Axel Springer’s Post

To my fellow news readers/anchors: AI bots are coming for your jobs! So hone in your live, unscripted breaking news coverage skills as well as your interviewing techniques to remain relevant (and employed)! #journalism #generativeAI #artificialintelligence #technology #academia

The biggest report about the trends and predictions that will be shaping #journalism in the year ahead is here. 📈 Reuters Institute Digital News Report 2024 explores the integration of AI tools, shifting priorities in news and the media, the further rise of video content, and more. Read the summary:

GenAI vs. Journalism... half of global news giants draw the digital line – what it means for the future of information In a groundbreaking study released on February 22, 2024, by Dr. Richard Fletcher, offered a glimpse into the complex dynamics shaping the future of AI in the news industry. The factsheet reveals a significant trend: as of the end of 2023, nearly half (48%) of the top news websites across ten countries have initiated a blockade against OpenAI's crawlers, with Google's AI crawlers facing restrictions from 24% of these sites. This strategic move by publishers, especially prevalent among legacy print outlets and those with substantial online reach, signals a critical pivot point in the digital transformation journey of the news ecosystem. As we stand at the crossroads of AI and journalism, the choices made today will shape the informational landscape of tomorrow. It's time for CXOs to champion innovative strategies that embrace these changes, ensuring that their organizations remain at the forefront of the digital frontier. A quesiton I am pondering after reading this valuable research is whether or not it will force Big Tech to pay for content and help journalism thrive in the digital era. How about you what does this research highlight to you? #DigitalTransformation #AI #Leadership #Innovation #bigtech #responsibleai #journalism https://lnkd.in/gM_Wjms8

Many relevant insights, so do check our new report on Generative AI in Journalism! Here are five key take-aways on the ethics questions that I found particularly noteworthy: 1. Many ethical concerns centre around the quality of output, in terms of accuracy, the lack of bias, reduced quality, plagiarism etc. Lack of human oversight was another key concern. Correspondinngly, human oversight is among the most important strategies to make use of generative AI responsible. 2. Equally noteworthy were the concerns left unmentioned: concerns about the ecological footprint of generative AI, extractive labour practices and the working conditions of AI workers, the growing power imbalance and dependency of the media on large tech companies, the danger of further reinforcing social injustice and disparate treatment are all concerns that figure prominently in the public debate, but not in the responses. The overall picture is that ethical concerns around the use of generative AI in journalism are primarily inward-looking and not so much concerned (yet) with the bigger picture. 3. Interesting was also that the by far most dominant strategy to address ethical concerns was not to use generative AI. Put differently, unresolved ethical concerns can be a real obstacle to deployment and experimentation with generative AI. 4. I was struck by the fact that there was a strong focus on monitoring the output but testing the model or engaging in responsible procurement were the least common strategies. In other words, there is little critical engagement with how much a model is aligned with professional values or supports responsible use. Instead there is a strong reliance on the ability of respondents to effectively supervise the output. Arguably, here lies an untapped opportunity for the media to play a stronger role in creating demand for responsible and also smaller generative AI models, and creating some counterweight to the ever-growing dependency on Big Tech. 5. Finally, the challenge with guidelines sits in their operationalisation and integration into responsible workflows, providing useful examples but also their ability to evolve in a dynamic technological environment. Much more food for thought. Comments and suggestions are super welcome. Thanks Nicholas Diakopoulos Hannes Cools Charlotte Li Ernest Kung Aimee Rinehart Lisa Gibbs to for great cooperation! AI, Media and Democracy Lab Northwestern University The Associated Press

As AI reshapes journalism, backlash has hit G/O Media and Sports Illustrated for their AI-written content. G/O Media's "The Inventory Bot" disclaims potential inaccuracies in its many articles, while Sports Illustrated got caught in a scandal for AI articles with made-up bylines. These cases spotlight pressing concerns about journalism's direction, the trustworthiness of AI content, and the moral issues of AI replacing human reporters. Are media companies' goals for efficiency and cost savings worth the possible erosion of journalistic integrity and truthfulness? What effect will journalism's AI transformation have on news credibility, and what steps are needed to guarantee AI content is transparent and responsible? We invite you to share your perspective! #journalism #fakenews #deepfakes #generativeai

Ladina Heimgartner, Head Media Ringier AG & CEO Ringier Medien Schweiz: "We don’t see Gen AI as just a threat to the media. We use Gen AI as an opportunity and to be better at our jobs as journalists. It's a catalyst for excellence in journalism. It allows us to overcome language barriers, enhance content creation, and deliver impactful storytelling with unprecedented speed and accuracy. Let's harness the power of AI to elevate journalism, shape the media landscape, and ensure our journalism remains at the forefront of innovation." #AI #innovation #leadership #media #marketplaces #upskilling #transformation

Excited to see the progress and potential of AI in journalism! It's fascinating how AI is able to analyze vast amounts of data and deliver accurate information. Looking forward to seeing how this technology continues to evolve and shape the future of news. #AI #journalism #technology #innovation

Very interesting and nuanced report on the use of #GenerativeAI in Journalism for The Associated Press by Nicholas Diakopoulos, Hannes Cools, Charlotte Li, Natali Helberger, Ernest Kung, Aimee Rinehart, and Lisa Gibbs. Especially the balance between AI produced content and human supervision is an important task to solve. Other ethical concerns like bias or lack of accuracy are, of course, key factors for the future use of generative AI in journalism. At aureka, we're developing AI tools for people, companies, and institutions with high standards for accuracy and truthfulness. Making sure that those principles are guaranteed, is one of our main concerns. For example, we're still discussing how exactly we'll use generative AI in the results of our new #SemanticSearch. What do you think is the right balance between AI and human input in journalism? #Journalism