acknowledging both its utility and the risks inherent in trusting an AI that can be confidently wrong. Altman's observation points to a paradox at the heart of the AI revolution: while users are increasingly aware that AI can make mistakes, the convenience, speed, and conversational fluency of tools like ChatGPT have fostered a level of trust more commonly associated with human experts or close friends. This trust is amplified by the AI's ability to remember context, personalize responses, and provide help across a broad range of topics — features that Altman and others at OpenAI believe will only deepen as the technology improves. Yet, as Altman cautioned, this trust is not always well-placed. The risk of over-reliance on AI-generated content is particularly acute in high-stakes domains such as healthcare, legal advice, and education. While Altman praised ChatGPT's usefulness, he stressed the importance of user awareness and critical thinking, urging society to recognize that 'AI hallucinates' and should not be blindly trusted. The conversation also touched on broader issues of privacy, data retention, and monetization. As OpenAI explores new features — such as persistent memory and potential advertising products — Altman emphasized the need to maintain user trust by ensuring transparency and protecting privacy. The ongoing lawsuit with The New York Times over data retention and copyright has further highlighted the delicate balance between innovation, legal compliance, and user rights. On the date of publication, Caleb Naysmith did not have (either directly or indirectly) positions in any of the securities mentioned in this article. All information and data in this article is solely for informational purposes. This article was originally published on

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Media advisory - Minister Solomon to participate in Toronto Tech Week 2025

TORONTO, June 22, 2025 /CNW/ - The Honourable Evan Solomon, Minister of Artificial Intelligence and Digital Innovation and Minister responsible for the Federal Economic Development Agency for Southern Ontario, will participate in a series of events, meetings and visits with Canada's AI ecosystem and business leaders for Toronto Tech Week 2025. Minister Solomon to participate in a site visit at Xanadu Date: Monday, June 23, 2025 Time: 11:00 am (ET) Note: Members of the media are asked to contact ISED Media Relations at media@ to receive event location details and confirm their attendance. Stay connected Find more services and information on the Innovation, Science and Economic Development Canada website. Follow Innovation, Science and Economic Development Canada on social media.X (Twitter): @ISED_CA, Facebook: Canadian Innovation, Instagram: @cdninnovation, LinkedIn: Innovation, Science and Economic Development Canada SOURCE Innovation, Science and Economic Development Canada View original content: Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data