Author: Marie-Michele Caron

Too often self limiting my comments to my job description, now wanting to speak up on trends, global movements and what I believe matters. I am originally from Quebec City, Canada and now live in the Bay Area. Growing up, speaking english was a differentiator and pursuing opportunities outside of our bubble was much harder. Moved to San Francisco a few years ago and with it I found the power of voicing my opinion and hope I can inspire others to find their voice!

Protection in Perpetuity for the Online Giants?

Published on by Marie-Michele Caron1 Comment

Earlier this year, social media companies, such as Facebook and Twitter, started putting up warnings on comments made on their platforms. The warnings were an initial effort to slow down the spread of misinformation. As 2020 progressed, they started taking down entire articles and video content deemed misleading.

One example is the cascade of measures that Twitter announced around the protection of the integrity of the US 2020 election process. Twitter said that “between Oct. 27 and Nov. 11, it had labeled about 300,000 tweets as containing ‘disputed and potentially misleading’ information about the election.” That represented 0.2% of all tweets related to the U.S. election in that time frame. 

Facebook also updated its terms of service and announced that it would now authorize the removal or restriction of content from its social media platforms, if that content may have regulatory or legal impacts on the company. “Effective October 1, 2020, section 3.2 of our Terms and Service will be updated to include: We also can remove or restrict access to your content, services or information if we determine that doing so is reasonably necessary to avoid or mitigate adverse legal or regulatory impacts to Facebook”

Even YouTube also removed certain videos of the World Health Organization covering COVID-19. YouTube justified this action by claiming that the removed videos were misleading and that the WHO was contradicting itself as more information was learned about the virus through 2020.

By interfering with the content that is published on their platform and censoring certain stories, these companies are no longer acting solely as distribution platforms but effectively as editorial authorities on a variety of topics of matter.

AI powered feeds already imply editorial decisions

We already agreed that these companies “decide” which content we consume by accepting the ordering of our daily feeds based on an algorithmic redistribution amplification method as opposed to traditional real time feed distribution. AI powered data “ranking” is what made Facebook, Twitter and others’ experiences so great and addictive to its users and profitable to its shareholders. 

We’ve agreed to this arrangement assuming these companies would be neutral speech platforms and not attempt to influence public opinion by putting their thumb on the scale and unfairly benefitting one side or another. But now, we increasingly see them taking sides on a variety of topics.

A little bit of history

Over a decade ago, user generated content became a big trend. Companies no longer needed to rely on publishers since users were creating tons of relevant content. Platforms played a fundamental role in syndication and distribution of users’ content. The online internet companies positioned themselves as distribution channels with a mission to provide a platform for anyone to publish their content: pictures, videos, blogs, comments, etc.

Despite their continuously growing influence of what is distributed, read and consumed, the online internet companies’ responsibility remained minimal.

This was made possible because of Section 230

Section 230 of the Communications Decency Act was passed in 1996 and is a law that is designed to protect common carriers and web hosters of any legal claims that may come from hosting third party information. Section 230 states that “no provider or user of an interactive computer service shall be treated as the publisher or speaker of any information provided by another information content provider.” This law is intended to protect “interactive computer services” from being sued over what users post, effectively making it possible to run a social network, a website like Wikipedia, or have a comment section on a news website.

Simply said:

  • If you leave a comment on this blog, I am not responsible for your comment. 
  • Same applies for online medium companies. If they are hosting a blog they are not responsible for the comments. 

Without question, this law greatly aided the development of the Internet by enabling companies and websites the ability to leverage user-generated content.

Should these protected rights remain when user-generated content is pushed by advanced AI technology? 

Section 230 was passed in 1996. Back then, we had no conception of social distribution and AI based feeds that raise specific content targeted to users’ preferences and greatly increases a users engagement on those platforms. 

These companies have mastered algorithms and amplification methods, based on AI to promote or demote the content that will keep us clicking and staying on their site. Make no mistake, the data and signals they use to help promote specific content is the choice of those companies. They build their own algorithms, assemble which dataset will feed these algorithms and even the weight of the influence, i.e our click history, what is likely clicked on, our profile, our preferences, etc. 

For years, they have been “choosing” what content we, our family and our children are being served.

From Content Distribution to Content Editing platforms

The advanced AI techniques, coupled with the recent prescriptive interference and censorship of what is published on their platforms confirms that these online internet companies are no longer acting solely as distribution platforms but more so as an editorial authority.

Does the End Justify the Means?

With the social media companies’ change of tone, confirmed by the changes in their policies, they are signaling to the world that they are fully prepared to take a position on what is right and wrong for their platform. 

Understanding that they may be doing so in an attempt to reduce the spread of misinformation and encourage people to reconsider if they want to amplify certain posts and tweets, we need to make sure that they are not abusing their legacy privileges (Section 230) and dig deeper on the consequences of having distribution platforms manipulate the content it allows or disallows.

As Machiavelli famously said, “the end justifies the means.” 

In a world that is more and more digital, online communities of influencers are emerging as sources of truth. Their voices will likely only become louder. We need to be careful of the echo chambers of opinions, amplified by AI who are likely to tighten our positions. The future of media isn’t new companies but a billion unique voices. 

Who will monitor is becoming as important as what is created. Removing hate speech, vulgar content and reducing disinformation is noble, even necessary. But Beauty is in the Eye of the beholder. Culture, education, political beliefs naturally infer bias in opinions. 

The days of having those companies shielded under Section 230 are probably counted…

It took a pandemic to realize…

Published on by Marie-Michele Caron1 Comment

“Prediction is very difficult, especially if it’s about the future.” – Niels Bohr

Each time we open an app and start interacting with it, we’re bombarded with suggestions: articles to read, items to buy, people to connect with, etc… The ability to predict and recommend what will make us click and convert online is remarkable, consequently so is its influence on our perceptions.

In my last blog post, I touched on how AI is reshaping our world by democratizing and automating predictions.

With a global health pandemic on our hands, the tone of the media has amplified our fear factor. Coupling this with an even more acute machine powered capability to recommend readings, our perceptions are naturally biased. For a few weeks, I too was skeptical of what laid ahead.

I wanted to share my take on some movements that I trust will only be accelerated and anchored in without the emotional nuances related to this tragedy.

Crises are an important catalyst to profound changes. What was already in transition is often only accelerated by them.

Covid-19 is no different.

But I guess it took a pandemic to realize that:
  • Everyday at an office is unnecessary, perhaps even counter productive. But everyday on Zoom is also not sustainable. The physical workplace will continue to morph into a more hybrid mode.
  • Megacities are not the only option. Along with the workplace transformation, new energy efficient and autonomous transportation will make anywhere become somewhere.
  • Blindly believing media filtered experts is risky. Blindly trusting politicians can be even worse. As mainstream media continues to present biased datasets, online communities of influencers are emerging as voices of reason. Their voice will only become louder as communities become more trusted. We need to be careful of the echo chambers opinions, amplified by AI, who are likely to tighten our positions. The future of media isn’t new companies but a billion unique voices. 
  • Our education system is outdated and forced to adapt. From what is taught to how it is being taught and by whom. Creating a “microschool,” is a concept that emerged from the lock downs and that sits between two of the most polarizing points on the education spectrum: private school and homeschooling. In any case, the new learning model will need to be on par with the pace of innovation. The future generation of leaders depends on it.
  • Telemedicine needs to become the default. To better protect our healthcare workers but also to better constrain future pandemic.  Shutting down the economy to protect a population at risk is not a viable option. Investments in identifying and containing viruses should not be subverted by the investments made in finding its cure. Both need to be celebrated.
  • We live in a global system where decisions have a global impact. A virus that started in China shut down the entire world. International Organizations have been challenged by how they responded to the crisis but their presence will be necessary in supporting how we want to shape our global economy of the future. There won’t be a vaccine for a global energy crisis. 

One common denominator: Leadership Matters.

Great leaders who understand global movements and who are challenging status quo are emerging. Across diverse functions and communities, they are rising and striving to create certainty and cooperative goals for the greater good.

As Churchill said during the great crisis of World War II, there’s a way to reassure people that they are progressing, while still keeping them focused and aligned for the tough times ahead that remains.

So what’s next is uncertain and what we are facing is extraordinary. But I refuse to let negativity infest us with discouragements and get in the way of the greater changes that have started emerging.

You can’t control the future but you can control how you will inspire and lead through this transition. 

As always, thoughts and feedback welcome!

Marie

Why AI Matters – The Democratization of Predictions

Published on by Marie-Michele Caron3 Comments

Throughout the last few years, I had the opportunity to be at the forefront of witnessing how transformational the application of AI is to different businesses. The ability to automatically extract insights from data to make better, smarter and more informed decisions is no longer a “nice to have,” it is one of the most essential ways to successfully compete in today’s marketplace.

Already, multiple business functions have realized the benefits of using AI:

  • Increased employee proficiency in the digital workspaces
  • Enhanced self service capabilities on communities through machine based recommendations
  • And more recently with the e-commerce rush, AI has helped deliver higher conversion rates through personalized online consumer experiences.

We have numerous examples illustrating the ROI of applied AI, and there is ample literature about this topic. But in my opinion, the broader economic impact of AI adoption merits a deeper evaluation.

Simple question: What does AI reduce the cost of? AI profoundly reduces the cost of Prediction

I recently came across the book Prediction Machines: The Simple Economics of Artificial Intelligence  co-authored by professors Joshua Gans, Avi Goldfarb, Ajay Agrawal. They argue that AI serves a transformative, economic purpose: it significantly lowers the cost of prediction.

Because of this, I believe AI is fundamentally more important relative to other technology innovations.

A parallel technological innovation discussed in the book that helps equate the possible impact on the cost reduction of a useful outcome is semiconductors.  The book illustrates how semiconductors democratized arithmetic. Semiconductors drastically reduced the cost of calculating now elementary statistics such as averages and medians.

And then 3 things happened:

  1. The first obvious consequence: cheaper cost increased the availability and adoption of the technology.  Current industries that were already using arithmetics expanded their usage  into  other business functions such as inventory management, accounting, and cost forecasting. It was easier and cheaper to run a software program, and it greatly reduced human errors.
  2. The second consequence is a little less intuitive, but has a profound impact on innovation and ultimately on society. When the cost of arithmetic went down, it became compelling for other non traditional users to contemplate using it. As a result, arithmetic started being used to solve problems that hadn’t traditionally been framed as arithmetic problems. The book discussed how we used calculations to solve for the creation of photographic images by employing chemistry (film-based photography). Then, as arithmetic became cheaper, we began using arithmetic-based solutions in the design of cameras and image reproduction (digital cameras).
  3. The third thing that happened was that it changed the value of other things—the value of arithmetic’s complements went up and the value of its substitutes went down. Going back to the photography, the complements then were the software and hardware used in digital cameras. The value of these increased because we used more of them, while the value of substitutes, the components of film-based cameras, went down because we started using less and less of them.

The democratization of prediction through cheaper AI is likely to have similar impacts.

My experience working with diverse companies and partners has demonstrated already profound impacts both in the corporate world but also in the society at large.

  1. The first consequence: Increased adoption of AI across a myriad of use cases: I firmly believe that it is now an “AI take all economy”. Even the most traditional industries are forced to reinvent themselves as they are facing new competition (i.e. Marriott vs. AirBnB, Hertz vs. Uber). Companies cannot rely on a simple website or an app to check the digital box. Digital is a given. Companies now need to deliver the most relevant experience to each unique buyer – and the only way to do this at scale is through AI.

    Traditional retailers have been hit really hard in 2020. Local pet food retailers are now competing against e-commerce giants such as Cheewie. Cheewie delivers faster, cheaper and targeted product recommendations through AI.

    Every partner I am working with is expanding their capabilities to cater to this new environment; even within the most conservative industries such as banking, government and insurance.
  1. The second consequence to the democratization of AI – similarly to what we experienced with arithmetic – is how we are using predictions to solve problems that have not historically been thought of as prediction problems.

    The medical field, more specifically radiologists, is a great first example. Radiologists traditionally relied on their experience and judgement to interpret scans. Technology then focused on improving the quality of the image for better decisions. Reducing the risk of mistakes and facilitating decision making are prediction problems. Using AI methods, more specifically extracting insights from data through machine learning, doctors can now automatically recognize complex patterns in imaging data and provide quantitative, rather than qualitative, assessments of radiographic.

    Another example is around programming. Traditionally, programming was built using logic in a controlled environment: “If this then that”.  AI has allowed programs to use prediction to respond more effectively to uncontrolled environments. Solving problems such as autonomous driving is well documented. Traditional programs would have tried to code all options manually:  If a human crosses the street then stop. If the light is yellow then slowdown. But no matter how many lines of code you build you can never fully capture the whole picture.

    We never thought of autonomous driving as a prediction problem but it is the only way to solve it. The AI needs to predict the answer to the question: What would a good human driver do? Then ingest the data and learn from it.

In every scenario, the AI makes a lot of mistakes at first. But it learns from its mistakes and updates its model every time. Its predictions start getting better and better until it becomes so good at predicting what a human would do that we don’t need the human to do it anymore. The AI can perform the action itself. 

We could not do this until the cost of predictions was significantly low

  1. Finally, as the cost of prediction will continue to drop, just like demonstrated with arithmetic, there will be complementary products that will see their value go up and substitute products that will go down. The main complement to machine based prediction is human based one. 

    A few months ago, GPT-3 an autoregressive language model that uses deep learning to produce human-like text, the third-generation language prediction model in the GPT-n series created by OpenAI has already demonstrated that GPT-3 can take normal speech, and automatically turn it into ‘lawyer speak’. It can also take written text, and turn it into fully functioning code, in real-time. It can even write poetry! GPT-3 gives but a glimpse into the power we’re soon to unleash.

There are a lot of ethical aspects around this element that fuels a lot of passionate debates. 

  • Is my job safe or will a robot replace it?
  • Innovation is happening so fast, what will we do as a society to support the ones that have obsolete skills and can’t reinvent themselves?
  • Is our education system built in such a way that the next generation will be properly trained to strive in this new environment?

All very valid questions. Thankfully, organisations like @OpenAI (who built the GPT-3 model) are pathing the way to safe & sustainable AI. Employing the world’s greatest minds to ensure that AI remains a force for good.

Finally, by understanding the impacts of an increased adoption of AI, I am hoping it will make it easier for business leaders and public servants to figure out the most valuable ways to apply AI for the benefit of all stakeholders.

Got a comment, a question – I’d love to hear from you!

Marie

If it does not challenge you, it won’t change you

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What an incredible time to start speaking up! Never before have we been so empowered to speak up our minds. In today’s web-centric world, an opinion, a viewpoint, an interesting remark can echo beyond the conference room and become the basis for a quote, a Facebook post, a tweet or even a new article.

With time, I have come to believe over and over again that what is most important must be spoken, made verbal and shared, even at the risk of having it bruised or misunderstood.

I recently relocated in San Francisco – the epicentre of disruption – where traditional business model, ways of living, preconceived opinion are constantly challenged.

Based on my experience, I want to communicate with the world:

  • What I witness that amazes me, inspires me and disrupts me.
  • What I stand for and believe in.
  • What can be done to become better citizen, business person, politicians and potentially better family members.

I am willing to take the heat for asserting my ideas and opinions and get the conversation started.

“The most courageous act is still to think for yourself. Aloud.” – Coco Chanel

*****

Quelle époque incroyable pour se prononcer! Jamais auparavant avons nous été aussi équipés pour partager nos points de vue. Dans le monde d’aujourd’hui grâce à toutes les plateformes web, une opinion, un point de vue, une remarque pertinente peuvent avoir des impacts bien au-delà de la salle de conférence et de devenir la base d’une citation, d’un post Facebook, d’un tweet ou même d’un tout nouvel article.

Avec le temps, je suis venue à croire que ce qui est le plus important doit être dit et partagé, même au risque de le voir méjugé ou mal compris.

Récemment, je suis déménagé à San Francisco – l’épicentre du changement- où les modèles d’affaires traditionnels, les modes de vie, les opinions préconçues sont constamment remis en cause et les status quo reniés.

Sur la base de mon expérience, je veux communiquer avec le monde:

  • Ce dont je suis témoin, ce qui me surprend, m’inspire et me challenge.
  • Ce en quoi je crois et juge qu’il y aura un impact
  • Ce que l’on peut faire pour devenir de meilleurs citoyens, hommes/femmes d’affaires, politiciens et potentiellement de meilleurs parents.

L’idée est de partager mes idées et mes opinions et ultimement de commencer la conversation.

“L’acte le plus courageux est encore à penser par vous-même. À haute voix.” -Coco Chanel