media update’s Aisling McCarthy gives you the low-down on what AI is, some important terminology and how AI will affect the media, marketing and PR industries.
You may have found it difficult to ignore something as widely discussed as AI.
The technology that’s loved by many, and misunderstood by some, is more than just a one-trick pony.
What is AI?
AI refers to the development of computer systems that are able to perform tasks that would normally require human intelligence.
But it’s far more than just one type of technology – it’s a collection of powerful technologies that include:
Machine learning
A process in which machines are fed data, and continually develop the algorithms they have been programmed with. The more data the machines are fed, the more accurately it can process similar information in future, and the more sophisticated the algorithms will become.
Neural networks
A method of processing vast amounts of data, which is modelled on the way the human brain interprets information. Neural networks consist of layers of nodes that receive data, extract the most relevant information and send the data along to the next node.
Natural language processing
A component of machine learning that processes, sorts and categorises various elements of text. While a human can inherently understand the meaning of sentences and paragraphs, a computer cannot really understand language. Using the mechanics of language, computers can, however, identify the context and grammatical use of words in sentences.
Computer vision
This technology allows computers to identify patterns and recognise objects in images. It is used by some advert tracking companies to detect the logos of thousands of brands and businesses in newspapers and magazines. This technology allows the computer to understand what they ‘see’, which is why it is being used in self-driving cars, augmented reality as well as the development of robots.
Are there any terms I should know about?
While there is a huge amount of AI terminology, here are some of the most important terms to know:
- Algorithm: A set of steps that runs on a computer program and is designed to solve a problem. These problems are solved by running through a number of processes, which all have their own specific rules.
- Chatbot: A computer program that can simulate conversation with human users via a chat interface. Numerous brands have invested in chatbots on their social media accounts or websites to answer questions that consumers have about their products or services.
- Data mining: The process of extracting information from extremely large sets of data, and establishing patterns within it. It is a useful way to process Big Data, as it can be difficult to manually identify trends and find actionable insights within mounds of information.
- Image recognition: This technology, also known as ‘computer vision’, allows computers to identify patterns and recognise objects in images. It allows the computer to understand what they ‘see’, which is why it is being used in self-driving cars, augmented reality as well as the development of robots.
- Sentiment analysis: An AI process that studies opinions, attitudes, views and emotions that people express in text. Once these have been analysed, the sentiment analysis can mark the text, sentence by sentence, as being positive, negative or balanced.
- Turing Test: A test created by Alan Turing in 1951, designed to determine whether or not a computer could be classified as ‘intelligent’. It tests a machine’s ability to behave in a way that is inseparable from a human.
How will AI affect the media, marketing and PR industries?
The media industry
1. It will help journalists identify hot topics
AI-powered engines have the ability to process mountains of data at high speeds to find trends and common themes within the information. An AI engine can, for example, scan thousands of recent posts in an online forum and find the topics being discussed most frequently.
The AI platform, IBM Watson, was assigned to do a similar task in 2016. The technology was roped in to analyse hordes of social media posts during the Wimbledon tennis tournament.
With the insights IBM Watson provided, Wimbledon’s digital team was able to pick up on popular sports themes being discussed on social media at the time of the tournament. The information allowed the team to create content that enticed the social media users, who were discussing these topics, to read Wimbledon’s content.
At the time,
IBM's Sam Seddon was reported as saying: "We can come up with insights much faster than humans can and inform the media team so they can decide what kind of content they should be offering."
Media intelligence companies like
Newsclip Media Monitoring use a combination of natural language processing and machine learning to identify trends within media coverage from a variety of media channels.
With information about topics that are trending on print and digital channels, journalists will be able to create more content that taps into these conversations – serving audiences with information they actually want.
2. AI will free up time in newsrooms
Numerous major publishers, including
Los Angeles Times and
Associated Press in the United States, have announced that machine learning-powered algorithms will be responsible for some of their journalistic reporting.
AI technology was used by The Washington Post during the 2016 US presidential election to automatically create articles from the data that was generated. The result was a huge number of stories targeted at niche audiences. The system also alerted journalists of unusual data.
A system like this could, in future, take care of repetitive, labour-intensive tasks like reporting on election results. This could free up time for journalists, who previously had to do these tasks to write content that requires their specialist skills – investigation, in-depth analysis and creating stories that have context.
3. Machines will uncover more secrets in data
In the same way that AI engines can find trends within forums or social media posts, these systems can also find anomalies and patterns within data.
Jeff Jarvis, director of the Tow-Knight Center for Entrepreneurial Journalism, recognises the potential of AI to find newsworthy information. In a
Medium post, he points to the ever-increasing amount of data being created by humans. This data, he says, is “available to analyse, looking for patterns and anomalies, pictures of how we live and the correlations and exceptions that can make news”.
He mentions the
Panama Papers, a collection of 11.5 million documents, which were analysed by 400 journalists from 100 news organisations in 80 countries. The collection was 2.6TB in size. In future, machine learning could be used to find patterns within data like this and pass the information onto journalists so they can get to the important work of investigating and reporting on these facts.
The marketing industry
1. AI lets marketers understand what consumers really want
At the 2017
APEX Awards, ex-Googler turned banker Brett St Clair explained that the exponential growth in technology has changed the way in which people interact with the world around them, and that personalisation is key to winning consumers over.
“Listening to your customers is vital – hyper-personalisation is a huge deal for consumers.”
With every activity and habit of users who are logged in online being recorded, marketers have a way to see the interests and preferences of every single consumer. However, processing that data is not possible without the use of AI.
AI-powered technology is able to process consumer data quickly, analysing it and identifying trends. This technology also makes it possible to personalise adverts to consumers based on what they have purchased before, or what products are frequently purchased together.
2. Marketers can be more efficient with AI
A huge part of working as a marketer involves resource-intensive processes to complete before serving the right ad to their audience. AI-powered technology can automate many of the time-consuming steps, such as data analysis.
In an article for
Digiday, Mindshare CEO Norm Johnston says that this leaves marketers with more time to communicate with their clients, improving the customer experience.
“The rapid evolution of AI in media will enable our people to focus on innovation and intelligence rather than repetition and reports.”
Ilyse Liffreing says that there is no reason to fear this development.
“The journey really is no different from what we have seen in past decades. Jobs and activities that need a low level of skills and intellect, and those that are replicable, get automated.”
3. AI can help marketers pre-empt customer service needs
Companies already gather tons of data from customers – logging purchases, customer-service enquiries and various other online and in-person requests. Using AI technology, marketers can utilise this information to pre-empt consumer service needs.
Not only can AI capture the data (saving marketers valuable time and effort), but it can mine the data as well, quickly finding trends and outliers. This will allow customer concerns to be dealt with on a timely, individual level, as well as help marketers anticipate issues before customers even log a service request.
“Look for [areas] where you can apply customer service data to solve trouble spots in your toughest customer journey,” says marketer Jeff Foley in
CMS Wire.
“Then, identify when and how you can improve your existing systems and processes to tap into customer data. Finally, make sure that pre-emptive service using customer data is a centrepiece of your company’s digital transformation plans over the next three to five years.”
The PR industry
1. Machine learning automates daily PR tasks
As PR professionals, you know that the industry requires you to spend a large portion of your day scheduling meetings, crafting press releases, analysing data and managing your client’s strategic insights. And in such a demanding job, humans are bound to make a few mistakes here and there.
With the automation, or at the very least, assistance, of these repetitive tasks, machine learning technology will be able to more accurately collect and collate data to help increase the time you have to craft creative client solutions.
It will also allow you to master your client relationships, which will ensure the longevity of your professional career. You can use your new-found time to communicate with clients more effectively, ask more questions and be present for more opportunities.
Developing these human-centric traits is what will drive you to gain and maintain good business relationships.
2. Being an influential PR pro is made easy with machine learning
In the PR industry, you know that it is important to influence the mind of the consumer in the direction that suits the client’s objectives. With the expansion of the Internet, a large distinction between ‘online influence’ and ‘real-world influence’ has been created.
“PR pros spend enormous resources on influencing people who might not be influential at all,” says Raf Weverbergh, managing partner of Brussels-based PR agency FINN PR and founder of Mustr.
By using machine learning to assist you in classifying relevance and reach, you can ensure that you will be able to attract the right influencer for your client.
3. Machine learning can assist PRs in formulating news insights
As a PR, you know that one of the best ways to build, enhance and protect your clients’ brands is by staying informed with the latest news and events. News never stops pouring in, meaning that you need to be constantly monitoring the media and looking for trends.
Machine learning technology has the capacity to work around the clock to collect and collate the news so that you don’t have to, leaving you with more time to uncover insights that can inform your campaigns.
Did you know that AI can actually help humans with their day-to-day tasks? Find out these Three ways to be a better human with AI.