This column is a little cheerful, slightly analytical, both confident and tentative and just a tiny bit angry. But mostly, it's open, agreeable and conscientious. At least that's what IBM's Watson thinks.
Last week, IBM revealed that its Jeopardy-winning supercomputer has a new capability. It's called Watson Tone Analyzer. You can use it like spell check, except instead of checking your spelling, it checks the "tone" of your writing. (And, by the way, when I say you can use Watson Tone Analyzer, you can literally use it right now on IBM's experimental public page.)
Watson Tone Analyzer is part of a new generation of writing tools that go far beyond the old spelling and grammar check. Instead, they help you polish and perfect your writing to achieve very specific goals.
Of course, there is already software that does all the writing for you. For example, companies like Automated Insights and Narrative Science offer products that take published data (such as financial numbers or sports scores, stats and other data) and turn it into prose, usually in the form of news stories or financial reports.
Here are examples of current news stories written by Automated Insights' product, which is called Wordsmith.
The fact that this technology can do this kind of writing says a lot about this category of prose. It's all utilitarian information delivery -- stories and reports that no writer wants to write and no reader wants to read. But the information must be conveyed somehow, and artificial intelligence is far cheaper than real intelligence.
Writing well is way too hard for computers. For example, a good writer wants to delight, be evocative and hold the attention of readers, and humor is a great way to do that. Thing is, computers just aren't funny.
New research from the University of Michigan, Columbia University, Yahoo Labs, and The New Yorker has found that even the most advanced artificial intelligence software can't tell the difference between a funny New Yorker cartoon caption and an unfunny one, even after analyzing massive data sets and hunting for correlations.
Prose-generating software robots represent interesting technology, but they've got a long way to go before they can write stories people want to read.
A far more interesting branch of technology helps people write better, instead of trying to write for them. By write better, I mean to use language in a way that helps readers reach specific goals.
Watson Tone Analyzer is the newest of these technologies. It became available last week as part of the Watson Developer Cloud application programming interfaces and software developer kits, which are the tools IBM offers to developers so that they can use Watson's capabilities in their software.
Watson Tone Analyzer rates your language in three categories:
You'll note that the "judgment" in these three categories is positive or negative. One of Watson Tone Analyzer's potential uses is to help you boost the positive and cut the negative.
Other uses might be to customize or adjust the tone of marketing messages for specific target audiences, market research, PR and automated contact center management, according to IBM.
One other potential application that is very interesting is that the technology could give virtual assistants -- such as Apple's Siri, Google's Google Now, Microsoft's Cortana or Amazon's Alexa -- the ability to "understand" the "tone" of their users' requests and then respond with an appropriate "tone." For example, by detecting elation or sadness, one's virtual assistant could respond with excitement or empathy, respectively.
When you process your words in the Watson Tone Analyzer, it highlights and color-codes all the words that contribute to tone, and by clicking on those words you can see Watson's suggested alternatives and improvements.
IBM expects developers to create Watson Tone Analyzer plug-ins for browsers, email applications, social-media front ends and other applications.
While all this sounds great, the trouble is that "tone" in language is, to date, impossible for software to deal with. Back to my own example, Watson Tone Analyzer detected "anger" in my prose, but only because I was describing the ability of Watson Tone Analyzer to detect anger. The word "anger" repeated several times caused Watson to say, in effect, "Hey, calm down. Why so angry?"
This highlights the vast distance that artificial intelligence has to go before it can know the difference between talking about anger and writing in an angry tone.
In that respect, Watson is useless for most people who write well. But that's not the case with another major product in this category, called Textio.
A cloud-based artificial intelligence service, Textio is another example of how software is trying to help people write better -- or, at least, more effectively in the achievement of specific goals.
Textio was founded by big-data experts from Microsoft and Amazon. Their slogan is "words + data = magic."
Textio applies big data to link language with specific outcomes. For instance, verbatim job ads can be fed into the Textio algorithm, along with data on who applied, and the system can figure out which words and phrases either succeeded or failed in support of the hiring company's recruiting goals.
For example, if a company's goal is to not push away qualified female candidates, it's useful to learn from Textio that phrases like "under pressure" (as in, "we're looking for a candidate that works well under pressure") tend to drive women job hunters away, while phrases like "passion for learning" tend to attract women to jobs.
Some of the "gender biases" that Textio ferrets out with its big-data crunching are puzzling, but they can be verified statistically. For example, more women are more likely to apply for a job if the word extraordinary is used in the listing instead of the word exceptional.
Gender bias in job postings is one problem Textio claims to help with. The other is the need to simply hire better candidates, regardless of gender.
Textio costs $59 per user per month. After you sign up, you can just copy and paste a job posting into the Textio Web form, and the system will spit out its analysis.
Textio will highlight words and phrases known to turn away candidates, either because they're too jargony or too cliché, or because they contain keywords that Textio's analysis has determined will result in inferior candidates or unsuccessful hires.
Before Textio got into the business of detecting gender bias, the company used its analytical kung fu to try to predict which Kickstarter projects would be funded. And in the process, it discovered that the way a Kickstarter page was built and worded had a bigger influence on funding than what the product was.
Even now, according to Textio CEO and co-founder Kieran Snyder, who has a Ph.D. in linguistics and worked at both Microsoft and Amazon, people use Textio's service to evaluate all kinds of communications, even though the system is optimized on a huge set of job listings.
Unlike Watson Tone Analyzer, Textio could be significantly useful even to the most skilled writers, such as professional novelists or, say, tech journalists.
Even great writers can (and often do) write in a way that's unappealing to one gender or another, or in a way that will unintentionally push away prospective employees or crowd-funding investors.
The reason Textio works is that it doesn't try to understand human language -- something far beyond even the most advanced A.I. Instead, it does what computers are good at -- it finds correlations in data sets. It knows that the word exceptional in a job listing will attract fewer women candidates than the word extraordinary, even though it has no idea what exceptional means or why the correlation exists.
Some people may be tempted to fear that software, supercomputers and algorithms are going to replace us all -- including those of us who write for a living or for whom writing is a major part of how we make our living. Some may be tempted to dismiss these fears and say that software can never replace people in these discipline. Either way, this technology is astounding.
But there is a winning combination in all of this. As the technology gets better, it's becoming clear that, ultimately, the literary and creative skills of human writers combined with artificial intelligence writing tools can help us communicate better.