Deck and demo from our 1st public event: TrustedOut+Digimind.

It was this Thursday morning and it was great. It was our first public presentation and it was great to partner with Digimind to show why TrustedOut can make Intelligence smarter and trustworthy. Merci Aurelien and Valentin.

The deck. TrustedOut.com/Digimind

Deck is in english. If you have question, let us know with the form below.

The demo. Step by step.

The scenario

ACME is a sport car maker launching a new model extensively using Artificial Intelligence (AI). ACME has 2 main countries, US and France and wonder what market to test first.

Step 1. Corpus Creation for country comparison.

New corpus, the CMO (or Marketing Manager) defines 3 conditions to be necessary.

a. Where are the publications? We said France and the United States
b. What should these publications be about? ACME wants to grab how AI is perceived from publications covering Politics, for regulations, Law, for any legal aspects, Tech, to gauge technology used and perceptions and, of course, Transportation, for anything car related.
c. Want to be safe from any toxic content? Of course, no fake new and no junk science

TrustedOut classification knows how gauge the expertise level of a source and how sensitive to the news the taxonomy should be.

At this stage, we want generalist publications by setting the expertise level to “Covered”

Here is the corresponding query for our Corpus, which we are going to name “ACME AI in new model”.

Once ready, “Save” will show us how many media and sources our Corpus will include…

… and the Taxonomy of your Corpus.

Let’s now connect your Corpus to Digimind to get Social Intelligence from your Corpus. Process is simple, click on “Get” and, instead of “Downloading” a csv or json file with all media and sources, which will not be up dated at all time, click on Connect and pick Digimind.

Your “ACME AI in new model” Corpus is now live and accessible for any projects related to this corpus definition. TrustedOut will continue to update it, all the time, with relevant media and sources.

Digimind collects content from those media sources, so no need to also connect “article abstracts” with Digimind.

Step 2. Comparing countries on AI.

As the Corpus is immediately available and up to date in Digimind, we can read the following top concepts in both countries about AI.

ACME is very sensitive to ethic in AI, so consequently pick France as the first country to test its new model to handle this ethic topic super carefully.

Step 3. Best media profiles for ad campaigns.

ACME’s CMO wants to check if Pure Player Media (media only available online) is a good target. After all, Pure Players should be more reactive and not having to sync print, for example, that can be daily, weekly or monthly, with immediate online publishing.

Let’s go back to TrustedOut and change the Corpus as follow:

a. Where are the publications? We now want to limit to France.
b. Select Pure Players? We want media where “out of digital” is set to None to only get those not publishing on any other support.

“Save”. And now we get these amounts

Step 4. The perfect mix ethic and Business for a 1st ad campaign.

While France is more “Ethic” on AI, Pure Players are more Business Oriented vs all. ACME CMO is seeing the growth from 37% (all media) to 45% (Pure Players) in business for this selection of media as the perfect vehicle to test an ethic message onto business oriented people.

Step 5. Talk to the talk in AI.

Now, ACME wants to launch its first Press Release and wants to address first the geek, very technical community.

Let’s go back to TrustedOut and make the following changes:

a. What should these publications be about? We now want only Tech and Transportation publications
b. How expert? Dedicated.

… and, of course, more specialized pubs means less as a total:

Step 6. Key concepts for an optimal PR campaign.

Digimind gives us the key concepts to write our Press Release: European Union/Commission and Neuronal Networks.

With the Corpus we have what publications to target, with those key concepts we have how to write a Press Release that will interest those targets.

Bottom line:
TrustedOut+Digimind = Market selection, Optimal ad budgets and Perfect PR.

Questions? Shoot!

 

Important does not mean interesting. Quite the opposite.

Inversely proportionated.

The more Important a news topic is for daily life, the less interesting it is to follow.

Weather, Crime and traffic are top important for daily life but definitely not topics to follow.

Gov and Politics #1 in not important for daily life and a third of interest to follow vs Restaurants, Clubs and Bars.

This is to be related to:

The decline of local newspapers impact on democracy.

and this, to save a declining situation:

“Local leads to trust”

taken seriously by Google, Facebook, Knight Foundation, Automatic…

Saving journalism. [updated 2/19/19]

Questions? Shoot!

 

 

 

Brands buy Media Brands.

Reaching out to customers. Potential and existing.

There was advertising.
There was sponsoring.
There also was Commercial Brands creating their own media brand, such as (sources: Axios):

Now, Brands buy Media Brands

Robinhood, a trading app (raised $110M in 2017), instead of creating its own brand like seen above, is buying one: MarketSnacks , a newsletter and podcast media brand focused on financial trading. An interesting evolution for the media industry. Imagine, Nissan buying Car and Driver? Yes, I hear you. Jeff Bezos owns the Washington Post, but it’s not Amazon and WaPo is not a straight coverage for Amazon either.

All about transparency.

As written, trust in Media will come back with Privacy and Transparency. As long as you are aware of who is behind a Media, (or political orientation, or depth of expertise…) the content will be educational and useful as long as you accept the profile of the media.

Top 2019 predictions: Privacy and Transparency

04.11.19.900.Paris

If you are in Paris on April 11th, 9-11am, come and see us! Registration here.

Questions? Shoot!

 

Facebook’s news tab is a great idea IF users can curate her/his sources.

Screenshot from Facebook

The new News tab idea…

If you have an hour, this video/conversation is definitely worth it. Matthias Döpfner, Axel Springer’s CEO, was blunt and asked the right questions, from a journalist, online and print publisher, EU guy.

… if the user can define her/his trust criteria.

My fav part is well explained in this Recode article and in particular, the News tab idea is great but, to me and unsurprisingly, only if the FB user can do its own curation of publishers meeting his/her trust values.

“And as Zuckerberg notes in his comments, he isn’t sure whether Facebook should be curating a mix of news for users or letting them pick most of what they want to see.

Trust is personal. No-one can tell you what you trust.

As we wrote:

While distrust is general, trust definition is personal.

This is the foundation of TrustedOut.

04.11.19.900.Paris

If you are in Paris on April 11th, 9-11am, come and see us! Registration here.

Questions? Shoot!

Online lie detector or Machine learning how to lie.

Online lie detector or Machine learning how to lie.

Interesting article in Wired “RESEARCHERS BUILT AN ‘ONLINE LIE DETECTOR.’ HONESTLY, THAT COULD BE A PROBLEM”

Yes, it’s a first attempt. Yes, it should be taken very cautiously.
But yes, it has merit.

Typing and writing.

The way you type and the words you use show a level of lie or truth, from your standpoint. While recording and analyzing the typing part sounds more like a lie detection test, the word used are, in fact, much more accurate.

TrustedOut uses a similar method.

As mentioned, TrustedOut uses extensively machine learning. In this previous post, we explained how machine learning is the basis of our classification. For taxonomy or how to spot how a media is perceived on the internet.

The How and What: Mixing attitude and expertise.

Now, imagine you mix an attitude, such as lying or being blunt, or positive, or sarcastic and a taxonomy classification, and you mix two or more classifications based on machine learning. And you get the how and what…

04.11.19.900.Paris

If you are in Paris on April 11th, 9-11am, come and see us! Registration here.

Questions? Shoot!

 

Distrust in Media driven by distrust in government.

According to VisionCritical: “trust [in Media] among the informed public in the U.S. plunged 23 points to 45, making it the lowest of the 28 countries surveyed. The collapse of trust is driven by a staggering lack of faith in government. This fell 14 points to 33 percent among the general population, and 30 points to 33 percent among the informed public. [Numbers are for the USA]”

63% can’t recognize journalism from rumors.

“The 2018 Trust Barometer found 63 percent of respondents don’t know how to tell good journalism from rumor, or whether a respected media organization had produced a piece of news. But the public doesn’t rely solely on news media organizations to stay informed. We also use search engines and social media. The irony is that these platforms—once hailed as the future of media—are hurting too. The rising distrust of traditional media comes at a time when social media giants such as Facebook are facing intense scrutiny about their role in spreading disinformation. The Huffington Post recently announced it would no longer rely on unpaid bloggers.

Journalism for the win!

It’s all about brand values.

We recently published in “Why customer trust is more vital to [media] brand survival than it’s ever been” :

Gaining trust: demonstrate [media] brand clarity of purpose and core values and be transparent with all policies and procedures.

“Board and staff members need to adhere to these ethical standards as, in effect, they are the brand and only they can elicit consumer trust,” he [Director of brand agency Hulsbosch, Jaid Hulsbosch] says.

To do this, a corporation and its brand needs to be determined to demonstrate brand clarity of purpose and core values and be transparent with all policies and procedures”

Profiling Media Brands to secure trust in analytics and brand safety.

Brand values for any business, including Media, are the foundation of trust for customers, readers. Understanding them is the solution to secure trust in analytics support for strategic decision making and totally secure advertiser’s brand within a campaign.

Questions? Shoot!

 

Time for journalists to acknowledge that they write from a set of values, not simply from a disinterested effort at truth?

As Columbia Journalism Review puts it, “one gets the sense that the pitch of anti-press sentiment is now the most fevered it’s been since the founding of the republic. In fact, presidents from George Washington on, including Thomas Jefferson… judged newspapers to be full of lies. “. Sounds familiar?

Credits: cjr.org

Readers responsibility to discern for themselves the difference between what can be trusted as factual and reporter’s judgment. 

“… the old days of ritually objective news reporting (he said/she said) are not gone but have been reduced in importance from the 1970s on, as mainstream outlets have increasingly emphasized analysis in news coverage—not quite so much “who, what, when, where” as “why.” There has been a profound cultural shift in journalism during this period. The limitations of straitjacketed objectivity came to be understood and journalism began to embrace the necessity of interpretation… In the face of the severe economic problems afflicting daily newspapers, leading metro dailies have continued, whenever possible, to pursue aggressive, analytical journalism. This places great responsibility on readers to discern for themselves the difference between what can be trusted as factual and what represents the reporter’s judgment—a judgment that, however conscientious, goes beyond documented facts.”

“It may also be time for journalists to acknowledge that they write from a set of values, not simply from a disinterested effort at truth.”

“This will not be easy, since journalists have spent decades denying that their personal values have anything to do with their news reporting.”

Trust is personal. Personal is Trust.

“Tom Rosenstiel, the executive director of the American Press Institute, told her that for many people, “there’s ‘the media’ (bad) and there’s ‘my media’ (fairly good).” Likewise, he noted, people have little faith in Congress but think their own local representatives are okay.

Sounds familiar? Yep. We wrote about this…

developed in this post: While distrust is general, trust definition is personal.

Bottom line: Media should strengthen their brand values with the upmost  transparency to increase Reader’s trust.

Questions? Shoot!

TrustedOut AI-Operated Classification

Data Collection and Content Classification.

Our database of Media profiles has 2 distinct jobs. Collecting intangible data, like revenue, ownership, years online…) and Classifying content for our taxonomy and how sites are “spotted as” (like “fake news”, “junk science”…)

Data Collection is a multi-references, cross checking and evolution watch crawling exercise when…

Content Classification is all about Machine Learning.

And all about “bags of words”. For every classification job, we build datasets made of words onto which the frequency of occurence is used to train a classifier.

As mentioned above, we have 2 types of Classification: Taxonomy and “spotted as”.

Taxonomy Classification.

As in the graphic above, every articles is matched against our taxonomy datasets so we can classify each and every article. This gives us a clear picture of a feed, and thus, the whole media.

This, of course, makes a (big) lot of operations: 75,000 per article. Yes, 75 Billions ops per million of articles daily.

Taxonomy fun facts (as of today!)

Taxonomy DNA

Hereafter is the visualization of the New York Times, Tech section’s DNA.

Sensitiveness and depth customization. Tailor-made for the analyst.

Datasets used to classify articles can use a customized buffer of time for those datasets and thus, manage how sensitive to daily news the taxonomy will be. In addition, cliffs can also be customized to select a depth of expertise, from “dedicated” to “covered” or even “all sounds”. Both combined, plus the “always up-to-date” factor, makes our taxonomy perfectly tailor-made for the job the analyst wants to run. Reason why we use “Corpus Intelligence” as our tagline.

Enterprise mapping.

We can also link our taxonomy to our Enterprise Client’s taxonomy, so Corpus Intelligence can use the client’s business environment, (We’ll cover this in a dedicated post later. If you can’t wait, ask using the form below)

“Spotted as” Classification.

Point of being AI-Operated is we do not have any emotion or opinion. Everything is made for our client to define what they truly need and trust for content.

TrustedOut does not score nor judge anything or anyone. In addition, notions like “fake news” is not as cristal clear as people may think. The “Media, Trust and Democracy report” says it perfectly in its introduction: “Concern about “fake news” is high, but we can’t agree on what that means.”

A vivid picture on how a Media is “spotted as”.

As, TrustedOut profiles Media and their brand values, we have developed a sophisticated way to classify how a Media is “spotted”. In other words, we do not score or judge, we tell you if a Media is “spotted as” a fake news publication, for example.

In addition, the way a Media is “spotted as” varies over time. Some are getting worse, some are just revivals of previously shutdown ones, some are, of course, fixed and improved. This is why it’s mandatory to keep an always updated classification. And consequently, have your Corpus of documents always up-to-date.

Works with any terms. Bad or good.

“Fake news” is always the first coming to mind, then all toxic or suspicious terms like “Extreme bias”, “Junk Science”… but it can also works perfectly for neutral or positive terms, like “Visionary”, “Optimistic”… This opens doors to Enterprise-wide personalization.

Questions? Shoot!

 

 

 

 

 

Keywords (Data) Voids: Misinformations via Google and Bing.

Credit: pexels.com

In decreasing order of Trust in News: Media I use, Media Overall, Search engines and Social Media.

From the must-read Reuters Institute and Oxford University Digital News Report, you can read the following for the US:

Misinformation using keyword voids via Google and Bing. The “evil unicorn problem”.

Keywords Voids, also known as Data Voids, might not be the only reason for this low level of Trust but it’s important to know how this works.

Desperately seeking quality content.

Every one of us searches Google 3-4 times every day.

But every searches are not equal. Lots of searches are too vague and thus will return lots of noise and (yes!) 15% of all searches on a yearly basis were never searched before.

Bottom line, in the too vague a query, you will add more words and the combinaison may not have much quality content. Same for searches never searched before.

This means there are many search terms for which the available relevant data is limited, non-existent, or deeply problematic. We call these “data voids” or “keywords voids”

The malicious exploit: Wide open door to misinformation and manipulation.

Typology of Keywords/Data Voids (source (highly recommended read): Data Voids: Where Missing Data Can Easily Be Exploited)

Active Keywords/Data Voids on breaking news.

“Data voids that are actively weaponized by adversarial actors immediately following a breaking news event, usually involving names of locations or suspects in violent attacks (e.g., “Sutherland Springs” or “Parkland.”)”

Active Keywords/Data Voids on problematic terms.

“Data voids that are actively weaponized by adversarial actors around problematic search terms, usually with racial, gendered, or other discriminatory intent (e.g., “black on white crime” or “The Greatest Story Never Told” or “white genocide statistics.”)”

Passive Keywords/Data Voids on a particular group

“Data voids that passively reflect bias or prejudice in society but are not ac- tively being weaponized or exploited by a particular group (e.g., “CEO.”)”

A byproduct of cultural prejudice.

Not an easy task. “Data voids are a byproduct of cultural prejudice and a site of significant manipulation by individuals and organizations with nefarious intentions. Addressing data voids cannot be achieved by removing problematic content, not only because removal might go against the goals of search engines but also because doing so would not be effective. Without high-quality content to re- place removed content, new malicious content can easily surface”

Responding to data voids requires making certain that high-quality content…

“Unlike other forms of content moderation, responding to data voids requires making certain that high-quality content is available in spaces where people may seek to exploit or manipulate users into engaging with malignant information.”

… but only you can decide what is a “quality content”.

This is why we are building TrustedOut. Am AI-Operated database of media profiles. Unbiased. Up-to-date. Universal.

Questions? Shoot!

 

“Local leads to trust”

“The shorter the distance between our neighbors and our news, the stronger our community.”

This article from NiemanLab about an event organized by the Knight Foundation is a perfect follow up to our previous post:

The decline of local newspapers impact on democracy.

Saving the Soldat Local News

… and, as a reminder the Knight Foundation did commit an addition $300M to support journalism and local news

Saving journalism. [updated 2/19/19]

The American Journalism Project

Things are definitely moving with the launch of the American Journalism Project, a venture philanthropy effort co-led by Chalkbeat founder Elizabeth Green and Texas Tribune founder John Thornton, with $42 million in its first fund.

Attention, money, efforts… we’ll keep you updated on this. Stay tuned.

Questions? Shoot!