Unboxing Google’s 7 new principles on Artificial Intelligence

How many times have you heard that Artificial Intelligence (AI) is humanity’s biggest threat? Some people think that Google brought us a step closer to a dark future when Duplex was announced last month, a new capability of Google’s digital Assistant that enables it to make phone calls on your behalf to book appointments with small businesses. You can see it in action here:

The root of the controversy lied on the fact that the Assistant successfully pretended to be a real human, never disclosing its true identity to the other side of the call. Many tech experts wondered if this is an ethical practice or if it’s necessary to hide the digital nature of the voice.

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Google was also criticized last month by another sensitive topic: the company’s involvement in a Pentagon program that uses AI to interpret video imagery and could be used to improve the targeting of drone strikes. Thousands of employees signed a letter protesting the program and asking for change:

“We believe that Google should not be in the business of war. Therefore we ask that Project Maven be cancelled, and that Google draft, publicize and enforce a clear policy stating that neither Google nor its contractors will ever build warfare technology.”

A “clear policy” around AI is a bold ask because none of the big players have ever done it before, and for good reasons. It is such a new and powerful technology that it’s still unclear how many areas of our life will we dare to infuse with it, and it’s difficult to set rules around the unknown. Google Duplex is a good example of this, it’s a technological development that we would have considered “magical” 10 years ago, that today scares many people.

Regardless, Sundar Pichai not only complied with the request, but took it a step further by creating 7 principles that the company will promote and enforce as one of the industry drivers of AI. Here are some remarks on each of them:

1. Be socially beneficial

For years, we have dealt with comfortable boundaries, creating increasingly intelligent entities in very focused areas. AI is now getting the ability to switch between different domain areas in a transparent way for the user. For example, having an AI that knows your habits at home is very convenient, especially when your home appliances are connected to the same network. When that same AI also knows your habits outside home, like your favorite restaurants, your friends, your calendar, etc., its influence in your life can become scary. It’s precisely this convenience that is pushing us out of our comfort zone.

This principle is the most important one since it bows to “respect cultural, social, and legal norms”. It’s a broad principle, but it’s intended to ease that uncomfortable feeling by adapting AI to our times and letting it evolve at the same pace as our social conventions do.

2. Avoid creating or reinforcing unfair bias

AI can become racist if we allow it. A good example of this happened in March 2016, when Microsoft unveiled an AI with a Twitter interface and in less than a day people taught it the worst aspects of our humanity. AI learns by example, so ensuring that safeguards are in place to avoid this type of situations is critical. Our kids are going to grow in a world increasingly assisted by AI, so we need to educate the system before it’s exposed to internet trolls and other bad players.

3. Be built and tested for safety

This point goes hand in hand with the previous one. In fact, Microsoft’s response to the Tai fiasco was to take it down and admit an oversight on the type of scenarios that the AI was tested against. Safety should always be one of the first considerations when designing an AI.

4. Be accountable to people

The biggest criticism Google Duplex received was whether or not it was ethical to mimic a real human without letting other humans know. I’m glad that this principle just states that “technologies will be subject to appropriate human direction and control”, since it doesn’t discount the possibility of building human-like AIs in the future.

An AI that makes a phone call on our behalf must sound as human as possible, since it’s the best way of ensuring a smooth interaction with the person on the other side. Human-like AIs shall be designed with respect, patience and empathy in mind, but also with human monitoring and control capabilities.

5. Incorporate privacy design principles

When the convenience created by AI intersects with our personal feelings or private data, a new concern is revealed: our personal data can be used against us. Cambridge Analytica’s incident, where personal data was shared with unauthorized third parties, magnified the problem by jeopardizing user’s trust in technology.

Google didn’t use many words on this principle, probably because it’s the most difficult one to clarify without directly impacting their business model. However, it represents the biggest tech challenge of the decade, to find the balance between giving up your privacy and getting a reasonable benefit in return. Providing “appropriate transparency and control over the use of data” is the right mitigation, but it won’t make us less uncomfortable when an AI knows the most intimate details about our lives.

6. Uphold high standards of scientific excellence

An open approach to building the AI systems of tomorrow is the best way of keeping any company honest. Providing access to “educational materials, best practices, and research that enable more people to develop useful AI applications” is a great commitment because it can expose problems faster and help find solutions sooner.

7. Be made available for uses that accord with these principles

It’s not an accident that this last principle is the predecessor of a section that outlines the applications that Google promises not to pursue. Many people fear AI just because they imagine what could go wrong if a faulty and uncontrollable system had the capability to make judgement calls on human behavior.

Google promises not to build AIs that can cause physical harm, promote surveillance that “violates internationally accepted norms” or any type of law/human right violation.

These principles are an invaluable start and a commendable attempt to establish the rules that will drive us towards the future. But they are not enough, proper regulation should be there to protect consumers. We are on the verge of a long journey involving AI that will change us, and we need to push forward and ensure that the proper guidelines are in place. Self-regulation cannot be the only type of control we see on AI. We need to push the tech industry towards the highest standards, for our future’s sake.

You can read Google’s principles here.


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Image via University of Canterbury

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Amazon Go: A.I.’s grim face?

I have been waiting since college on RFID’s failed promise to deliver a walk-away checkout experience, and Amazon finally made it possible. After reading my co-blog writer’s experience in the Amazon Go store I had to check it out for myself and was excited for it. All my friend’s pictures were of long lines, but thankfully I am a morning person and there was no line when I got there. My goal was to pretend I had no idea what it was or how it worked. My experience overall was good, with the exception of the on-boarding process. I was greeted with a condescending “oh, you don’t have the app?” and was asked to stay aside. My T-Mobile reception was very poor so it took me a bit to get started. Once I downloaded the app and signed into my Amazon account everything was smooth. Mission accomplished! In this post, I’m not going to talk about the actual store (Ivan did a great job already) but about the implications of the first tangible and successful AI automated store.

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Exterior of the Amazon Go store

Automation has always been part of our history. Automation has helped us evolve into the society we have now. Such as, automating how we grow and crop food so we can have a good food supply, the industrial revolution to make things faster and cheaper, the assembly line to make them even faster and cheaper, and finally computers to automate processes and tasks. Now, AI is here and it will automate all of our productivity.

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I experienced the future of retail: Amazon Go

The craziest thing I’ve seen is someone who came in dressed in a Pikachu costume“, said an Amazon employee while she handed me a promotional bag with the Amazon Go logo on one side and the text ‘good food fast’ on the other.

I arrived at the new store in downtown Seattle around 7:20 pm and was surprised to see the line of people still reached the end of the block. It had been a cold day in Seattle but that didn’t discourage the hundreds of people who came to see the ‘magical’ store on day 0. I didn’t use the term ‘magical’ lightly here: the experience was truly unique and it felt too good to be true. Amazon Go is probably the store with more sensors on the planet right now, and it is intimidating:

The ceiling of the Amazon Go store

Each of those boxes on the ceiling are cameras connected to deep learning algorithms that analyze every move you make: which aisle you walk through, what items you grab to read and then return to the shelf, what items you put in your pockets or bag… everything to ensure you only get charged for what you take home. But also, everything to ensure your shopping pattern is studied and well understood. Maybe not today, but it’s the inevitable next step and the ultimate dream for any retail store: to know what their customers like and the type of advertisements that will work best on them.

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Are you rude to your virtual assistant?

2017 has been the year of the smart speaker. Amazon’s Echo Dot and Google’s Home Mini are currently selling for around $30, which makes them a popular Christmas gift. Using an Artificial Intelligence (AI) has never been cheaper and it’s finally reaching critical mass.

Companies are investing on AI more than ever: natural language recognition still has to improve a lot, but the current algorithms are already impressive. My favorite example: it’s now possible to ask “how long would it take me to get to Starbucks on 15th Ave?” and get an accurate response with the right assumptions. What a time to be alive!

All of this progress comes with side effects: having to learn how to talk to a machine. Often, people start talking without the wake-up keyword, and sometimes they forget to check if the device is actually listening, getting confused when there is no response to their inquiry. Talking to a machine is not easy and usually, very unsatisfactory.

Perhaps that dissatisfaction is what makes us be less aware about our manners when addressing an AI. What would you think if someone interrupted you mid-sentence with a sudden “STOP”? What if someone kept giving you orders relentlessly, never pausing to thank you? That’s how most of us talk to AI’s like Alexa or Siri, never saying “please” or “thank you”.

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Why we will never fall in love with our smartphone’s virtual assistant

After watching Her last night (the Golden Globe winner for the Best Screenplay category) I was captivated by its amazing performances and its delightfully depicted technology. What motivated me the most to watch the movie was this article from Wired: why Her will dominate UI design even more than Minority Report.

In the movie, technology is almost completely transparent for the user: most of the interactions between Theodore, the main character, and his “smartphone” happen through the earpiece and the virtual assistant, and he only touches the little screen when he wants to watch a picture. This is what his gadgets look like:

Visual user interfaces are almost nowhere to be seen, and that’s the message: human interactions are the future of personal computing.

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