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Archive for the 'Artificial Intelligence' Category

You’ve probably experienced both these frustrations with search engines: You’re not quite sure which terms to use, so you poke around hoping you’ll find something relevant, or you get lots of irrelevant results that happen to include your search terms but have nothing to do with what you are looking for.

Text mining, also known as text analytics, promises the ability to find meaning and patterns in mountains of textual material by going far beyond conventional search capabilities. Unlike simple word and phrase searches that require exact or near-exact matches, text mining systems can find relevant material even if you don’t know the specific terminology the sources use, or if they use different words to express the same concepts. By applying linguistic principles through natural language processing, text mining systems can recognize meaning in context. This capability also helps text mining tools filter out irrelevant material that uses the same terms, such as excluding material about biological reproduction if you are searching for material about document or file reproduction.

Another major benefit of text mining is the ability to copy all the searched material and reorganize it into consistent records, even if it came from a variety of sources in different formats. For example, a system could be instructed to pull in social media posts, emails, and text messages and “clean” and merge them into a single data set for easier analysis.

Text mining is a potential solution whenever a business needs to analyze hundreds, thousands, or even millions of text records. Examples of current applications include product research and development (such as searching patent records for similar designs), sentiment analysis (finding trends of satisfaction or dissatisfaction in public tweets, customer emails, and other sources), competitive intelligence (finding out what competitors are up to by analyzing their document and social media output), and risk management (such as analyzing financial news and reports in search of potential risks).

Class activity ideas

  1. Natural language processing applies the same linguistic rules and concepts that humans use to encode and decode language. Ask students if they think computers will ever be able to understand text the way that humans can. Why or why not?
  2. How do students feel about their public social media posts being available for companies and other organizations to analyze?

 

Sources: “About Text Mining,” IBM Knowledge Center, accessed 7 April 2018, www.ibm.com; “What Is NLP Text Mining?” Linguamatics, accessed 7 April 2018, www.linguamatics.com; Text Mining Applications: 10 Examples Today,” Expert System, 18 April 2016, www.expertsystem.com.



The last few decades have been marked by waves of technology-driven innovation in business communication, starting with digital’s disruption of print communication, then social media giving a voice to everyone in the marketplace, followed by the way mobile is freeing communicators from their desks.

We’re well into the next wave, and this one could be the most intriguing and far-reaching of all: the application of artificial intelligence to enhance the communication experience. Starting with the upcoming 13th Edition of Excellence in Business Communication (releasing in January 2019) we are covering communication uses of AI that students are likely to encounter on the job or in their job-search efforts.

The Recent Explosion of Business AI

Although “artificial intelligence” still has a science fiction ring to it, forms of AI are now used extensively in business and business communication. It’s a virtual guarantee that your students are already experiencing AI as consumers—Amazon, Apple, Facebook, Google, Microsoft, Netflix, and Spotify are just a few of the companies that rely on AI to deliver their services.

Research in AI has been going on for more than a half century, but the practical outcomes never really lived up to hopes until recently, when several developments converged within the space of a few years. First, the primary focus of the research shifted from pursuing the generalized, humanlike intelligence of science fiction (sometimes called general AI or strong AI) to developing specialized systems aimed at handling specific tasks such as reading text or recognizing images (called narrow AI or weak AI). Second, an AI method involving neural networks, which emulate the function of neurons in the brain, was refined in a way that made it much more powerful. And third, several critical computer capabilities became available around the same time: massive sets of data that AI systems could learn from, low-cost storage to handle all that data, and fast processors capable of handling the number-crunching that the most-common AI approaches require.

Communication Applications of AI

Thanks to these developments, AI is now being applied in virtually every functional area of business. Many of these applications involve business communication, including augmented writing, automated writing, emotion recognition, job applicant evaluation systems, chatbots and taskbots, robotic process automation, cognitive automation, voice recognition, real-time voice translation, and augmented ability systems. Here are a few specific examples:

  • Businesses use text mining for social listening—identifying themes (such as prevailing customer sentiment or threats to a company’s reputation) hidden in mountains of written information, from Twitter and Facebook posts to customer emails and surveys. The Clarabridge image shown above (click on the thumbnail for a larger version) illustrates the use of social listening in the hospitality industry.
  • The Textio augmented-writing system gives company recruiters real-time writing feedback while they draft job postings. By analyzing hundreds of millions of postings and comparing the candidate pools they attracted, the system is figuring out the most compelling way to describe job opportunities. Plus, the system can help writers avoid biased or exclusionary language by showing how various demographic groups respond to different word choices.
  • Any of your students who play fantasy football on Yahoo! Sports might be intrigued to know that the game summaries they receive each week are written by an AI system.

From a user’s perspective, AI-enhanced communication isn’t skills-based to the same degree as social media and mobile communication, but we believe it has become a vital topic to address in any well-rounded business communication course. In future posts, we’ll explore many of these applications and discuss how they are giving professionals powerful new tools to improve communication efficiency and effectiveness.

 

Adapted from Excellence in Business Communication, 13th Edition, Pearson, 2020.

Image: Courtesy Clarabridge



This is the fifth post in a series about technologies that are shaping the future of communication. We’ve been following technologies that cover an interesting array of possibilities, from enhancing existing communication modes to replacing at least one of the humans in a conversation to assisting people who have a variety of motor, vision, and cognitive impairments. They are all across the adoption curve, from technologies that are already approaching mainstream usage (such as bots and gamification) to a few that are closer to the sci-fi end of things (such as holograms and telepathic communication). Many of these systems rely on artificial intelligence, which is reshaping business communication in some profound ways. All of them present interesting discussion topics for business communication, because they get to the heart of matter, which is trying to exchange information and meaning in the most effective and efficient ways possible. To offer students a peek into the future, we've started covering these innovations in our business communication texts, beginning with the 14th Edition of Business Communication Today (published January 2017) and the 8th Edition of Business Communication Essentials (published January 2018).

 

The Internet of Things (IoT) refers to the several billion devices now connected to the Internet and the networking potential of having all these gadgets communicate with each other, feed data into powerful analysis and control algorithms, and interact with people and the physical environment. These “things” range from simple sensors that measure temperature, location, and other parameters all the way up to robots and other complex systems. People and animals with Internet-capable sensors (such as implanted chips) or devices also qualify as things in this model.

Imagine you walk into a department store and your mobile phone automatically gives you directions to the aisle where you could find the clothing styles you have recently been browsing online or discussing in social media. When you reach that aisle, a coupon pops up on your phone with a discount on the specific items you’re considering. When you pull a garment off the rack, the store’s customer database checks other purchases you’ve made and suggests which items you already own that coordinate with this piece. If you could use an accessory to complete the outfit, the store’s computers can tell your phone just where to take you. And if you need more advice, you can text or talk—and possibly not know whether you’re conversing with a store employee or an automated chat algorithm.

Now imagine this simple concept expanded and applied in various ways to industrial facilities, agriculture, transportation, buildings, health care, and other systems. By relying on networked IoT devices for such communication functions as observing, measuring, and reporting, these enhanced systems can supplement or replace communication flows that were previously carried out by human participants. IoT raises some serious concerns about security and privacy, but it’s already a multitrillion-dollar industry that doesn't show any signs of slowing down.

IoT's impact on business communication will be fascinating to watch over the next few years, particularly as the technology gets linked with automated writing and other AI tools. Ideally, it will take over some routine communication tasks and give businesspeople more time for higher-level communication and strategizing.

Class activity idea: Have students research the current state of IoT innovation to identify one way in which the technology has the potential to change business communication practices, such as automated data collection and status reporting. Do they agree with the predictions the experts make? Why or why not?

 

Sources: Steve Ranger, “What Is the IoT? Everything You Need to Know About the Internet of Things Right Now,” ZDNet, 19 January 2018, www.xdnet.com; Bernard Marr, “The Internet of Things (IOT) Will Be Massive In 2018: Here Are the 4 Predictions From IBM,” Forbes, 4 January 2018, www.forbes.com.

Image: laboratoriolinux on VisualHunt.comCC BY-NC-SA

 



smiles-conversely-chatThis is the third post in a series about technologies that are shaping the future of communication. We’ve been following technologies that cover an interesting array of possibilities, from enhancing existing communication modes to replacing at least one of the humans in a conversation to assisting people who have a variety of motor, vision, and cognitive impairments. They are all across the adoption curve, from technologies that are already approaching mainstream usage (such as bots and gamification) to a few that are closer to the sci-fi end of things (such as holograms and telepathic communication). Many of these systems rely on artificial intelligence, which is reshaping business communication in some profound ways. All of them present interesting discussion topics for business communication because they get to the heart of matter, which is trying to exchange information and meaning in the most effective and efficient ways possible. To offer students a peek into the future, we've started covering these innovations in our business communication texts, beginning with the 14th Edition of Business Communication Today, which launched in January 2017, and 8th Edition of Business Communication Essentials, which launches in January 2018.

Trying to converse in a language in which you are not fully fluent presents a rather staggering cognitive workload. As a listener, you have to convert the incoming sounds to discrete words and assemble those words into coherent phrases and sentences in order to extract the meaning—and if the other party uses idioms or slang, the task can get exponentially harder. And unlike reading a written document, you have to do all this processing almost instantaneously, without the luxury of going back over something you didn't get. As a speaker, you have to find the right words, assemble them into phrases and sentences using the language’s grammar rules, and then pronounce them all correctly enough so they make sense to the other party. Honing this level of proficiency can take years of study and practice.

Machine translation has been one of the long-standing goals of artificial intelligence, offering hope for real-time communication between people who don’t have a common language. Developers have made impressive strides toward translating speech in near real-time by combining deep learning techniques that apply computational models of human neural networks to massive data sets of languages with advances in natural language processing and natural language generation.

Systems such as Skype Translator and Google Translate are getting remarkably adept. Google’s new Pixel Buds ear buds offer nearly instantaneous translation across dozens of languages (when paired to a Google Pixel phone), making it possible to travel much of the world and converse with anyone who is similarly equipped. A variety of other smartphone and smartwatch apps offer translation without the need for each party to have identical equipment; speakers take turns talking to the device, then listen as it outputs the translated speech. Microsoft’s PowerPoint Presentation Translator adds real-time translation for presenters, making it easier for global professionals to connect with their audiences.

This video from the launch event for Google Pixel Buds shows the devices translating a conversation between English and Swedish. (The translation demonstration starts at 0:48.)

Class activity idea: Ask students to research several apps and other solutions that offer real-time translation. Are they being used successfully in business communication? Do students think these tools will ever eliminate the need to learn other languages in order to communicate effectively with diverse, global audiences?

 

Sources: Andrew Tarantola, “Google’s Pixel Buds Translation Will Change the World, Engadget, 4 October 2017, endgadget.com; “Skype Translator,” Skype, accessed 10 November 2017, www.skype.com; iTranslate Voice, accessed 10 February 2017, itranslatevoice.com; Davide Castelvecchi, “Deep Learning Boosts Google Translate Tool,” Nature, 27 September 2016, nature.com; Devindra Hardawar, “Microsoft PowerPoint Adds Real-Time Presentation Translation,” Engadget, 10 May 2017, endgadget.com.

Photo via Visualhunt



ViolinistThis is the second post in a series about technologies that are shaping the future of communication. We’ve been following a dozen-plus technologies that cover an interesting array of possibilities, from enhancing existing communication modes to replacing at least one of the humans in a conversation to assisting people who have a variety of motor, vision, and cognitive impairments. They are all across the adoption curve, from technologies that are already approaching mainstream usage (such as bots and gamification) to a few that are closer to the sci-fi end of things (such as holograms and telepathic communication). Many of these systems rely on artificial intelligence, which is reshaping business communication in some profound ways. All of them present interesting discussion topics for business communication, because they get to the heart of matter, which is trying to exchange information and meaning in the most effective and efficient ways possible. To offer students a peek into the future, we've started covering these innovations in our business communication texts, beginning with the 14th Edition of Business Communication Today, which launched this past January.

Most people like to think they are unbiased and capable of making fair, objectives decisions when it comes to judging or assessing others. Unfortunately, that is far from reality. Decades of research suggests that unconscious or implicit bias is universal, and these attitudes and stereotypes affect decision making in ways that people aren’t aware of. Even people who consciously go out of their way to avoid biased assumptions can be influenced by unconscious biases that have been accumulating since childhood.

Implicit bias has been a longstanding concern in job interviewing and hiring decisions. A classic case that opened many eyes to the problem involved classical musicians auditioning for symphony orchestras. In the 1970s, women made up only 5 percent of professional symphony musicians. Orchestras gradually moved to blind auditions, where the performer is hidden behind a curtain so the people evaluating them can hear but not see them—meaning they can’t make judgments based on gender, age, appearances, or anything other than how well the musicians play. Within a decade, the ratio of women had risen to 25 percent.

The concept is now applied across a range of industries and professions. The GapJumpers system, for example, enables job applicants to take skill auditions anonymously. The employers sponsoring the auditions have no personal information about the applicants when they judge the scores—it is strictly about talent. Applicants who do well on blind auditions are then invited to participate in a more conventional interviewing process, at which point the employers learn who they are. GapJumpers’ analysis indicates that more women and more community college graduates make it through to the second stage of interviewing than they do in a traditional selection process.

As your students start to turn their attention to the job market and begin preparing their employment communication packages and interviewing strategies, this is a great time to discuss the intersection of human and machine communication. Students may encounter a range of communication technologies during their job searches, from online skill auditions to applicant tracking systems that “read” their résumés before any humans see them. We’ll continue to explore these innovations here on the blog and in all the upcoming editions of Bovée and Thill texts.

Class activity idea: Ask students to research current practices in blind auditions across professions. Is the technique catching on? Do they think variations on this method hold promise to reduce employment discrimination?

Sources: “Understanding Implicit Bias,” Kirwan Institute for the Study of Race and Ethnicity, accessed 3 May 2017, kirwaninstitute.osu.edu; Sarah Fister Gale, “Turning a Blind Eye to Hiring a Good Idea,” Workforce, 30 September 2016, www.workforce.com; GapJumpers, accessed 3 May 2017, www.gapjumpers.me; Jacquelyn Smith, “Why Companies Are Using ‘Blind Auditions’ to Hire Top Talent,” Business Insider, 31 May 2015, www.businessinsider.com.

Photo credit: FaceMePLS via Visual hunt / CC BY