By Rosalie Chan.

With the rise of email came came the rise of spam filling inboxes.

Email has become sophisticated faster than spamming technology and now, the internet’s junk mail is often caught in a folder; out of sight and out of mind are messages with the subject line “Kindly get back to me urgently” and the greeting “Dear Beneficiary.”

There’s good news for anybody who sees fake news — not the sort that’s simply true but politically difficult for the president; but actual, fake, conspiracy theory-baiting chum — as another form of spam.

At least that’s what Dean Pomerleau, research scientist at Carnegie Mellon University’s Robotics Institute, said recently during a panel in New York on the proliferation of fake news. We solved the spam problem using artificial intelligence, he argued, and with A.I., we can solve the problem of fake news by filtering out credible news from the misinformation. Wheat from chaff, etc.

Also on the panel, put on by the New York Daily News Innovation Lab in Manhattan, was CNN political commentator Sally Kohn, who was well aware of her network’s reputation as purveyors of fakery over its coverage of the notoriously sensitive President Donald Trump.

“According to half the country, that means I’m an expert on fake news,” Kohn said. “As a citizen, I’m invested in facts. As a journalist, even an opinion journalist, I’m grounded in facts.”

At the panel, Pomerleau spoke about ways A.I. can combat fake news. He co-directs the Fake News Challenge, a competition to create a fact-checking tool. The idea for the challenge started shortly after the election. So far, there are almost 200 teams signed up and 300 people who registered for the Fake News Challenge Slack channel.

“We were speculating among friends, what could we as machine-learning people do to improve the situation moving forward? That was the genesis of the idea,” Pomerleau tells Inverse.

Even the challenge problem for the annual International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction and Behavior Representation in Modeling and Simulation is fake news and propaganda. “Simulation studies, data science studies, machine learning studies, and network science studies are all encouraged,” the prompt announced when it was posted recently.

Inverse asked Pomerleau just how fake news will be killed and here’s what he said.

How do we see A.I. creating fake news in the future?

I think in the near future, technology is likely to help in the creative process. It won’t be too long before generated video can be created, very much like PhotoShop. Those two things together will really undermine our ability to believe what we see. Image processing and audio processing tools will foster easy creation by just about anyone to create fake news.

How can A.I. fight fake news?

Using smart filtering and content analysis and natural language processing — these can all be used as signals to an algorithm that’s attuned to detect fake news, just like we have filters for spam to prevent it from getting into your inbox. There are ways A.I. can assist humans in identifying fake news, or in the future, do it automatically.

What are some ways the Fake News Challenge has addressed fake news so far?

We kicked it off as a casual wager on Twitter, thinking naively we can jump to the end stage and build a system that can classify real news versus fake news. It turns out it’s a much more subtle problem than that. You run into problems like opinion pieces or satire that falls into a gray area that makes it a much more challenging task that so far requires some human judgment.

We backed off the task of trying to predict the fake versus real distinction to focus on a tool to help fact-checkers by solving a problem. It will allow fact-checkers or journalists to gather the best stories on both sides of an issue. By gathering those pro-con arguments quickly, human fact checkers will be able to quickly assess what the truth is and debunking things that are clearly made up.

How can A.I. help the average user who might read or run into fake news?

We’ve actually started brainstorming about how the kind of tool we’re building can assist the average individual rather than news organizations. Suppose you read an article that makes a claim about a fact in the article. You can imagine that if you highlight it or click a button, you can use our detection tool that finds other content on the internet that takes the pro or con stance and find out just how credible the claim is in the story you’re currently reading.

How might tech companies respond to fake news?

I would love to see a more concerted effort for tech companies. They’ve set up industry groups for other things. They recently created partnerships for A.I., and I’d like to see them do something similar and do a best practices industry group to address fake news.

I think one of the biggest problems is the economy has made it quite lucrative to game the system and get more clicks and eyeballs because that’s how you make money on the Internet now. The model that tech giants have created has seriously undermined the news media industry to make it almost incumbent for news media creators to create tantalizing headlines that get people to click on them for whatever reason.

[The Fake News Challenge has] caught the attention of well-meaning people who see fake news as a big problem and use their machine learning skills and try to address it. I’ve been a little disappointed that the tech community and machine learning community haven’t faced up to the responsibility of using their skills in development to benefit society.

One of the reasons we’ve attracted so many smart people from the tech community is it does offer the opportunity to use some of the cutting-edge machine learning and natural language processing work in A.I. to do something for the social good right here and right now.

This interview has been edited for clarity and brevity.

Photos via Flickr / The Public Domain Review

By Rosalie Chan

Rosalie is an editorial intern at Inverse. She grew up in the Chicago area and studies journalism and computer science at Northwestern University. She has previously worked for TIME and the Chicago Reporter. She likes writing, books, podcasts and running.

Sourced from Inverse Innovation

We live in an era where we can tell a virtual assistant like Amazon’s Alexa to re-order washing powder while we’re video chatting with friends across the globe and Googling how long it took to build the pyramids.

We can organise a weekend away with friends in a WhatsApp group and have a chat bot change the time of our flight.

But we have almost none of that technology at work.

It won’t be this way for long. Everyone, and not just millennials, clearly want more intelligent software at work. We’re moving from a workplace where Bring Your Own Device (BYOD) is the norm to one where Bring Your Own Software (BYOS) is the expectation.

The return of Clippy? Not so much.

Workplace technology doesn’t just need to catch up — it needs to leap ahead. The demands of a modern digital workplace call for innovations such as smart bots, micro applications, artificial intelligence, and team messaging.

A study of business leaders by outsourcing giant Capita found that 91% of HR Directors see automation as an opportunity, with 76% believing it will drive greater productivity.

Our previous blog post dealt with the dire state of software at work in contrast to the smart software we now have at home. Here, we’ll offer some solutions and set out a vision of a modern digital workplace.

1. The end of email
Two of the biggest roadblocks to modern productivity were actually building blocks in the past: meetings and emails.

Almost everyone hates meetings — it’s that sinking feeling your time would be better spent doing something else. It’s the same with email. According to research by McKinsey as far back as 2012, employees can spend as much as 28 per cent of their day reading and responding to emails. Yet meetings and emails still prevail as the primary time drain, despite there being clearly better ways of communicating and getting things done.

The benefits of a digital workplace go much further though. They can actually help make companies more flexible and agile, not to mention more attractive to talent.

Using modern messaging apps, a unified interface to work becomes possible, where conversations and applications come together in one place. Group messaging replaces email for projects, initiatives and team collaboration. Workflow and actions take place within the conversation, using intelligent bots.

Furthermore, the content within these faster, real-time conversations becomes an easily searchable resource of all past organisational knowledge.

2. Searchable information
Among the manifold problems with enterprise software, one of the principal shortcomings is the archaic user experience. The simple solution is to use an intelligent interface that can access the most relevant functions and data from within these enterprise systems and present them in a more intuitive and streamlined way.

Search remains a real problem at work — looking for the right information in so many different places. The rise of BYOS makes things worse, as people bringing more cloud applications into their work multiplies the numer of potential locations. How much time do you spend asking, “Was that file on Sharepoint or Dropbox? Where are we tracking that project?”

McKinsey found that the aforementioned employees wasting 28 per cent of their time managing email were spending a further 20 per cent on looking for internal information or for colleagues to help them with something.

By connecting your individual applications to a single intelligent app, a universal search function then allows you to search across all content and applications. That means work can be treated as a single entirety, rather than as bits of content scattered across numerous independent silos.

At last, a single search box for work.

3. Everyone gets an assistant
In modern offices, the directors won’t be the only ones with an assistant. Now, with digital assistants becoming smarter, more intuitive and easier to use, anyone within the company can have a Alexa-like helper.

The growing crop of digital assistants are becoming more mainstream, thanks to endorsements from celebrities like Alec Baldwin and Missy Elliott. However, these digital assistants have practical uses in the office. Instead of using a paper calendar or trying to remember a schedule, just talking to a digital assistant can save time and money — and keep employees productive.

4. Real-time data
Data is the lifeblood of modern organisations, offering insights into customers and processes that are critical to decision making. But how easy is it to have the right data to hand, in the right place, at the right time? Most useful data is hidden away in silo’d systems that are hard to access.

But a modern enterprise messaging platform can use micro-apps and bots to talk to these systems in realtime, from anywhere, and get the information you need. Often before you even realise you need it.

Internal data is even harder to come by. Want to know the internal dynamics of your company and gain sentiment analysis from its people? Good luck. Want to know how well your employees like a new programme you started a few months ago? No chance.

But it doesn’t have to be this way. We can use sentiment analysis, bots and natural language processing to talk to thousands of employees — anonymously if necessary — in seconds.

Executives and managers can easily take the pulse of the office and see what can be improved and what is working smoothly, rather than wait for anecdotal feedback when it might be too late.

Businesses deserve better
The verdict on meetings and emails is loud and clear. People don’t like them, they waste huge amounts of time and productivity — and therefore money — and they are holding businesses back. Intelligent workplace technology such as messaging, bots and micro-apps offer new ways of doing everything better. It’s not a case of if you move to better ways of working, but when.

The digital workplace isn’t just new software you use at work. It is a whole new way of working. It’s about working intelligently.

We’re Blink, and we’re building the intelligent interface to work. Blink connects to your existing applications and applies modern intelligence to cut through the noise, automate tasks and help you accomplish more.

Sourced from Medium