Skip to Content

Messenger Bots Are Overhyped, Underpowered—and Growing like Crazy

They may not be particularly useful yet, but they’re being created faster than apps were in their heyday.
September 16, 2016

The world went mad for bots when Facebook promised that a legion of automated assistants would help us tackle everyday problems. While they’ve yet to truly deliver on that promise, they’re certainly being developed at a rapid rate.

Five months on from Facebook’s grand unveiling of its interactive bots, which are designed to help people “communicate with businesses” (read: buy stuff), the social network has acknowledged that it may have exaggerated their early abilities. This week, the company’s Messenger chief, David Marcus, admitted that the idea “got really overhyped really, really quickly” and that the resulting bots have not performed as well as he hoped.

But it seems that the hype either is well placed or is driving fanatic developers to build bots without much thought for how useful they’ll be. According to research from Citigroup cited by Bloomberg, the increase in the number of bots available on Facebook’s Messenger platform is 70 percent greater than the growth in the number of apps in Apple’s App Store shortly after launch.

That’s not the only parallel to be drawn between bots and apps. According to the Financial Times, the former head of Evernote, Phil Libin, thinks we’re in a period when we’re being inundated with bots that are little more than gimmicks. Early adopters of the iPhone will remember a similar situation with apps in 2007.

Mercifully, future bots do look set to become more useful, albeit slowly. Bots on Facebook can now accept payments, which should in theory make them rather more capable in terms of actually getting things done. First off the mark is Domino’s, meaning you can now (lucky you) order a bad pizza from within Facebook’s messaging app.

Meanwhile, in the same lab that created Siri, a new bot is being developed that will be able to sense your mood and respond accordingly. Using machine learning, the system could learn to, say, slow down if you seem confused, or use different language if you appear frustrated.

Which, for now at least, you’re likely to be.

(Read more: Financial Times, Bloomberg, The Verge, TechCrunch, “Facebook Wants You to Chat with Business Bots,” “Customer Service Bots Are Getting Better at Detecting Your Agitation”)

Keep Reading

Most Popular

Large language models can do jaw-dropping things. But nobody knows exactly why.

And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.

OpenAI teases an amazing new generative video model called Sora

The firm is sharing Sora with a small group of safety testers but the rest of us will have to wait to learn more.

Google’s Gemini is now in everything. Here’s how you can try it out.

Gmail, Docs, and more will now come with Gemini baked in. But Europeans will have to wait before they can download the app.

This baby with a head camera helped teach an AI how kids learn language

A neural network trained on the experiences of a single young child managed to learn one of the core components of language: how to match words to the objects they represent.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.