Rahul Matthan: Technology and law are joined at the hip as they evolve together
The Industrial Revolution led the first major transformation of society on the whole. It replaced human power with mechanical and spawned a number of 'macro-inventions' that changed how society operated. As machines replaced human labour, the accidents and injuries they caused forced common law courts to re-evaluate doctrines that had worked so far in a pre-industrial agrarian context.
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Nowhere is this more visible than in common law, which has repeatedly evolved in response to technological upheaval. Where it used to impose near-automatic liability for harm caused by a person's actions, after industrialization it adopted the principle of fault-based negligence, requiring plaintiffs to prove a breach of 'duty of care' to hold defendants liable. In time, the 'duty of care' principle was extended to protect individuals holding manufacturers liable for injuries caused to consumers, even if they had no direct contract with them.
Technological advancements in transport and telecommunications made it possible for business to be conducted at a distance. This forced courts to change the way they thought about contract law, giving rise to the 'mailbox rule,' which held that acceptance of a contract was effective once posted, even if the letter was delayed or lost in transit. Further evolutions in communication technology tested this idea, and while it was extended to contracts concluded over the telegraph, it was denied to the more-instantaneous telephone technology.
Mass production transformed the nature of contracting itself, making standard-form agreements and boilerplate terms the norm. As courts came to appreciate that large industries had an unequal bargaining power, they began to temper the egregious excesses of these contracts through the doctrine of unconscionability and laws of consumer protection.
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But no law has been more directly influenced by changes in technology than intellectual property, which came into being because of it. The Statute of Anne, widely recognized as the world's first copyright law, was enacted to offer authors (and their publishers) exclusive rights over their works because the printing press had made it relatively trivial for anyone to generate multiple copies of it.
When engravings on metal plates made it easy to mass-produce art, this right was extended to images and to music when the descendants of Johann Sebastian Bach asserted copyright over the sheet music of his compositions. Each subsequent creative technology forced society to revisit the ways in which intellectual property law was being applied, incrementally shifting the scope and extent of regulation in response to what technology made possible.
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We stand today on the verge of another technological shift. Just as the Industrial Revolution rewrote the legal framework as it then existed, artificial intelligence (AI) is likely to upend much of the legal system as we know it today. This will present itself in many different ways.
Autonomous vehicles and robotic tools are already testing the boundaries of existing liability doctrines. When a self-driving car causes an accident or an AI-powered medical tool results in harm to patients, traditional doctrines of foreseeability and proximate cause may no longer be useful. AI behaves in unpredictable and emergent ways, and companies may try to escape liability by claiming that it is impossible to reasonably foresee what AI-powered devices will do.
At the same time, the integration of AI into professional workflows could redefine what is considered 'reasonable care.' When that happens, doctors who fail to consult AI for a second opinion, or lawyers who omit to run their advice through AI for a reference check, may be deemed to have failed to do what was expected of them as professionals.
As AI agents proliferate, the offer and acceptance framework that defines to this day how contracts are concluded may no longer apply. Future workflows will call for multiple agents to interact in numerous ways that simply cannot be anticipated in advance, making each agreement a combination of hundreds of micro-arrangements concluded between autonomous AI systems to achieve a larger task.
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But it is in the area of intellectual property that we are likely to see the most dramatic change. AI is increasingly being used in the creative process, giving rise to entirely new forms of expression and novel methods of production. While creators may take time to adapt, adapt they will, and the law will have no option but to keep pace. The purpose of intellectual property law has always been to incentivize the act of creation. But AI will challenge distinctions between human authorship and machine-generated content, forcing courts and policymakers to grapple with how and if legal personhood should attach to algorithmic creativity.
Just as steam and steel reshaped the legal system, AI will as well. It is not a question of whether the law will change, but when.
The author is a partner at Trilegal and the author of 'The Third Way: India's Revolutionary Approach to Data Governance'. His X handle is @matthan.
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Hindustan Times
3 days ago
- Hindustan Times
How spy agencies are experimenting with the newest AI models
ON THE SAME day as Donald Trump's inauguration as president DeepSeek, a Chinese company, released a world-class large language model (LLM). It was a wake-up call, observed Mr Trump. Mark Warner, vice-chair of the Senate Intelligence Committee, says that America's intelligence community (IC), a group of 18 agencies and organisations, was 'caught off guard'. Last year the Biden administration grew concerned that Chinese spies and soldiers might leap ahead in the adoption of artificial intelligence (AI). It ordered its own intelligence agencies, the Pentagon and the Department of Energy (which builds nuclear weapons), to experiment more aggressively with cutting-edge models and work more closely with 'frontier' AI labs—principally Anthropic, Google DeepMind and OpenAI. On July 14th the Pentagon awarded contracts worth up to $200m each to Anthropic, Google and OpenAI, as well as to Elon Musk's xAI—whose chatbot recently (and briefly) self-identified as Hitler after an update went awry—to experiment with 'agentic' models. These can act on behalf of their users by breaking down complex tasks into steps and exercise control over other devices, such as cars or computers. The frontier labs are busy in the spy world as well as the military one. Much of the early adoption has been in the area of LLM chatbots crunching top-secret data. In January Microsoft said that 26 of its cloud-computing products had been authorised for use in spy agencies. In June Anthropic said it had launched Claude Gov, which had been 'already deployed by agencies at the highest level of us national security'. The models are now widely used in every American intelligence agency, alongside those from competing labs. AI firms typically fine-tune their models to suit the spooks. Claude, Anthropic's public-facing model, might reject documents with classified markings as part of its general safety features; Claude Gov is tweaked to avoid this. It also has 'enhanced proficiency' in the languages and dialects that government users might need. The models typically run on secure servers disconnected from the public internet. A new breed of agentic models is now being built inside the agencies. The same process is under way in Europe. 'In generative AI we have tried to be very, very fast followers of the frontier models,' says a British source. 'Everyone in UKIC [the UK intelligence community] has access to top-secret [LLM] capability.' Mistral, a French firm, and Europe's only real AI champion, has a partnership with AMIAD, France's military-AI agency. Mistral's Saba model is trained on data from the Middle East and South Asia, making it particularly proficient in Arabic and smaller regional languages, such as Tamil. In January +972 Magazine reported that the Israeli armed forces' use of GPT-4, then OpenAI's most advanced LLM, increased 20-fold after the start of the Gaza war. Despite all this, progress has been slow, says Katrina Mulligan, a former defence and intelligence official who leads OpenAI's partnerships in this area. 'Adoption of AI in the national-security space probably isn't where we want it to be yet.' The NSA, America's signals-intelligence agency, which has worked on earlier forms of AI, such as voice-recognition, for decades, is a pocket of excellence, says an insider. But many agencies still want to build their own 'wrappers' around the labs' chatbots, a process that often leaves them far behind the latest public models. 'The transformational piece is not just using it as a chatbot,' says Tarun Chhabra, who led technology policy for Joe Biden's National Security Council and is now the head of national-security policy at Anthropic. 'The transformational piece is: once you start using it, then how do I re-engineer the way I do the mission?' A game of AI spy Sceptics believe that these hopes are inflated. Richard Carter of the Alan Turing Institute, Britain's national institute for AI, argues that what intelligence services in America and Britain really want is for the labs to significantly reduce 'hallucinations' in existing LLMs. British agencies use a technique called 'retrieval augmented generation', in which one algorithm searches for reliable information and feeds it to an LLM, to minimise hallucinations, says the unnamed British source. 'What you need in the IC is consistency, reliability, transparency and explainability,' Dr Carter warns. Instead, labs are focusing on more advanced agentic models. Mistral, for example, is thought to have shown would-be clients a demonstration in which each stream of information, such as satellite images or voice intercepts, is paired with one AI agent, speeding up decision-making. Alternatively, imagine an AI agent tasked with identifying, researching and then contacting hundreds of Iranian nuclear scientists to encourage them to defect. 'We haven't thought enough about how agents might be used in a war-fighting context,' adds Mr Chhabra. The problem with agentic models, warns Dr Carter, is that they recursively generate their own prompts in response to a task, making them more unpredictable and increasing the risk of compounding errors. OpenAI's most recent agentic model, ChatGPT agent, hallucinates in around 8% of answers, a higher rate than the company's earlier o3 model, according to an evaluation published by the firm. Some AI labs see such concerns as bureaucratic rigidity, but it is simply a healthy conservatism, says Dr Carter. 'What you have, particularly in the GCHQ,' he says, referring to the NSA's British counterpart, 'is an incredibly talented engineering workforce that are naturally quite sceptical about new technology.' This also relates to a wider debate about where the future of AI lies. Dr Carter is among those who argue that the architecture of today's general-purpose LLMs is not designed for the sort of cause-effect reasoning that gives them a solid grasp on the world. In his view, the priority for intelligence agencies should be to push for new types of reasoning models. Others warn that China might be racing ahead. 'There still remains a huge gap in our understanding as to how and how far China has moved to use DeepSeek' for military and intelligence gaps, says Philip Reiner of the Institute for Security and Technology, a think-tank in Silicon Valley. 'They probably don't have similar guardrails like we have on the models themselves and so they're possibly going to be able to get more powerful insights, faster,' he says. On July 23rd, the Trump administration ordered the Pentagon and intelligence agencies to regularly assess how quickly America's national-security agencies are adopting AI relative to competitors such as China, and to 'establish an approach for continuous adaptation'. Almost everyone agrees on this. Senator Warner argues that American spooks have been doing a 'crappy job' tracking China's progress. 'The acquisition of technology [and] penetration of Chinese tech companies is still quite low.' The biggest risk, says Ms Mulligan, is not that America rushes into the technology before understanding the risks. 'It's that DoD and the IC keep doing things the way they've always done them. What keeps me up at night is the real possibility that we could win the race to AGI [artificial general intelligence]...and lose the race on adoption.'
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Business Standard
23-07-2025
- Business Standard
China leads the AI race as US struggles on energy, warns AI firm Anthropic
The United States is lagging behind China in terms of energy generation, warned Anthropic, a Silicon Valley artificial intelligence startup in its report. The company has urged Washington to cut down 'red tape' surrounding the power infrastructure development to stay competitive with China. Citing data from a February 2025 report by Australian think tank Climate Energy Finance, Anthropic stated that China, last year, added 400 gigawatts of power capacity, whereas the US only added 'several dozen', amounting to just one-tenth of China's total. Anthropic, the firm that is behind the Claude large language models (LLM), noted that the artificial intelligence sector in the US would require at least 50 gigawatts of power capacity by 2028 to maintain its leadership in global AI. It further mentioned that the disparity with China in terms of power capacity was 'concerning'. The report further added that while US President Donald Trump's Administration has already taken steps toward removing barriers by setting ambitious nuclear power targets and accelerating National Environmental Policy Act (NEPA) reviews, to compete with China, the US must take further action to address regulatory challenges that can delay energy projects. As the world's two largest economies engage in a tech race — from advanced semiconductor technology to artificial intelligence algorithms — energy generation has emerged as a critical new frontier. According to Matty Zhao, co-head of China equity research at Bank of America Securities, in an interview last month said that while the US capital expenditure on artificial intelligence was heavily focused on hardware like semiconductors, a significant chunk of China's artificial intelligence investments would go in building data centers, the energy infrastructure needed to support them. Earlier in May, billionaire and Tesla chief Elon Musk warned that the US could face power capacity issues related to artificial intelligence development by 2026, CNBC reported. The report comes at a time when China announced its plan to build a mega dam project in Tibet. With an estimated investment of about 1.2 trillion yuan ($167 billion) and an expected annual electricity generation capacity of 300,000 gigawatt-hours, the dam in Tibet would make it the world's largest hydropower facility. According to a report in South China Morning Post, China, in 2024, accounted for 71 per cent of the global rise in hydro power generation, adding more wind and solar power than the rest of the world combined. However, the Anthropic report suggests that in comparison, the US 'is not on track to meet the energy needs of AI training or inference by 2028'. This, according to the report, is partly because of regulatory issues, including the construction permits and approvals needed to build transmission lines. It further claimed, 'China – also vying for AI leadership – does not face the same set of regulatory constraints that we do. While China's infrastructure projects also required permits, regulators processed them far more quickly."
The Hindu
16-07-2025
- The Hindu
New NCERT textbook explains how ‘colonial powers stole India's wealth'
The new Class 8 Social Science textbook of the National Council of Educational Research and Training (NCERT) introduced to students in academic year 2025-26 describes the colonial rule of the European powers especially the British to be the one which 'drained India of its wealth'. Chapter 4 of the new NCERT textbook Exploring Society: India and Beyond states that, '…the Industrial Revolution in Britain, which required investment, was made possible at least partly by the 'stolen wealth from India'.' 'Stolen wealth from India' is a phrase used by U.S. historian Will Durant, it states. 'The general thrust of Britain's dominance in India was plunder, exploitation, trade dominance, imposition of educational, administrative and judicial systems, and Christianization,' Michel Danino, Head, the NCERT's Curricular Area Group for Social Science, told The Hindu. An official statement released by the NCERT said, 'All the facts presented in this textbook are based on well-known primary and secondary academic sources. However, in order to avoid generation of any prejudice and misunderstanding, 'A note on history's darker period' at page 20 has been added.' The note states, 'While those happenings cannot be erased or denied, it would be wrong to hold anyone today responsible for them...' The fourth chapter goes on to include a quote by William Digby which states, '...Modern England has been made great by Indian wealth, ...wealth always taken by the might and skill of the stronger.' 'A recent estimate for the wealth extracted out of India given by Indian economist Utsa Patnaik, in the period from 1765 to 1938, coming at 45 trillion U.S. dollars or about 13 times Britain's GDP in 2023. Had this wealth remained invested in India, it would have been a very different country when it attained independence,' the chapter states. 'This was extracted not just through taxes, but by charging Indians for the colonial power's expenditures on building the railways, the telegraph network and even on wars!' the chapter further states. 'In India, it is common to find the colonial period portrayed as a positive one, with the British bringing industries, railways, the telegraph, modern education, and so on. We have tried to correct this perspective by showing what really happened — the destruction of India's indigenous industries and educational system, the enormous revenue extraction from the Indian population to finance railway and telegraph, etc,' Mr. Danino stated. 'Of course we have also shown the other side — the opening up of India to the world and Europe's discovery of India's ancient culture, among others,' he further added. The chapter also states that converting indigenous populations to Christianity was a powerful motivation (for territorial expansion of European powers). Colonisation led to loss of independence, exploitation of resources by the colonisers, destruction of traditional ways of life and the imposition of foreign cultural values, the new NCERT textbook states. Portugese navigator Vasco da Gama 'seized, tortured and killed Indian merchants, and bombarded Calicut from sea,' the chapter states. 'The Portuguese presence was characterised by religious persecution... of Hindus, Muslims, Jews and Christian converts...,' the chapter further says. It also highlights the destruction of Pondicherry's original Vedapurishwaram temple, ordered by Joseph François Dupleix, Governor General of French India in 1748. The chapter states that the British systematically dismantled indigenous governance systems of village communities and replaced them with a centralised bureaucracy. 'While presented as modernisation, this imposition of a foreign system unsuited to India alienated Indians from the judicial system, creating courts that were expensive, time-consuming and conducted in a foreign language,' it states. Traditional versus modern systems of education The chapter states that diverse educational traditions such as padashalas, madrasas and viharas transmitted not only practical knowledge but also cultural values and traditions. It quotes from British reports which stated that hundreds of thousands of village schools were present across India (for instance, 1,00,000 to 1,50,000 of them in Bengal and Bihar) 'where young natives are taught reading, writing and arithmetic, upon a system so economical ... and at the same time so simple and effectual...' Also, the chapter states that the system education proposed by the British became a powerful tool for the creation of a class of Indians who would serve British interests; it quotes Thomas B. Macaulay who emphasised that 'Indians needed British education... to create a class of Indians who would be Indian in blood and colour, but English in taste, opinions, morals and intellect.' The chapter goes on to say that while a few prominent British Orientalists argued that Indian students should be left to study in their own languages, Macaulay's policy gained the upper hand and India's traditional schools slowly disappeared, while English became a language of prestige associated with colonial masters. This resulted in lasting divisions in Indian society between English-educated elites and the masses. 'It also sidelined traditional sources of knowledge and authority, creating generations of Indians disconnected from their own cultural heritage,' the chapter states. Addition of a chapter on the Maratha Empire The new NCERT textbook, unlike the earlier ones that made a passing reference to the Marathas, has now introduced an entire chapter dedicated to 'The Rise of the Marathas'. 'In effect, the British took India from the Marathas more than from the Mughals or any other power,' the NCERT textbook states. Marathas have been described as 'a powerful political entity that will alter the course of India's history'. The chapter talks about Shivaji's need to establish a navy as a 'revolutionary step' and his exploits as 'legendary'. The chapter goes on to state that when Shivaji attacked Surat, which was a wealthy port city in Mughal Empire, he obtained an enormous treasure of almost one crore rupees, but was careful not to attack religious places. In contrast, the Mughal rulers (like Babur, Akbar and Aurangzeb) have been described as 'brutal' in the previous chapter titled 'Reshaping India's Political Map'. The chapter says they 'destroyed temples' and their rule was fraught with 'religious intolerance.' In contrast, Shivaji has been described as 'a devout Hindu... who rebuilt desecrated temples, promoted Sanskrit and Marathi literature, religious institutions and traditional arts'. Ahilyabai Holkar, an 18th century Maratha ruler, has been described as 'a devout person who built and restored hundreds of temples, ghats, wells and roads throughout India, from Kedarnath in north to Rameswaram in south. She rebuilt the Kashi Vishwanath temple in Varanasi that had been destroyed by Aurangzeb and Somnath temple in Gujarat destroyed by Mahmud of Ghazni,' the chapter states. 'Evolution of India' 'Class 8 being the last year of the middle stage, the students are expected to acquire a broad multi-perspective understanding of our past between 13th to mid-19th century and how the various events of that period have helped shape and influenced the evolution of India of today,' a official statement from the NCERT said. 'This textbook attempts to provide an idea about the geography, history (medieval & modern), economic life and governance of the country, from a multi-disciplinary perspective in an integrated way,' it says. 'Our aim has been to consistently avoid attempting to load the child with too much information and to develop a critical understanding of the subject. Hence , the various facts, have been presented in a comprehensible manner to promote holistic learning in this textbook,' the statement further said.
