Artificial Intelligence (AI) studies were carried out with the hope of creating a healthier life and a more livable world. The idea of getting rid of the human body, on the one hand, the need to automate some challenging and long–term works, on the other hand, the potential of systems to be superior and long–the term has brought humanity to a series of Artificial Intelligence (AI) studies that result in machine learning today. With mechanization, humanity’s struggles with nature and each other have changed many dimensions from history to today. Technology has created unexpected changes in human life at every stage of history. In addition to the incredible innovations and conveniences it has added to human life, it has massive–sized wars that destroyed nature. Moreover, it has made people and their labor dysfunctional by automating some business lines as a functional area that should be included in people’s daily lives. However, all kinds of automation before the 21st century were based on a symbiotic relationship between man and machine.
At the point reached today, the situation has become complex and challenging. Thanks to software developed with a more complex robotic technology and Artificial Intelligence (AI) logic, the works that many people do in a long time are carried out in a much shorter time and more efficient way. Automatic functions, which were previously performed only based on archives in software databases, have now reached a new point in themselves due to the robots working by recording and learning experiences, with the concept called Machine Learning (ML). In the face of this situation, the responsibilities of people, societies, and states are also increasing. Therefore, it becomes essential to act with a different level of awareness and learning against Machine Learning (ML), which is advancing at such a rapid pace.
What happened in Artificial Intelligence (AI) technology today could be called a dream for many societies in the early 1900s. The technological process, which profoundly affects all life forms and fields, profoundly affects the journalism profession as it does many other jobs. Algorithmic news technology, which eliminates the dependency on time, labor, and space, and enables news production processes much faster than ever before, brings with it the realization of some human-specific abilities and reflexes by robots with Machine Learning (ML) in Artificial Intelligence (AI). Technological progress has created stressful and painful transformations in every period and has profound effects. The outcome of this progress in the future is beginning to emerge much more sharply. The widespread use of Artificial Intelligence (AI) software in professions leads societies to an emotional dissolution in large populations.
For this reason, the risk of people becoming unemployed and turning into dysfunctional has begun to be discussed. But, mainly thanks to Machine Learning (ML), robot software starts to think and act like humans and create new solutions with their impressions from previous experiences. A software technology close to the human mind and learning increases its impact day by day in business lines and areas where it has a place.
In today’s digital age, many concepts, from fake news to alternative truths, from the post–truth to the echo chamber, are the words used in the discussions on the role of journalism. Such terms send alarming signals of deepening distrust in online media and news outlets. This insecurity and how people navigate news content in the chaos we call the Internet should foster more informed democratic debate among citizens.
While these problems may seem new, they are not. They’ve been in the spotlight since Gutenberg. Still, dramatic changes in the way we learn about the news have worsened the situation. Considering that social media is the primary source of information, especially among young people, this results in an ideological resonance when people share the news with their friends with similar political views and reinforce their prejudices.
The rise of social media as a distribution channel has also increased fake news because websites cannot fully comply with high journalistic standards. Clickbait headlines are shared more than investigative journalism because of their hearsay appearances, reader verification bias, and targeted advertising benefit. While major players focus on the problem, the proposed solutions are imperfect and inherently controversial.
You can’t tell a person exactly what they can and cannot trust. However, you can easily guide them to find the necessary information and compare their perspectives.
A DEMOCRACY LOST IN DATA
A free and independent press may be necessary to democracy, but what is suitable for the freedom and independence of these institutions? Is it because the Internet puts them in the same environment as individuals who do not comply with the same standards of journalism? Investigative journalism is difficult and costly. Why should a journalist be paid to research when a short article with a catchy headline gets more reads? Why trust a journalist if anyone can write and share a short story?
As Christopher Hitchens said, “I became a journalist because I didn’t want to rely on newspapers for information.”
Results from search engines are personalized based on your browsing history and filled with targeted ads. Searching for information in a news story and getting a list full of hundreds or even thousands of pages isn’t strictly informative at first glance. The time it takes to scroll through information is prohibitive. The knowledge itself is open to discussion. Traditional search engines are helpful for many things. However, we can do much better to gain information healthily.
MACHINE LEARNING AND DATA JOURNALISM CAN HELP
