Expanding comments with AI

The problem with human moderators is that they have human limitations that cannot keep up with a

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huge influx of comments. That was the problem the New York Times faced in balancing reader comments demand with an editorial standard of civility for all published comments. Its solution was a partnership with , an incubator owned by Google's parent company, Alphabet.

Back in September, the Times announced the partnership in an article that set out the challenge faced by its 14 moderators tasked with reviewing the comments on the 10% of articles that do allow them. That alone amounted to 11,000 comments a day. As the article invited readers to try their hand at moderating, it was entitled Approve or Reject: Can You Moderate Five New York Times Comments?

I took the test. The official summary of my results were: "You moderated 4 out of 5 comments as the Community desk would have, and it took you 81 seconds. Moderating the 11,000 comments posted to nytimes.com each day would take you 49.5 hours."

That summation was followed by this: "Don't feel too bad; reviewing all of these comments takes us a long time, too." According to my calculations, however, the Times actually allows more time for their moderators. Given 14 people working 8 hours a day, the number of working hours each day would be 112, or more than twice the number of hours they said would be required for my rate of moderation.

That investment of so many hours is not something they regret, as they regard it as a requisite part of building up "one of the best communities on the web." However, they recognize that needs must dictate a new approach. That's where the machine assistance enters into the picture, enabling the same number of humans to effectively moderate a much larger number of comments and reduce the delay for reviewing time.

Flash forward to June 13, 2017, and the Gray Lady herself announces: The Times Sharply Increases Articles Open for Comments, Using Google's Technolog

Read more in How AI Can Moderate Comments, Eliminate Trolls

Personalized video marketing

“What's in a name?” Possibly quite a lot when it comes to personalized marketing.

Several months back I received a marketing email from Sprinklr that was rather ironic given its message about effective use of data. It opened like this: “ Hi {lead.First Name:default=}.”  Obviously, something went wrong, and I saw the code rather than my name.

Of course, personalized emails are not all that unusual any more, so some marketers have upped their game with personalized video. After receiving the “A Dog's Purpose” video (above) — in a correctly personalized email — I contacted Adgreetz's co-founder and CEO Eric Frankel about what data is used for this kind of personalized video marketing, and how the video was delivered to people who are 1) dog owners, and 2) have a dog of that particular name? 

read more in A Marketer's Best Friend

Define "good"

I don't mean that in an abstract way or with the kind of depths of thought about what we mean by "qulity" that drove the author of Zen and the Art of Motorcycle Maintenance toward madness. I just mean it in the context of "good pay."  The question arises from this job posting:

We pay really well because we want really good content.
“Really good content” means well-constructed, well-reasoned arguments that are also extremely engaging.
Articles need to be a minimum of 500 words, though analysis pieces need to be a minimum of 1,000 words
We provide you with the headlines and an initial source
We’re looking for both weekday AND weekend writers. There’s a bonus for weekend writers.
We often promote writers to management positions

Ah, I think, they say they have high standards but compensate accordingly, so I was picturing a minimum of three figures and not just with a one or two at the beginning of the number. But my illusions about some shared view on what constitutes "good" pay was shattered an instant later as I read on:

What We’ll PayPay will start at $15/article during the test period. Afterward, we’ll bump it to $20/article for weekday news articles, and $30/article for weekday analysis articles. Weekend news articles are $25/article and weekend analysis pieces are $35/article. 

So, basically, they'll pay you what teen babysitters get per hour for an article that should take you several hours to write.  Certainly, any beginning writer -- and that's the only kind who likely would apply for this job -- would likely need more than hour to crank out an article of that length that is not merely recycled platitudes.

Related: http://writewaypro.blogspot.com/2017/05/on-working-almost-for-free.html
http://writewaypro.blogspot.com/2016/05/writing-for-free-is-not-deductible.html
http://writewaypro.blogspot.com/2016/05/an-idiots-guide-for-writers.html

AI gets a boost from curiosity

As data analytics become increasingly driven by artificial intelligence (AI),

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researchers search for a way to drive machine learning. The key ingredient its future development may be a dash of curiosity.

There are all kinds of AI systems currently used by various businesses with different names like Alexa and Albert to personalize then. Perhaps it's time for an AI system named George after the monkey whose curiosity propels him into various adventures.

That would be an apt choice for the Intrinsic Curiosity Module (ICM) developed by a group of four researchers at University of California, Berkeley. The attempt to inject curiosity to achieve self-motivated advances in machine learning was the subject of their paper, Curiosity-driven Exploration by Self-supervised Prediction, that was just submitted to the 34th International Conference on Machine Learning (ICML 2017).

Their premise is that external rewards for learning are of necessity limited and actually rather rare in real life. That doesn't mean that people stop exploring or seeking out answers even when there are no prizes for doing. They are motivated by their own human curiosity. Infusing that kind of motivation in a virtual agent gets it to test things out for itself even when not directed to do so. The test of the effect was done in monitoring how far it would proceed in two video games, VizDoom and Super Mario Bros. as you see in the demo video here:

Read more in Machine Learning Taps Power of Curiosity