The media industry is facing the biggest changes in its history. Constantly evolving technologies are transforming the media landscape at lightning speed. Media companies are moving toward agile workflows and user-centered design. Journalists are advocating for quality journalism and are beginning to understand the importance of moving from print to digital. Producing and publishing across multiple platforms and services is becoming the norm for many publishers and the continued decline in advertising revenue must be offset by attracting new paying subscribers while reducing overall costs. Say no to plagiarism. Get a Tailored Essay on “Why Violent Video Games Should Not Be Banned”?Get Original Essay Publisher Must Transform to Adapt to Changing Landscape, Now Delivering Compelling, Integrated Experiences to Advertisers and to readers. Depending on who you ask about the future of media and journalism, it's either the best or the worst. (Kaul, 2012) Recent and Emerging Technology Trends in Media Industry. Artificial intelligence, machine learning and deep learning. Artificial intelligence (AI) is a branch of computer science in which computers are programmed to do things that normally require human intelligence. (Russell and Norvig, 2003) This includes problem solving, pattern recognition, learning, perceiving situations or environments, and understanding language. AI uses its own computer languages, special types of computer networks modeled similarly to the human brain. Machine learning programs run on neural networks and analyze data to help computers find new things without being explicitly programmed to know where to look. Machine learning is useful because it allows computers to predict and make decisions in real time without human intervention. (Schmidhuber, 2015) Deep learning is a relatively new branch of machine learning. Such systems are trained to learn on their own. This means that more and more human processes will be automated. Automation and augmented journalism Companies like Arria NLG, a UK-based AI technology company, have built workflow systems that can turn raw data into stories indistinguishable from human-written text. Recaps, criminal reports or financial summaries are today written by automated systems and published by media companies. For now, such systems are only capable of telling the story of “what” autonomously. Other AI systems can help increase journalists' workflow. By working alongside these systems, journalists gain new abilities to understand the “why.” However, we can assume that future systems will also be able to do this autonomously. Voice InterfacesEthical Issues and TradeoffsThe problem with AI machine learning is that the data and models used are encoded in a biased way. This flaw goes back to the people who built the models. These people themselves are subject to homogenous working and learning environments, leading to unconscious bias. Keep in mind: this is just a sample. Get a personalized article from our expert writers now. Get a Custom Essay Studies have been undertaken by ProPublica (Mattu et al., 2016), Princeton, MIT, Harvard,..