Much before the advent of Artificial Intelligence, and the buzz about deepfakes, the border between the true and the untrue has been a porous boundary, allowing for migration from one to the other. In his 1973 biography of Marilyn Monroe, Norman Mailer coined the term ‘factoid’, to mean something that resembled truth, and was taken for a fact, but was not, in fact, a fact and had no basis in reality.

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The word gained currency and over time its meaning began to morph until for many it came to signify its opposite: a small, or isolated, piece of data or genuine information, something that was real. An untruth repeated long enough becomes a truth.

The commentator William Safire predicted this in 1993 and, sure enough, soon after Webster’s New World Dictionary defined factoid as ‘a single fact or statistic’.

Though it is incorrect, or fake, this definition of the word has become, as the Grammatistblog, which stands vigil over the sanctity of the language, puts it “so widespread that those who dislike it…eventually have to accept it, even if it contradicts the word’s original meaning”.

Lewis Carroll’s Humpty Dumpty would have been a great fan of factoids. Humpty told Alice, “When I use a word it means just what I choose it to mean – neither more nor less.” When Alice wondered if we can make words mean whatever we want, Humpty asked whether we’re to be ruled by language, or whether language should be ruled by us, factoids and all.

This factual – or factoidal, if you prefer – account of how a word can get not just distorted, but the very concept that it represents can come to mean its reverse, shows that we don’t need Artificial Intelligence to create fake news of deepfakes for us; human intelligence, or lack of it, is quite capable of doing the job on its own.

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AI can give us deepfakes, like the Pope doing the bhangra with Ayatollah Khamenei, or Pakistan’s PM giving his army the boot and declaring the country a democracy.

But we’re not bad at faking it ourselves. And that’s a fact. Or a factoid.

If these foundational conflicts in AI regulation are not resolved in time, they could lead to cross-border divergence on standards for AI trust and safety, paralyse efforts toward positive rulemaking and prolong regulatory uncertainty for AI innovators and investors. This will come at the expense of both public safety and AI innovation and economic growth. There is an urgent need to comprehensively and rigorously cross-compare conflicting stakeholder positions and mobilise stakeholder consensus on proposals for regulatory reform to foster the safe and responsible adoption of AI for the benefit of all.

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World leaders need to balance any aspirations for AI supremacy with sustained international cooperation efforts to advance this critical agenda. Alongside other countries, India could play a key role in this effort by leveraging its presidency of the Global Partnership on AI as well as the unique geopolitical importance it holds to the innovation and regulatory powerhouses of the world – the United States and European Union respectively.