Large language models (LLMs) are widely used for long-form text generation. However, factual errors in the responses would undermine their reliability. Despite growing attention to LLM factuality, the effect of response length on factuality remains underexplored. In this work, we systematically investigate this relationship by first introducing an automatic and bi-level long-form factuality evaluation framework, which achieves high agreement with human annotations while being cost-effective. Using this framework, we conduct controlled experiments and find that longer responses exhibit lower factual precision, confirming the presence of length bias. To explain this phenomenon, we empirically examine three hypotheses: error propagation, long context, and facts exhaustion. Our results reveal that facts exhaustion, where the model gradually exhausts more reliable knowledge, is the primary cause of factual degradation, rather than the other two hypotheses.

The use of artificial intelligence (AI) and newer technologies can help the judiciary dispose of thousands of pending cases, Aravind Kumar, Gujarat High Court Chief Justice, said. "Consider Motor Vehicle (MV) cases that account for highest in any court…They can be broadly classified into death cases, grievous injuries cases, simple injuries and for insurance claims," he added.

Yes, it's not technology because, At its core, AI is the Ideology of teaching computers how to "learn, reason, perceive, infer, communicate, and make decisions like humans do." The initial goal is called machine learning, where the machine (a computer) begins to make decisions with minimal programming. Instead of manually writing rules for how the computer should interpret a set of data, machine learning algorithms (i.e., sets of instructions for solving particular problems) allow the computer to determine the rules itself. Beyond machine learning lies an even bigger goal, deep learning. Deep learning uses more advanced algorithms to perform more abstract tasks such as recognizing images and detecting the early stage of the disease and saving millions of lives.

Chief Justice of India S A Bobde on Friday highlighted the need for artificial intelligence (AI) in the judicial system, pertaining to cases of repetitive nature and document management, to accelerate the dispute resolution process. Speaking at 79th Foundation Day celebration of the Income Tax Appellate Tribunal (ITAT), the Chief Justice of India said the use of technology in judicial functioning will play a significant role in docket management and decision making. "Though I must make one thing clear: Because we have been dealing with the introduction of artificial intelligence in courts, I am firmly of the view, based on the experience of systems that have used artificial intelligence, that it is only the repetitive area or decision making such as rates of taxation, etc, or something that is invariably the same or which is in a sense mechanical, and that must be covered by artificial intelligence," he said. "The artificial intelligence system we are looking to employ in courts possesses the reading speeds of 1 million character per second", he added. Chief Justice Bobde said that it reassures him to discover that more countries are resorting towards experimenting and implementing Artificial Intelligence in their respective Justice Delivery System.

Chief Justice of India, Sharad Arvind Bobde on Saturday hinted at the possibility of Artificial Intelligence being developed for the court system while making it clear that it will never replace human discretion. Speaking at an event here, Bobde said, "We have a possibility of developing Artificial Intelligence for the court system. Only for the purpose of ensuring that the undue delay in justice is prevented." "I must make it clear at the outset as there are times when even judges have asked this. AI is not going to replace human judges or human discretion", he added.

Chief Justice of India, Sharad Arvind Bobde on Saturday hinted at the possibility of Artificial Intelligence being developed for the court system while making it clear that it will never replace human discretion. Speaking at an event in Bengaluru, Bobde said, "We have a possibility of developing Artificial Intelligence for the court system. Only for the purpose of ensuring that the undue delay in justice is prevented." "I must make it clear at the outset as there are times when even judges have asked this. AI is not going to replace human judges or human discretion", he added.

Justice Sharad Arvind Bobde, who will be succeeding Chief Justice of India Ranjan Gogoi has proposed the usage of high-end technology including Artificial Intelligence in courts. Justice Bobde who will be the 47th Chief Justice of India has asserted that there may be a need for some minor changes in the justice system of the country by the inclusion of the use of technology such as artificial intelligence. "Justice delivery system is good, it might require some minor changes, including the use of technology like artificial intelligence. It's a good system, you need to use some other things," Justice Bobde told ANI. He said the justice delivery system is good, but also pressed on the need to introduce some long term and short-term measures to make the justice delivery system better.

New Delhi [India], Oct 31 (ANI): Chief Justice of India (CJI) designate, Sharad Arvind Bobde, on Thursday advocated the usage of high-end technology including Artificial Intelligence (AI) in courts. Speaking to ANI here, Justice Bobde, who will become the 47th Chief Justice of India, stated that the justice delivery system is "good" in the country and may require the use of minor changes including the use of technology. "Justice delivery system is good, it might require some minor changes, including the use of technology like artificial intelligence. It's a good system, you need to use some other things," Justice Bobde told ANI. The CJI designate also said that some long and short term measures need to be introduced to make the justice delivery system better. "There are long term measures and short term measures.