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We Counter Hate

One of the most fascinating examples of social innovation Ive been tracking recently was the We Counter Hate platform, by Seattle-based agency POSSIBLE (now part of Wunderman Thompson Seattle) that sought to reduce hate speech on Twitter by turning retweets of these hateful messages into donations for a good cause.

Heres how it worked: Using machine learning, it first identified hateful speech on the platform. A human moderator then selected the most offensive and most dangerous tweets and attached an undeletable reply, which informed recipients that if they retweet the message, a donation will be committed to an anti-hate group. In a beautiful twist this non-profit wasLife After Hate, a group that helps members of extremist groups leave and transition to mainstream life.

Unfortunately (and ironically) on the very day I reached out to the team, Twitter decided to allow users to hide replies in their feeds in an effort to empower people faced with bullying and harassment, eliminating the reply function which was the main mechanism that gave #WeCounterHate its power and led to it being able to remove more than 20M potentialhatespeech impressions.

Undeterred, I caught up with some members of the core teamShawn Herron, Jason Carmel and Matt Gilmoreto find out more about their journey.

(From left to right)Shawn Herron, Experience Technology Director @ Wunderman ThompsonMatt ... [+] Gilmore, Creative Director @ Wunderman ThompsonJason Carmel, Chief Data Officer @ Wunderman Thompson

Afdhel Aziz: Gentlemen, welcome. How did the idea for WeCounterHate come about?

Shawn Herron: It started when we caught wind of what the citizens of the town of Wunsiedel, Germany were doing to combat the annual extremists that were descending on their town every year to hold rally and march through the streets. The towns people had devised a peaceful way to upend the extremists efforts by turning their hateful march into an involuntary walk-a-thon that benefitted EXIT Deutschland, an organization that helps people escape extremist groups. For every meter the neo Nazis marched 10 euro would be donated to Exit Deutschland. The question became, how can we scale something like that so anyone, anywhere, could have the ability to fight against hate in a meaningful way?

Jason Carmel: We knew that, to create scale, it had to be digital in nature and Twitter seemed like the perfect problem in need of a solution. We figured if we could reduce hate on a platform of that magnitude, even a small percentage, it could have a big impact. We started by developing an innovative machine-learning and natural-language processing technology that could identify and classify hate speech.

Matt Gilmore: But we still needed the mechanic, a catch 22, that would present those looking to spread hate on the platform with a no-win decision to make. Thats when we stumbled onto the fact that Twitter didnt allow people to delete comments on their tweets. The only way to remove a comment was to delete the post entirely. That mechanic is what gave us a way put a permanent marker, in the form of an image and message, on tweets containing hate speech. Its that permanent marker that let those looking to retweet, and spread hate, know that doing so would benefit an organization theyre opposed to, Life After Hate. No matter what they chose to do, love wins.

Aziz: Fascinating. So, what led you to the partnership with Life After Hate and how did that work?

Carmel: Staffed and founded by former hate group members and violent extremists, Life After Hate is a non-profit that helps people in extremist groups break from that hate-filled lifestyle. They offer a welcoming way out thats free of judgement.We collaborated with them in training the AI thats used to identify hate speech in near real time on Twitter. With the benefit of their knowledge our AI can even find hidden forms of hate speech (coded language, secret emoji combinations) in a vast sea of tweets. Their expertise was crucial to align the language we used when countering hate, making it more compassionate and matter-of-fact, rather than confrontational.

Herron: Additionally, their partnership just made perfect sense on a conceptual level as the beneficiary of the effort. If youre one of those people looking to spread hate on Twitter, youre much less likely to hit retweet knowing that youll be benefiting an organization youre opposed to.

Aziz: Was it hard to wade through that much hate speech? What surprised you?

Herron: Being exposed to all the hate filled tweets was easily the most difficult part of the whole thing. The human brain is not wired to read and see the kinds of messages we encountered for long periods of time. At the end of the countering process, after the AI identified hate, we always relied on a human moderator to validate it before countering/tagging it. We broke up the shifts between many volunteers, but it was always quite difficult when it was your shift.

Carmel: We learned that the identification of hate speech was much easier than categorizing it. Or initial understanding of hate speech, especially before Life After Hate helped us, was really just the movie version of hate speech and missed a lot of hidden context. We were also surprised at how much the language would evolve relative to current events. It was definitely something we had to stay on top of.

We were surprised by how broad a spectrum of people the hate was coming from. We went in thinking wed just encounter a bunch of thugs, but many of these people held themselves out as academics, comedians, or historians. The brands of hate some of them shared were nuanced and, in an insidious way, very compelling.

We were caught off guard by the amount of time and effort those who disliked our platform would take to slam or discredit it. A lot of these people are quite savvy and would go to great lengths to attempt to undermine our efforts. Outside of the things we dealt with in Twitter, one YouTube hate-fluencer made a video, close to an hour long, that wove all sorts of intricate theories and conspiracies about our platform.

Gilmore: We were also surprised by how wrong our instincts were. When we first started, the things we were seeing made us angry and frustrated. We wanted to come after these hateful people in an aggressive way. We wanted to fight back. Life After Hate was essential in helping course-correct our tone and message. They helped us understand (and wed like more people to know) the power of empathy combined with education, and its ability to remove walls rather than build them between people. It can be difficult to take this approach, but it ultimately gets everyone to a better place.

Aziz: I love that idea - empathy with education.What were the results of the work youve done so far? How did you measure success?

Carmel: The WeCounterHate platform radically outperformed expectations of identifying hate speech (91% success) relative to a human moderator, as we continued to improve the model over the course of the project.

When @WeCounterHatereplied to a tweet containing hate, it reduces the spread of that hate by an average of 54%. Furthermore, 19% of the "hatefluencers" deleted their original tweet outright once it had been countered.

By our estimates, the Hate Tweets we countered were shared roughly 20 million fewer times compared to similar Hate Tweets by the same authors that werent countered.

Matt: It was a pretty mind-bending exercise for people working in an ad agency, that have spent our entire careers trying to gain exposure for the work do on behalf of clients, to suddenly be trying to reduce impressions. We even began referring to WCH as the worlds first reverse-media plan, designed to reduce impressions by stopping retweets.

Aziz: So now that the project has ended, how do you hope to take this idea forward in an open source way?

Herron: Our hope was to counter hate speech online, while collecting insightful data about how hate speech online propagates. Going forward, hopefully this data will allow experts in the field to address the hate speech problem at a more systemic level. Our goal is to publicly open source archived data that has been gathered, hopefully next quarter (Q1 2020)

I love this idea on so many different levels. The ingenuity of finding a way to counteract hate speech without resorting to censorship. The partnership with Life After Hate to improve the sophistication of the detection. And the potential for this same model to be applied to so many different problems in the world (*anyone want to build a version for climate change deniers?). It proves that the creativity of the advertising world can truly be turned into a force for good, and for that I salute the team at Possible for showing whats, well, possible.

See the article here:

The Power Of Purpose: How We Counter Hate Used Artificial Intelligence To Battle Hate Speech Online - Forbes

To understand how humans might better marshal autonomous forces during battle in the near future, it helps to first consider the nature of mission command in the past.

Derived from a Prussian school of battle, mission command is a form of decentralized command and control. Think about a commander who is given an objective and then trusted to meet that goal to the best of their ability and to do so without conferring with higher-ups before taking further action. It is a style of operating with its own advantages and hurdles, obstacles that map closely onto the autonomous battlefield.

At one level, mission command really is a management of trust, said Ben Jensen, a professor of strategic studies at the Marine Corps University. Jensen spoke as part of a panel on multidomain operations at the Association of the United States Army AI and Autonomy symposium in November. Were continually moving choice and agency from the individual because of optimized algorithms helping [decision-making]. Is this fundamentally irreconcilable with the concept of mission command?

The problem for military leaders then is two-fold: can humans trust the information and advice they receive from artificial intelligence? And, related, can those humans also trust that any autonomous machines they are directing are pursuing objectives the same way people would?

To the first point, Robert Brown, director of the Pentagons multidomain task force, emphasized that using AI tools means trusting commanders to act on that information in a timely manner.

A mission command is saying: youre going to provide your subordinates the depth, the best data, you can get them and youre going to need AI to get that quality data. But then thats balanced with their own ground and then the art of whats happening, Brown said. We have to be careful. You certainly can lose that speed and velocity of decision.

Before the tools ever get to the battlefield, before the algorithms are ever bent toward war, military leaders must ensure the tools as designed actually do what service members need.

How do we create the right type of decision aids that still empower people to make the call, but gives them the information content to move faster? said Tony Frazier, an executive at Maxar Technologies.

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An intelligence product, using AI to provide analysis and information to combatants, will have to fall in the sweet spot of offering actionable intelligence, without bogging the recipient down in details or leaving them uninformed.

One thing thats remained consistent is folks will do one of three things with overwhelming information, Brown said. They will wait for perfect information. Theyll just wait wait, wait, theyll never have perfect information and adversaries [will have] done 10 other things, by the way. Or theyll be overwhelmed and disregard the information.

The third path users will take, Brown said, is the very task commanders want them to follow: find golden needles in eight stacks of information to help them make a decision in a timely manner.

Getting there, however, where information is empowering instead of paralyzing or disheartening, is the work of training. Adapting for the future means practicing in the future environment, and that means getting new practitioners familiar with the kinds of information they can expect on the battlefield.

Our adversaries are going to bring a lot of dilemmas our way and so our ability to comprehend those challenges and then hopefully not just react but proactively do something to prevent those actions, is absolutely critical, said Brig. Gen. David Kumashiro, the director of Joint Force Integration for the Air Force.

When a battle has thousands of kill chains, and analysis that stretches over hundreds of hours, humans have a difficult time comprehending what is happening. In the future, it will be the job of artificial intelligence to filter these threats. Meanwhile, it will be the role of the human in the loop to take that filtered information and respond as best it can to the threats arrayed against them.

What does it mean to articulate mission command in that environment, the understanding, the intent, and the trust? said Kumashiro, referring to the fast pace of AI filtering. When the highly contested environment disrupts those connections, when we are disconnected from the hive, those authorities need to be understood so that our war fighters at the farthest reaches of the tactical edge can still perform what they need to do.

Planning not just for how these AI tools work in ideal conditions, but how they will hold up under the degradation of a modern battlefield, is essential for making technology an aide, and not a hindrance, to the forces of the future.

If the data goes away, and you still got the mission, youve got to attend to it, said Brown. Thats a huge factor as well for practice. If youre relying only on the data, youll fail miserably in degraded mode.

More:

One key to artificial intelligence on the battlefield: trust - C4ISRNet

The past decade has seen the rise of remarkably human personal assistants, increasing automation in transportation and industrial environments, and even the alleged passing of Alan Turings famous robot consciousness test. Such innovations have taken artificial intelligence out labs and into our hands.

A.I. programs have become painters, drivers, doctors assistants, and even friends. But with these new benefits have also come increasing dangers. This ending decade saw the first, and likely not the last, death caused by a self-driving car.

This is #20 on Inverses 20 predictions for the 2020s.

And as we head toward another decade of machine learning and robotics research, questions surrounding the moral programming of A.I. and the limits of their autonomy will no longer be just thought-experiments but time-sensitive problem.

One such area to keep on eye on going forward into a new decade will be partially defined by this question: what kind of legal status will A.I. be granted as their capabilities and intelligence continues to scale closer to that of humans? This is a conversation the archipelago nation Malta started in 2018 when its leaders proposed that it should prepare to grant or deny citizenship to A.I.s just as they would humans.

The logic behind this being that A.I.s of the future could have just as much agency and potential to cause disruption as any other non-robotic being. Francois Piccione, policy advisor for the Maltese government, told Inverse in 2019 that not taking such measures would be irresponsible.

Artificial Intelligence is being seen in many quarters as the most transformative technology since the invention of electricity, said Piccione. To realize that such a revolution is taking place and not do ones best to prepare for it would be irresponsible.

While the 2020s might not see fully fledged citizenship for A.I.s, Inverse predicts that there will be increasing legal scrutiny in coming years over who is legally responsible over the actions of A.I., whether it be their owners or the companies designing them. Instead of citizenship or visas for A.I., this could lead to further restrictions on the humans who travel with them and the ways in which A.I. can be used in different settings.

Another critical point of increasing scrutiny in the coming years will be how to ensure A.I. programmers continue to think critically about the algorithms they design.

This past decade saw racism and death as the result of poorly designed algorithms and even poorer introspection. Inverse predicts that as A.I. continues to scale labs will increasingly call upon outside experts, such as ethicists and moral psychologists, to make sure these human-like machines are not doomed to repeat our same, dehumanizing, mistakes.

As 2019 draws to a close, Inverse is looking to the future. These are our 20 predictions for science and technology for the 2020s. Some are terrifying, some are fascinating, and others we can barely wait for. This has been #20. Read a related story here.

More here:

In the 2020s, human-level A.I. will arrive, and finally ace the Turing test - Inverse

tech2 News StaffDec 26, 2019 17:21:10 IST

Samsung has been teasing Neon for quite a while on social media. It appears to be an artificial intelligence (AI) project by its research arm and the company will be announcing more details about it during CES 2020 in January.

Samsung Neon AI project. Image: Neon

Neon hasnt really revealed any details. Its being developed under Samsung Technology & Advanced Research Labs (STAR Labs). STAR Labs could be a reference to the Scientific and Technological Advanced Research Laboratories (STAR Labs) from DC Comics, but we cant confirm that. Samsungs research division is led by Pranav Mistry who earlier worked on the Samsung Galaxy Gear and is now the President and CEO of STAR Labs.

The company has set up a website with a landing page that doesnt really mention any details. It only has a message saying, Have you ever met an Artificial? It has been continuously posting images on Twitter and Instagram, including a couple of videos. These images contain the same message in different languages as well, indicating that the AI has multilingual functionality. Mistry has also been teasing Neon on his own Twitter account.

This wont be Samsungs first venture into AI since it already has the Bixby digital assistant. However, it never really took off. CES 2020 begins on 7 January and well get to know more about Neon during the expo.

Find latest and upcoming tech gadgets online on Tech2 Gadgets. Get technology news, gadgets reviews & ratings. Popular gadgets including laptop, tablet and mobile specifications, features, prices, comparison.

See the original post here:

Samsung to announce its Neon artificial intelligence project at CES 2020 - Firstpost

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Artificial Intelligence in Transportation Market 2020: New Innovative Solutions to Boost Global Growth with New Technology, Business Strategies,...