Opinion | A.I. Is Endangering Our History - The New York Times - 0 views
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Fortunately, there are numerous reasons for optimism about society’s ability to identify fake media and maintain a shared understanding of current events
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History can be a powerful tool for manipulation and malfeasance. The same generative A.I. that can fake current events can also fake past ones
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there is a world of content out there that has not been watermarked, which is done by adding imperceptible information to a digital file so that its provenance can be traced. Once watermarking at creation becomes widespread, and people adapt to distrust content that is not watermarked, then everything produced before that point in time can be much more easily called into question.
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countering them is much harder when the cost of creating near-perfect fakes has been radically reduced.
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There are many examples of how economic and political powers manipulated the historical record to their own ends. Stalin purged disloyal comrades from history by executing them — and then altering photographic records to make it appear as if they never existed
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Slovenia, upon becoming an independent country in 1992, “erased” over 18,000 people from the registry of residents — mainly members of the Roma minority and other ethnic non-Slovenes. In many cases, the government destroyed their physical records, leading to their loss of homes, pensions, and access to other services, according to a 2003 report by the Council of Europe Commissioner for Human Rights.
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The infamous Protocols of the Elders of Zion, first published in a Russian newspaper in 1903, purported to be meeting minutes from a Jewish conspiracy to control the world. First discredited in August 1921, as a forgery plagiarized from multiple unrelated sources, the Protocols featured prominently in Nazi propaganda, and have long been used to justify antisemitic violence, including a citation in Article 32 of Hamas’s 1988 founding Covenant.
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In 1924, the Zinoviev Letter, said to be a secret communiqué from the head of the Communist International in Moscow to the Communist Party of Great Britain to mobilize support for normalizing relations with the Soviet Union, was published by The Daily Mail four days before a general election. The resulting scandal may have cost Labour the election.
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Decades later Operation Infektion — a Soviet disinformation campaign — used forged documents to spread the idea that the United States had invented H.I.V., the virus that causes AIDS, as a biological weapon.
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As it becomes easier to generate historical disinformation, and as the sheer volume of digital fakes explodes, the opportunity will become available to reshape history, or at least to call our current understanding of it into question.
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In indexing a large share of the world’s digital media to train their models, the A.I. companies have effectively created systems and databases that will soon contain all of humankind’s digitally recorded content, or at least a meaningful approximation of it.
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They could start work today to record watermarked versions of these primary documents, which include newspaper archives and a wide range of other sources, so that subsequent forgeries are instantly detectable.
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many of the intellectual property concerns around providing a searchable online archive do not apply to creating watermarked and time-stamped versions of documents, because those versions need not be made publicly available to serve their purpose. One can compare a claimed document to the recorded archive by using a mathematical transformation of the document known as a “hash,” the same technique the Global Internet Forum to Counter Terrorism, uses to help companies screen for known terrorist content.
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creating verified records of historical documents can be valuable for the large A.I. companies. New research suggests that when A.I. models are trained on A.I.-generated data, their performance quickly degrades. Thus separating what is actually part of the historical record from newly created “facts” may be critical.
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Preserving the past will also mean preserving the training data, the associated tools that operate on it and even the environment that the tools were run in.
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Such a vellum will be a powerful tool. It can help companies to build better models, by enabling them to analyze what data to include to get the best content, and help regulators to audit bias and harmful content in the models