AI emerged in an era of eroding public trust — TIME
Artificial intelligence has entered a period when public mechanisms for establishing truth and trust have already been significantly weakened, Tiffany Sin Yu Wang, author of the book The Trust Code, writes in an article for TIME. In her view, the most complex cognitive technologies in history are developing against the backdrop of a fragmented information environment, where trust in institutions, the media and shared methods of fact-checking has declined.
From post-truth to the loss of trust
The author distinguishes between the concepts of “post-truth” and the “post-trust era.” In 2016, Oxford Dictionaries defined “post-truth” as circumstances in which emotions and personal beliefs have more influence on shaping public opinion than objective facts. At the same time, the “post-trust era,” as Wang defines it, means a deeper problem: the loss of shared procedures through which society determines what to consider reality.
Over the past two decades, the information ecosystem has changed from a model in which materials were selected by editors and distributed by a limited number of intermediaries to an environment where anyone can publish, amplify, distort or fabricate information. Algorithms began optimizing for clicks, engagement and sensationalism. As Wang notes, nearly eight out of ten people primarily encounter news through algorithmic systems, including social media feeds, search engines and aggregators.
In the United States, trust in the federal government has fallen from more than 70% in the late 1950s to less than 20% today, while fewer than a third of Americans express even some trust in mass media. The author also points to declining trust in religious institutions, financial systems, medical organizations and science.
More current news is available on the UA.News Telegram channel Telegram.
AI and the scaling of distortions
Wang recalls that photography was perceived as evidence of reality for nearly two centuries. However, in early 2023, an AI-generated image of Pope Francis in a white puffer jacket spread widely on social media, and many people initially took it for real. Within two years, AI-generated images, voices and videos became so convincing that the question shifted from the ability to identify a fake to whether it is possible to trust what one sees.
The author cites research by Duke and New York University, according to which exposure to opposing political views on social media can intensify polarization. Another study, published in the journal Science, found that false news spreads online substantially faster and more widely than reliable news.
Unlike previous technologies that expanded human capabilities, AI can generate arguments, summarize information, provide recommendations and create texts, code or music. Such models identify patterns and correlations in data, but do not understand truth in the way humans do. They are trained on news, social media posts, digitized books, archives, political disputes, scientific discoveries and disinformation, reproducing not only knowledge but also existing distortions and conflicts.
