دانلود کتاب هوش مصنوعی در روزنامه‌نگاری

Close your eyes. Listen closely. What don’t you hear as you enter that space once known as a newsroom? Maybe it’s the New York Times or the Washington Post. Maybe it’s CNN or NBC. What’s missing? People. Reporters. Editors. Researchers. Storytellers. Flash forward. It’s now 2030. If the experts’ predictions are correct, the silence is, to use a cliché that skilled writers try to avoid, deafening. Where did all the voices go? ose magnicent purveyors of information that sometimes rose to the level of wisdom. e gaggle of, well, a “gaggle,” that assembly of human beings bringing not only sound but also voice to an audience. Maybe it wasn’t one voice, but many voices, each unique, each bringing dierent perspectives to the same narrative. It is narrated. Who does the narrating? e answer is a tale of then, now and next. Each individual in that long-ago news space looked at what we once called facts through a unique lens, shaped by one’s own experiences, skills, and talents. Yes, sometimes that lens would be discernibly blurred. Readers knew that. Viewers knew that. Or they used to think they did, because the trail that led to their consumption of information called “news” passed through human brains, hands, and hearts. Accuracy, accountability, and trust—there’s nothing articial about any of those concepts. All, among others, are components of what we historically accept as major tenets of journalism. Each depends upon the exercise of judgment. Traditionally, that’s where experienced editors and reporters come in. ey provide not only knowledge but also context, connections that extend much farther than the distance between the nger and the keyboard—or at least when they do their job well. It is not a mechanical process and, at its highest level, there is nothing articial about it at all. It’s born of time, experience, learning, adaptation and innovation. It encompasses information gleaned from the past but hopefully also adds to the repository of human knowledge. But it’s 2030 and the news space, what we once called a newsroom, is quiet, still, haunted, but for one brain stem, not really a brain, but a wholly dierent kind of space populated by the work of humans, but not, in and of itself, human at all. We may call it articial intelligence, but it is very much real, very much a part of the tapestry of art, science, medicine—and journalism. Its potential is enormous, its power seemingly innite. Journalists once researched the background to stories, rst using previous stories written on a topic, maybe even books, often turning to a newspaper or broadcast station’s archives (ironically referred to as the “morgue”). Articial intelligence scrapes from information it’s been given to formulate stories based upon a body of knowledge on any given topic, delivering, in some instances, a fully written, fully realized news story. e term “scrape” itself suggests skimming the surface of a topic or story, but articial intelligence proponents suggest otherwise. e argument goes that AI (the accepted abbreviation for articial intelligence) can sift through millions, billions, potentially trillions of articles, reports, stories, records, an entire database of all the knowledge on any subject far faster and more eciently than any human possibly can or could. If it sounds like, to quote Huxley, a brave new world, it may well be—at least for AI’s developers and the corporations that back them. But for journalists, what does AI mean? Does it increase accuracy, accountability, and trust in news media or dramatically reduce these things? Is it a useful tool, along with all the other, more traditional tools used by journalists in their quest for better storytelling, or can it add to the problem of mis- or disinformation already so prevalent in American society? Beyond its potential and power, does AI have a downside? Does better or even somewhat improved journalism result from what is essentially a robotic process, or does an important part of developing and receiving information result from collaboration and the interaction of human neurons processing, judging, and balancing that information? From the perspective of eciency and economy of scale, AI and journalism would seem, from a corporate media standpoint, a perfect match: faster stories created at much less expense. But what might be lost in the process? Is that loss worth the gain? As you read the pages ahead, keep in mind a central theme: these are not idle, academic questions, and the horizon on which they are posed is not distant. AI is now. It is and has been in our lives for much longer than any of us recognize: in our homes, in our cars, in nearly every aspect of what we say, see, and do. Why would or should journalism be any dierent? Unbeknownst to you, it’s highly possible, if not entirely probable, that you have already read, heard, or seen news stories that are completely created not by human brains and hands but by AI bots—a term that will be further dened shortly. ere is little wonder that some in the AI community refer to it as “the new internet,” its rapid development outpacing the rise of the greatest, most powerful disruptive change in media and communication since Gutenberg invented the printing press. Whether that claim is hyperbole or prophecy will be determined by how we use this technology and our vigilance as a society to ensure we don’t abuse it. at process depends upon preparing the next generation of decision-makers, both journalists and their audiences, for a level of media literacy that’s unprecedented. In the upcoming chapters, many questions will be posed: important questions that might lead to some solutions surrounding AI’s place in journalism and in democracy, with the underlying assumption that the two are critically connected at this point in America’s history. If articial intelligence is the new internet, let’s begin with the question of how we are wiring ourselves not only for the challenge that is here and now but also for the challenges that lie ahead.