Tags containing: "automation"

Practical advice for putting AI to work in the newsroom

January 17, 2018 Rande Price, Research VP – DCN

Journalists today are using Artificial intelligence (AI) in newsroom as part of their daily reporting process. The Tow Center for Digital Journalism and the Brown Institute for Media Innovation’s research report, Artificial Intelligence: Practice and Implications for Journalism, discusses new AI developments and the impact on news organizations.

Today, more and more resources are available digitally. The days of manually searching for data in basement archives are long gone. However, given all of the digital resources available, the process requires significant human effort. AI and automated journalistic processes can help ease that burden.

BuzzFeed’s BuzzBot allows the collection of information from on-the-ground new sources.

The Tow Center and Brown Institute have identified three major journalistic AI achievements to date:

Finding needles in haystacks: AI can find and fact-check faster than the human eye.
Identifying trends: AI can parse through data, again faster than humans, and group findings into categories to identify trends.
Examining an application of AI or computation as the subject of the story itself: Since AI algorithms are built by humans, AI can also proof itself for unintentional bias in its applications and outputs.

Further, there are several new successful applications of AI in newsrooms. One is Wibbitz, a resource used by USA Today to create short videos. Others include News Tracer, an algorithmic prediction tool that helps Reuters journalists gauge the integrity of a tweet and BuzzBot, software from BuzzFeed, which allows the collection of information from on-the-ground new sources. Still, journalists must be careful to evaluate the credibility of AI data, its sources and understand how the algorithms work.

Key steps to integrating AI in the newsroom:

Train editors and reporters to incorporate AI as a new resource for storytelling.
Develop and promote the use of AI guidelines regarding the ethical use of data. Further, public disclosure of methodology is a must especially in terms of editorial values and standards.
Small operations for which AI is too expensive should consider partnerships with academic institutions.
Reporters and journalists should continue to be transparent about AI usage in a report or how it’s used in the production of a story.

According to The Tow Center and Brown Institute, journalists have two main responsibilities. First, they need to present the information to the reader in a clear and concise manner. And second, they need to explain its authenticity. This includes the practice of AI, including full disclosure of details and formulas for its algorithms. Importantly, as AI helps facilitates the newsroom, journalists need to question and critique the process and the information received.

Advertising | Industry-Research

Today’s challenges offer an opportunity to rebuild trust in digital media

January 24, 2017 DCN

With trust in mass media at a record low, publishers look to 2017 as an opportunity to distinguish quality journalism from the fake news landscape and bot traffic of big tech platforms.

CEOs, editors and digital leaders today recognize both the opportunities and the challenges in 2017. Reuters Institute surveyed 143 senior publishing executives in 24 countries to recognize current business sentiment, uncover trends and identify new developments in the digital marketplace. Interestingly, Reuters found that more than two-thirds (70%) of executives believe fake news offers them a chance to strengthened their brands. More than half (56%) say that Facebook Messenger will be an “important/very important” part of their offsite initiatives this year (53% for WhatsApp and 49% for Snapchat). And at the same time, just under half (46%) of these same respondents are more worried today than a year ago, about the role of offsite platforms.

In Reuters Institute’s annual predictions report, the key trends identified for 2017 include:

1. Addressing fake news

Fact-checking news outlets becomes the new norm.
Platform and algorithm changes allowing for easier reporting of false news (and feeding these signals back into the core algorithms so these sources get devalued).
Regulation threats to remove fake news from sites.
Algorithms are expected to challenge our bias.
Fighting for quality news brands.

2. Redefining publishers’ relationship with platforms

Publishers fight back by creating platforms of their own (e.g. Schibsted, started its own platforms for content and advertising to create the scale and data competence to compete with Facebook).
Platforms pay hard cash for content.
Mergers and acquisitions happen more often as scale will mean operating across multiple platforms.

3. Digital advertising and sustainable business models

Subscription payments will focus more about membership and less about paywalls. News publishers, especially, will need to attract new customers, offer new pay services and earn more money from their current subscribers.
Data, loyalty and personalization will help with converting unidentified web users into loyal customers by creating more relevant and personal experiences.
Mobile alerts and the battle for locked screens signifies the shift to mobile notifications to attract consumers back to apps and websites.
Acceptable ads and ad-blocking apply pressure on the marketplace to ensure a more positive user experience with non-intrusive advertising.
Sponsored content replaces the displayad model.
Pop-up newspapers and magazines will offer in-depth coverage on certain topics but for only a limited period of time.

4. Messaging applications and news bots

Voice news bots with voice-activated platforms gain strong penetration (e.g. Alexa and Google Home).
Fact-checking bots are activated (e.g. Full Fact, a UK based company, is already looking to developing a service that fact checks live press conferences).
Conversational commerce emerges (e.g. Crosby, a travel bot service, that reads your email or group messaging conversations and send you recommendations for where to eat, what to do and when to leave for the airport).

5. Voice as an operating system and the rebirth of audio

Podcasts and audio books get a big boost in the car.
Improvements to data and advertising around podcasts lead to significant investments by publishers. A new measurement system form Nielsen’s and a Swedish start-up platform Acast offer metrics for podcasts to support advertising models.
Businesses start to deploy Amazon Echo and Google Home speakers (e.g. hotels use voice-controlled devices to enable guests to order room service, check the weather and find TV channels).

6. Online video and the future of TV

Disillusion with Facebook Live shifts a live focus towards sport and exclusive music, both strong vehicles to attract audiences and advertisers.
Oversupply of short form video leads to falling advertising premiums.
New opportunities with feature-based videos for brands integrate messages into videos.
Video-selfies to experiment with new fantastical filters (e.g. Splash is a new app that allows you to create and annotate 360-degree experiences).

7. The blurring of television and online video

Top content will increasingly be watched on big screens.
Competition for talent and rights heats up to drive new subscription and retain existing users.
News bulletins lose audiences triggers new ways to appeal to young (e.g. CNN acquired video-sharing app start-up Beme, co-founded by YouTube creator Casey Neistat, is building a new brand around distinctive reporting and commentary for millennials).
New cross-platform metrics for TV.

8. Virtual Reality (VR), Augmented Reality (AR) and Mixed Reality (MR)

New reality tech offers huge potential to shape experiences for entertainment, education and commerce. Forecasters suggest around 30m devices will be sold by 2020 generating revenue of around $21 billion.

9. AI and algorithms under fire (e.g. An example gone sour was Microsoft’s friendly AI driven chatbot Tay. Within its first 24 hours on Twitter with Millennials, it was spouting offensive and racist messages such as “Hitler was right”).

10. Automation and a jobless future means robo journalism on the way

More automated stories.
Intelligent content production systems.
Computer and networked assisted investigations.
Filters and alerts are being developed to help manage the information overload (e.g. SamDesk and Dataminr are deployed in newsrooms to pinpoint and manage breaking news in social networks).

11. Cyber-Wars, and Personal Security

Encryption and surveillance are on the rise.

12. New technology

Sharper screens, fold out phones, better batteries.
Faster and more reliable networks (e.g. 5G).
Clothes as a platform with wearable technology.
Biometrics, the end of passwords and checkout-free shopping. A new shopping experience, Amazon Go, that automatically detects when products are taken from or returned to the shelves using computer vision and sensor fusion.

13. Start-ups to watch

Cheddar is a new business news video network for millennial. Founder Jon Steinberg of Buzzfeed is charging $6.99 for premium services on its own website and is looking to drive carriage fees from services like Facebook Live, Twitter and Netflix.
Zipline is a small robot airplane designed to carry vaccines, medicine and blood in developing countries.
Houseparty is a new group video chat, up to 8 people can chat at a time, from the creators of Meerkat.
Accompany aims to provide an automated briefing of all the information you need before you walk into any meeting including relevant files, email conversations with attendees, details about their lives sucked from the web plus up-to-date information on company performance.

2017 provides many opportunities for publishers to rebuild consumer trust in digital media. The Reuters Institute predictions suggest that publishers must help scrub the digital environment from bot traffic, annoying ads and fake or misleading news. They must hold themselves and others responsible and keep a watchful eye on the algorithmic accountability tied to the digital experience. Importantly, publishers must continue to build their digital brand and diversify their revenue streams beyond digital display advertising.

Innovation

The Washington Post, The Associated Press and LA Times get an assist from Artificial Intelligence

August 9, 2016 Michelle Manafy, Editorial Director – DCN

Robots aren’t taking over the media (yet) but Artificial Intelligence and automation are lending a helping hand.

The challenges of running a profitable media company have resulted in a “streamlining” of these organizations, often requiring staff reductions that create holes in coverage, particularly in areas that require domain expertise or a nuanced interpretation. What if there was a way to free up the increasingly valuable reporters from some of their tedious or time-consuming tasks to focus on telling complex stories or digging into subjects deeply? Enter Artificial Intelligence (AI) for journalism. An increasing number of media companies are employing robot journalists—or, more accurately, artificially intelligent algorithms adept at analyzing data and writing serviceable prose – to do just that. (Fusion’s Kevin Roose does a terrific job explaining how it works.)

Here are some of the ways AI is making its mark on journalism:

The Associated Press, working with Automated Insights and Zacks Investment Research, automatically generates almost 4,000 stories about U.S. corporate earnings each quarter—about twelve times what AP reporters and editors previously created. For a small fraction of these stories, editors add “the human touch” to provide more nuanced interpretations.

More recently, the AP added sports reporting to its automated journalistic endeavors. The move allowed the company to expand its coverage of Minor League Baseball (and could offer similar possibilities for other sports coverage). AP baseball editors and reporters worked with Automated Insights to configure the Wordsmith platform to ensure that it would follow AP standards for baseball coverage.

The Washington Post is also taking a crack at automated journalism, developing its own proprietary artificial intelligence tool, “Heliograf,” which automatically generates brief, multi-sentence updates. The Washington Post will roll it out to report key information from the 2016 Rio Olympics, including results of medal events. Heliograf, which will continue to be developed by Post engineers to enhance storytelling for large-scale projects, will also be leveraged for data-driven coverage of major news events, including the U.S. election. This technology can process a combination of different data sources, such as crime and real estate numbers, customize stories depending on individual user actions, and help look for anomalies in data to alert journalists to a potential story—all of which The Washington Post plans to leverage as it further develops Heliograf’s utility.

Algorithmic journalism is not limited to sports and finance, however. One of the longest-running robo-journalists in the game is Quakebot, which was written by Los Angeles Times Writer Ken Scwenkie. According to Business Insider, Quakebot is an automated system that resides on the Los Angeles Times’s servers, which receives emails from the US Geological Survey, runs that data through an information checklist, and then determines if it’s newsworthy based on the magnitude. It then parses out content from the email and inputs it into the Los Angeles Times’s content management system. Posts are structured using a formula based on previous posts.

It is interesting to note the LA Times also uses its own brand of automated journalism for The Homicide Report, which tracks every homicide victim in LA County. This sort of approach (visualized data journalism) is particularly suited to the algorithmic approach in that analyzing huge (and possibly constantly growing or changing) data sets is a massive undertaking. With solid structure and oversight, these can be reliably created, updated and presented in a dynamic visual way by leveraging AI.

The momentum for automated journalism has been building for years now and is definitely picking up steam. The New York Times reports that Tronc, Hearst, Bonnier, Gannett and the Weather Channel use automation to do everything from streamlining video production to analyzing and summarizing text and finding photographs and video clips to go with it. And, in an April memo to Bloomberg’s staff, Editor-in-Chief John Micklethwait announced that the news organization is creating a 10-person team to determine how automation can be used throughout the company’s portfolio of editorial products.

As Dr. Andreas Graefe, author of the Tow Center for Journalism report “Guide to Automated Journalism” noted, automated journalism is particularly useful in generating routine news stories for repetitive topics for which clean, accurate, and structured data are available. He also outlines the potential for algorithms to generate large volumes of news quickly, potentially in multiple angles and personalized for reader preference.

But, as the report points out, there are limitations to automation that must be carefully considered as more organizations use artificial intelligence to augment their journalism. Given many of the current implementations reliance on data, the quality of that data is paramount. And, as Micklethwait points out in his memo, “one irony of automation is that it is only as good as humans make it.” That, of course, extends to the media organizations that deploy algorithmic approaches, which must balance efficiency, transparency, and the consumer demands of more information, faster—but who also love a good read.

Industry-Research

Making automated journalism work for you

January 12, 2016 Research Team—DCN

As The Tow Center for Journalism’s newly released Guide to Automated Journalism points out, the use of algorithms to automatically generate news from structured data is increasingly impacting the journalistic industry. These algorithms can quickly and inexpensively create high volumes of news stories for a given topic. According to Tow, this has fueled journalists’ fears that automated content production will eventually eliminate newsroom jobs, while at the same time scholars and practitioners see the technology’s potential to improve news quality.

Tow’s guide summarizes recent research on the topic to provide overview of the current state of automated journalism, discusses key questions and potential implications of its adoption, and suggest avenues for future research.

Among the key findings…

For news consumers

People rate automated news as more credible than human-written news but do not particularly enjoy reading automated content.
Automated news is currently most suited for topics where providing facts in a quick and efficient way is more important than sophisticated narration, or where news did not exist previously and consumers thus have low expectations regarding the quality of the writing.
Little is known about news consumers’ demand for algorithmic transparency, such as whether they need (or want) to understand how algorithms work.

For news organizations

Since algorithms cannot be held accountable for errors, liability for automated content will rest with a natural person (e.g., the journalist or the publisher).
Algorithmic transparency and accountability will become critical when errors occur, in particular when covering controversial topics and/or personalizing news.
Apart from basic guidelines that news organizations should follow when automatically generating news, little is known about which information should be made transparent regarding how the algorithms work.