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#436546 How AI Helped Predict the Coronavirus ...

Coronavirus has been all over the news for the last couple weeks. A dedicated hospital sprang up in just eight days, the stock market took a hit, Chinese New Year celebrations were spoiled, and travel restrictions are in effect.

But let’s rewind a bit; some crucial events took place before we got to this point.

A little under two weeks before the World Health Organization (WHO) alerted the public of the coronavirus outbreak, a Canadian artificial intelligence company was already sounding the alarm. BlueDot uses AI-powered algorithms to analyze information from a multitude of sources to identify disease outbreaks and forecast how they may spread. On December 31st 2019, the company sent out a warning to its customers to avoid Wuhan, where the virus originated. The WHO didn’t send out a similar public notice until January 9th, 2020.

The story of BlueDot’s early warning is the latest example of how AI can improve our identification of and response to new virus outbreaks.

Predictions Are Bad News
Global pandemic or relatively minor scare? The jury is still out on the coronavirus. However, the math points to signs that the worst is yet to come.

Scientists are still working to determine how infectious the virus is. Initial analysis suggests it may be somewhere between influenza and polio on the virus reproduction number scale, which indicates how many new cases one case leads to.

UK and US-based researchers have published a preliminary paper estimating that the confirmed infected people in Wuhan only represent five percent of those who are actually infected. If the models are correct, 190,000 people in Wuhan will be infected by now, major Chinese cities are on the cusp of large-scale outbreaks, and the virus will continue to spread to other countries.

Finding the Start
The spread of a given virus is partly linked to how long it remains undetected. Identifying a new virus is the first step towards mobilizing a response and, in time, creating a vaccine. Warning at-risk populations as quickly as possible also helps with limiting the spread.

These are among the reasons why BlueDot’s achievement is important in and of itself. Furthermore, it illustrates how AIs can sift through vast troves of data to identify ongoing virus outbreaks.

BlueDot uses natural language processing and machine learning to scour a variety of information sources, including chomping through 100,000 news reports in 65 languages a day. Data is compared with flight records to help predict virus outbreak patterns. Once the automated data sifting is completed, epidemiologists check that the findings make sense from a scientific standpoint, and reports are sent to BlueDot’s customers, which include governments, businesses, and public health organizations.

AI for Virus Detection and Prevention
Other companies, such as Metabiota, are also using data-driven approaches to track the spread of the likes of the coronavirus.

Researchers have trained neural networks to predict the spread of infectious diseases in real time. Others are using AI algorithms to identify how preventive measures can have the greatest effect. AI is also being used to create new drugs, which we may well see repeated for the coronavirus.

If the work of scientists Barbara Han and David Redding comes to fruition, AI and machine learning may even help us predict where virus outbreaks are likely to strike—before they do.

The Uncertainty Factor
One of AI’s core strengths when working on identifying and limiting the effects of virus outbreaks is its incredibly insistent nature. AIs never tire, can sift through enormous amounts of data, and identify possible correlations and causations that humans can’t.

However, there are limits to AI’s ability to both identify virus outbreaks and predict how they will spread. Perhaps the best-known example comes from the neighboring field of big data analytics. At its launch, Google Flu Trends was heralded as a great leap forward in relation to identifying and estimating the spread of the flu—until it underestimated the 2013 flu season by a whopping 140 percent and was quietly put to rest.

Poor data quality was identified as one of the main reasons Google Flu Trends failed. Unreliable or faulty data can wreak havoc on the prediction power of AIs.

In our increasingly interconnected world, tracking the movements of potentially infected individuals (by car, trains, buses, or planes) is just one vector surrounded by a lot of uncertainty.

The fact that BlueDot was able to correctly identify the coronavirus, in part due to its AI technology, illustrates that smart computer systems can be incredibly useful in helping us navigate these uncertainties.

Importantly, though, this isn’t the same as AI being at a point where it unerringly does so on its own—which is why BlueDot employs human experts to validate the AI’s findings.

Image Credit: Coronavirus molecular illustration, Gianluca Tomasello/Wikimedia Commons Continue reading

Posted in Human Robots

#436470 Retail Robots Are on the Rise—at Every ...

The robots are coming! The robots are coming! On our sidewalks, in our skies, in our every store… Over the next decade, robots will enter the mainstream of retail.

As countless robots work behind the scenes to stock shelves, serve customers, and deliver products to our doorstep, the speed of retail will accelerate.

These changes are already underway. In this blog, we’ll elaborate on how robots are entering the retail ecosystem.

Let’s dive in.

Robot Delivery
On August 3rd, 2016, Domino’s Pizza introduced the Domino’s Robotic Unit, or “DRU” for short. The first home delivery pizza robot, the DRU looks like a cross between R2-D2 and an oversized microwave.

LIDAR and GPS sensors help it navigate, while temperature sensors keep hot food hot and cold food cold. Already, it’s been rolled out in ten countries, including New Zealand, France, and Germany, but its August 2016 debut was critical—as it was the first time we’d seen robotic home delivery.

And it won’t be the last.

A dozen or so different delivery bots are fast entering the market. Starship Technologies, for instance, a startup created by Skype founders Janus Friis and Ahti Heinla, has a general-purpose home delivery robot. Right now, the system is an array of cameras and GPS sensors, but upcoming models will include microphones, speakers, and even the ability—via AI-driven natural language processing—to communicate with customers. Since 2016, Starship has already carried out 50,000 deliveries in over 100 cities across 20 countries.

Along similar lines, Nuro—co-founded by Jiajun Zhu, one of the engineers who helped develop Google’s self-driving car—has a miniature self-driving car of its own. Half the size of a sedan, the Nuro looks like a toaster on wheels, except with a mission. This toaster has been designed to carry cargo—about 12 bags of groceries (version 2.0 will carry 20)—which it’s been doing for select Kroger stores since 2018. Domino’s also partnered with Nuro in 2019.

As these delivery bots take to our streets, others are streaking across the sky.

Back in 2016, Amazon came first, announcing Prime Air—the e-commerce giant’s promise of drone delivery in 30 minutes or less. Almost immediately, companies ranging from 7-Eleven and Walmart to Google and Alibaba jumped on the bandwagon.

While critics remain doubtful, the head of the FAA’s drone integration department recently said that drone deliveries may be “a lot closer than […] the skeptics think. [Companies are] getting ready for full-blown operations. We’re processing their applications. I would like to move as quickly as I can.”

In-Store Robots
While delivery bots start to spare us trips to the store, those who prefer shopping the old-fashioned way—i.e., in person—also have plenty of human-robot interaction in store. In fact, these robotics solutions have been around for a while.

In 2010, SoftBank introduced Pepper, a humanoid robot capable of understanding human emotion. Pepper is cute: 4 feet tall, with a white plastic body, two black eyes, a dark slash of a mouth, and a base shaped like a mermaid’s tail. Across her chest is a touch screen to aid in communication. And there’s been a lot of communication. Pepper’s cuteness is intentional, as it matches its mission: help humans enjoy life as much as possible.

Over 12,000 Peppers have been sold. She serves ice cream in Japan, greets diners at a Pizza Hut in Singapore, and dances with customers at a Palo Alto electronics store. More importantly, Pepper’s got company.

Walmart uses shelf-stocking robots for inventory control. Best Buy uses a robo-cashier, allowing select locations to operate 24-7. And Lowe’s Home Improvement employs the LoweBot—a giant iPad on wheels—to help customers find the items they need while tracking inventory along the way.

Warehouse Bots
Yet the biggest benefit robots provide might be in-warehouse logistics.

In 2012, when Amazon dished out $775 million for Kiva Systems, few could predict that just 6 years later, 45,000 Kiva robots would be deployed at all of their fulfillment centers, helping process a whopping 306 items per second during the Christmas season.

And many other retailers are following suit.

Order jeans from the Gap, and soon they’ll be sorted, packed, and shipped with the help of a Kindred robot. Remember the old arcade game where you picked up teddy bears with a giant claw? That’s Kindred, only her claw picks up T-shirts, pants, and the like, placing them in designated drop-off zones that resemble tiny mailboxes (for further sorting or shipping).

The big deal here is democratization. Kindred’s robot is cheap and easy to deploy, allowing smaller companies to compete with giants like Amazon.

Final Thoughts
For retailers interested in staying in business, there doesn’t appear to be much choice in the way of robotics.

By 2024, the US minimum wage is projected to be $15 an hour (the House of Representatives has already passed the bill, but the wage hike is meant to unfold gradually between now and 2025), and many consider that number far too low.

Yet, as human labor costs continue to climb, robots won’t just be coming, they’ll be here, there, and everywhere. It’s going to become increasingly difficult for store owners to justify human workers who call in sick, show up late, and can easily get injured. Robots work 24-7. They never take a day off, never need a bathroom break, health insurance, or parental leave.

Going forward, this spells a growing challenge of technological unemployment (a blog topic I will cover in the coming month). But in retail, robotics usher in tremendous benefits for companies and customers alike.

And while professional re-tooling initiatives and the transition of human capital from retail logistics to a booming experience economy take hold, robotic retail interaction and last-mile delivery will fundamentally transform our relationship with commerce.

This blog comes from The Future is Faster Than You Think—my upcoming book, to be released Jan 28th, 2020. To get an early copy and access up to $800 worth of pre-launch giveaways, sign up here!

Join Me
(1) A360 Executive Mastermind: If you’re an exponentially and abundance-minded entrepreneur who would like coaching directly from me, consider joining my Abundance 360 Mastermind, a highly selective community of 360 CEOs and entrepreneurs who I coach for 3 days every January in Beverly Hills, Ca. Through A360, I provide my members with context and clarity about how converging exponential technologies will transform every industry. I’m committed to running A360 for the course of an ongoing 25-year journey as a “countdown to the Singularity.”

If you’d like to learn more and consider joining our 2020 membership, apply here.

(2) Abundance-Digital Online Community: I’ve also created a Digital/Online community of bold, abundance-minded entrepreneurs called Abundance-Digital. Abundance-Digital is Singularity University’s ‘onramp’ for exponential entrepreneurs — those who want to get involved and play at a higher level. Click here to learn more.

(Both A360 and Abundance-Digital are part of Singularity University — your participation opens you to a global community.)

Image Credit: Image by imjanuary from Pixabay Continue reading

Posted in Human Robots

#436426 Video Friday: This Robot Refuses to Fall ...

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We’ll also be posting a weekly calendar of upcoming robotics events for the next few months; here’s what we have so far (send us your events!):

Robotic Arena – January 25, 2020 – Wrocław, Poland
DARPA SubT Urban Circuit – February 18-27, 2020 – Olympia, Wash., USA
Let us know if you have suggestions for next week, and enjoy today’s videos.

In case you somehow missed the massive Skydio 2 review we posted earlier this week, the first batches of the drone are now shipping. Each drone gets a lot of attention before it goes out the door, and here’s a behind-the-scenes clip of the process.

[ Skydio ]

Sphero RVR is one of the 15 robots on our robot gift guide this year. Here’s a new video Sphero just released showing some of the things you can do with the robot.

[ RVR ]

NimbRo-OP2 has some impressive recovery skills from the obligatory research-motivated robot abuse.

[ NimbRo ]

Teams seeking to qualify for the Virtual Urban Circuit of the Subterranean Challenge can access practice worlds to test their approaches prior to submitting solutions for the competition. This video previews three of the practice environments.

[ DARPA SubT ]

Stretchable skin-like robots that can be rolled up and put in your pocket have been developed by a University of Bristol team using a new way of embedding artificial muscles and electrical adhesion into soft materials.

[ Bristol ]

Happy Holidays from ABB!

Helping New York celebrate the festive season, twelve ABB robots are interacting with visitors to Bloomingdale’s iconic holiday celebration at their 59th Street flagship store. ABB’s robots are the main attraction in three of Bloomingdale’s twelve-holiday window displays at Lexington and Third Avenue, as ABB demonstrates the potential for its robotics and automation technology to revolutionize visual merchandising and make the retail experience more dynamic and whimsical.

[ ABB ]

We introduce pelican eel–inspired dual-morphing architectures that embody quasi-sequential behaviors of origami unfolding and skin stretching in response to fluid pressure. In the proposed system, fluid paths were enclosed and guided by a set of entirely stretchable origami units that imitate the morphing principle of the pelican eel’s stretchable and foldable frames. This geometric and elastomeric design of fluid networks, in which fluid pressure acts in the direction that the whole body deploys first, resulted in a quasi-sequential dual-morphing response. To verify the effectiveness of our design rule, we built an artificial creature mimicking a pelican eel and reproduced biomimetic dual-morphing behavior.

And here’s a real pelican eel:

[ Science Robotics ]

Delft Dynamics’ updated anti-drone system involves a tether, mid-air net gun, and even a parachute.

[ Delft Dynamics ]

Teleoperation is a great way of helping robots with complex tasks, especially if you can do it through motion capture. But what if you’re teleoperating a non-anthropomorphic robot? Columbia’s ROAM Lab is working on it.

[ Paper ] via [ ROAM Lab ]

I don’t know how I missed this video last year because it’s got a steely robot hand squeezing a cute lil’ chick.

[ MotionLib ] via [ RobotStart ]

In this video we present results of a trajectory generation method for autonomous overtaking of unexpected obstacles in a dynamic urban environment. In these settings, blind spots can arise from perception limitations. For example when overtaking unexpected objects on the vehicle’s ego lane on a two-way street. In this case, a human driver would first make sure that the opposite lane is free and that there is enough room to successfully execute the maneuver, and then it would cut into the opposite lane in order to execute the maneuver successfully. We consider the practical problem of autonomous overtaking when the coverage of the perception system is impaired due to occlusion.

[ Paper ]

New weirdness from Toio!

[ Toio ]

Palo Alto City Library won a technology innovation award! Watch to see how Senior Librarian Dan Lou is using Misty to enhance their technology programs to inspire and educate customers.

[ Misty Robotics ]

We consider the problem of reorienting a rigid object with arbitrary known shape on a table using a two-finger pinch gripper. Reorienting problem is challenging because of its non-smoothness and high dimensionality. In this work, we focus on solving reorienting using pivoting, in which we allow the grasped object to rotate between fingers. Pivoting decouples the gripper rotation from the object motion, making it possible to reorient an object under strict robot workspace constraints.

[ CMU ]

How can a mobile robot be a good pedestrian without bumping into you on the sidewalk? It must be hard for a robot to navigate in crowded environments since the flow of traffic follows implied social rules. But researchers from MIT developed an algorithm that teaches mobile robots to maneuver in crowds of people, respecting their natural behaviour.

[ Roboy Research Reviews ]

What happens when humans and robots make art together? In this awe-inspiring talk, artist Sougwen Chung shows how she “taught” her artistic style to a machine — and shares the results of their collaboration after making an unexpected discovery: robots make mistakes, too. “Part of the beauty of human and machine systems is their inherent, shared fallibility,” she says.

[ TED ]

Last month at the Cooper Union in New York City, IEEE TechEthics hosted a public panel session on the facts and misperceptions of autonomous vehicles, part of the IEEE TechEthics Conversations Series. The speakers were: Jason Borenstein from Georgia Tech; Missy Cummings from Duke University; Jack Pokrzywa from SAE; and Heather M. Roff from Johns Hopkins Applied Physics Laboratory. The panel was moderated by Mark A. Vasquez, program manager for IEEE TechEthics.

[ IEEE TechEthics ]

Two videos this week from Lex Fridman’s AI podcast: Noam Chomsky, and Whitney Cummings.

[ AI Podcast ]

This week’s CMU RI Seminar comes from Jeff Clune at the University of Wyoming, on “Improving Robot and Deep Reinforcement Learning via Quality Diversity and Open-Ended Algorithms.”

Quality Diversity (QD) algorithms are those that seek to produce a diverse set of high-performing solutions to problems. I will describe them and a number of their positive attributes. I will then summarize our Nature paper on how they, when combined with Bayesian Optimization, produce a learning algorithm that enables robots, after being damaged, to adapt in 1-2 minutes in order to continue performing their mission, yielding state-of-the-art robot damage recovery. I will next describe our QD-based Go-Explore algorithm, which dramatically improves the ability of deep reinforcement learning algorithms to solve previously unsolvable problems wherein reward signals are sparse, meaning that intelligent exploration is required. Go-Explore solves Montezuma’s Revenge, considered by many to be a major AI research challenge. Finally, I will motivate research into open-ended algorithms, which seek to innovate endlessly, and introduce our POET algorithm, which generates its own training challenges while learning to solve them, automatically creating a curricula for robots to learn an expanding set of diverse skills. POET creates and solves challenges that are unsolvable with traditional deep reinforcement learning techniques.

[ CMU RI ] Continue reading

Posted in Human Robots

#436209 Video Friday: Robotic Endoscope Travels ...

Video Friday is your weekly selection of awesome robotics videos, collected by your Automaton bloggers. We’ll also be posting a weekly calendar of upcoming robotics events for the next few months; here's what we have so far (send us your events!):

DARPA SubT Urban Circuit – February 18-27, 2020 – Olympia, WA, USA
Let us know if you have suggestions for next week, and enjoy today's videos.

Kuka has just announced the results of its annual Innovation Award. From an initial batch of 30 applicants, five teams reached the finals (we were part of the judging committee). The five finalists worked for nearly a year on their applications, which they demonstrated this week at the Medica trade show in Düsseldorf, Germany. And the winner of the €20,000 prize is…Team RoboFORCE, led by the STORM Lab in the U.K., which developed a “robotic magnetic flexible endoscope for painless colorectal cancer screening, surveillance, and intervention.”

The system could improve colonoscopy procedures by reducing pain and discomfort as well as other risks such as bleeding and perforation, according to the STORM Lab researchers. It uses a magnetic field to control the endoscope, pulling rather than pushing it through the colon.

The other four finalists also presented some really interesting applications—you can see their videos below.

“Because we were so please with the high quality of the submissions, we will have next year’s finals again at the Medica fair, and the challenge will be named ‘Medical Robotics’,” says Rainer Bischoff, vice president for corporate research at Kuka. He adds that the selected teams will again use Kuka’s LBR Med robot arm, which is “already certified for integration into medical products and makes it particularly easy for startups to use a robot as the main component for a particular solution.”

Applications are now open for Kuka’s Innovation Award 2020. You can find more information on how to enter here. The deadline is 5 January 2020.

[ Kuka ]

Oh good, Aibo needs to be fed now.

You know what comes next, right?

[ Aibo ]

Your cat needs this robot.

It's about $200 on Kickstarter.

[ Kickstarter ]

Enjoy this tour of the Skydio offices courtesy Skydio 2, which runs into not even one single thing.

If any Skydio employees had important piles of papers on their desks, well, they don’t anymore.

[ Skydio ]

Artificial intelligence is everywhere nowadays, but what exactly does it mean? We asked a group MIT computer science grad students and post-docs how they personally define AI.

“When most people say AI, they actually mean machine learning, which is just pattern recognition.” Yup.

[ MIT ]

Using event-based cameras, this drone control system can track attitude at 1600 degrees per second (!).

[ UZH ]

Introduced at CES 2018, Walker is an intelligent humanoid service robot from UBTECH Robotics. Below are the latest features and technologies used during our latest round of development to make Walker even better.

[ Ubtech ]

Introducing the Alpha Prime by #VelodyneLidar, the most advanced lidar sensor on the market! Alpha Prime delivers an unrivaled combination of field-of-view, range, high-resolution, clarity and operational performance.

Performance looks good, but don’t expect it to be cheap.

[ Velodyne ]

Ghost Robotics’ Spirit 40 will start shipping to researchers in January of next year.

[ Ghost Robotics ]

Unitree is about to ship the first batch of their AlienGo quadrupeds as well:

[ Unitree ]

Mechanical engineering’s Sarah Bergbreiter discusses her work on micro robotics, how they draw inspiration from insects and animals, and how tiny robots can help humans in a variety of fields.

[ CMU ]

Learning contact-rich, robotic manipulation skills is a challenging problem due to the high-dimensionality of the state and action space as well as uncertainty from noisy sensors and inaccurate motor control. To combat these factors and achieve more robust manipulation, humans actively exploit contact constraints in the environment. By adopting a similar strategy, robots can also achieve more robust manipulation. In this paper, we enable a robot to autonomously modify its environment and thereby discover how to ease manipulation skill learning. Specifically, we provide the robot with fixtures that it can freely place within the environment. These fixtures provide hard constraints that limit the outcome of robot actions. Thereby, they funnel uncertainty from perception and motor control and scaffold manipulation skill learning.

[ Stanford ]

Since 2016, Verity's drones have completed more than 200,000 flights around the world. Completely autonomous, client-operated and designed for live events, Verity is making the magic real by turning drones into flying lights, characters, and props.

[ Verity ]

To monitor and stop the spread of wildfires, University of Michigan engineers developed UAVs that could find, map and report fires. One day UAVs like this could work with disaster response units, firefighters and other emergency teams to provide real-time accurate information to reduce damage and save lives. For their research, the University of Michigan graduate students won first place at a competition for using a swarm of UAVs to successfully map and report simulated wildfires.

[ University of Michigan ]

Here’s an important issue that I haven’t heard talked about all that much: How first responders should interact with self-driving cars.

“To put the car in manual mode, you must call Waymo.” Huh.

[ Waymo ]

Here’s what Gitai has been up to recently, from a Humanoids 2019 workshop talk.

[ Gitai ]

The latest CMU RI seminar comes from Girish Chowdhary at the University of Illinois at Urbana-Champaign on “Autonomous and Intelligent Robots in Unstructured Field Environments.”

What if a team of collaborative autonomous robots grew your food for you? In this talk, I will discuss some key advances in robotics, machine learning, and autonomy that will one day enable teams of small robots to grow food for you in your backyard in a fundamentally more sustainable way than modern mega-farms! Teams of small aerial and ground robots could be a potential solution to many of the serious problems that modern agriculture is facing. However, fully autonomous robots that operate without supervision for weeks, months, or entire growing season are not yet practical. I will discuss my group’s theoretical and practical work towards the underlying challenging problems in robotic systems, autonomy, sensing, and learning. I will begin with our lightweight, compact, and autonomous field robot TerraSentia and the recent successes of this type of undercanopy robots for high-throughput phenotyping with deep learning-based machine vision. I will also discuss how to make a team of autonomous robots learn to coordinate to weed large agricultural farms under partial observability. These direct applications will help me make the case for the type of reinforcement learning and adaptive control that are necessary to usher in the next generation of autonomous field robots that learn to solve complex problems in harsh, changing, and dynamic environments. I will then end with an overview of our new MURI, in which we are working towards developing AI and control that leverages neurodynamics inspired by the Octopus brain.

[ CMU RI ] Continue reading

Posted in Human Robots

#436167 Is it Time for Tech to Stop Moving Fast ...

On Monday, I attended the 2019 Fall Conference of Stanford’s Institute for Human Centered Artificial Intelligence (HAI). That same night I watched the Season 6 opener for the HBO TV show Silicon Valley. And the debates featured in both surrounded the responsibility of tech companies for the societal effects of the technologies they produce. The two events have jumbled together in my mind, perhaps because I was in a bit of a brain fog, thanks to the nasty combination of a head cold and the smoke that descended on Silicon Valley from the northern California wildfires. But perhaps that mixture turned out to be a good thing.

What is clear, in spite of the smoke, is that this issue is something a lot of people are talking about, inside and outside of Silicon Valley (witness the viral video of Rep. Alexandria Ocasio-Cortez (D-NY) grilling Facebook CEO Mark Zuckerberg).

So, to add to that conversation, here’s my HBO Silicon Valley/Stanford HAI conference mashup.

Silicon Valley’s fictional CEO Richard Hendriks, in the opening scene of the episode, tells Congress that Facebook, Google, and Amazon only care about exploiting personal data for profit. He states:

“These companies are kings, and they rule over kingdoms far larger than any nation in history.”

Meanwhile Marietje Schaake, former member of the European Parliament and a fellow at HAI, told the conference audience of 900:

“There is a lot of power in the hands of few actors—Facebook decides who is a news source, Microsoft will run the defense department’s cloud…. I believe we need a deeper debate about which tasks need to stay in the hands of the public.”

Eric Schmidt, former CEO and executive chairman of Google, agreed. He says:

“It is important that we debate now the ethics of what we are doing, and the impact of the technology that we are building.”

Stanford Associate Professor Ge Wang, also speaking at the HAI conference, pointed out:

“‘Doing no harm’ is a vital goal, and it is not easy. But it is different from a proactive goal, to ‘do good.’”

Had Silicon Valley’s Hendricks been there, he would have agreed. He said in the episode:

“Just because it’s successful, doesn’t mean it’s good. Hiroshima was a successful implementation.”

The speakers at the HAI conference discussed the implications of moving fast and breaking things, of putting untested and unregulated technology into the world now that we know that things like public trust and even democracy can be broken.

Google’s Schmidt told the HAI audience:

“I don’t think that everything that is possible should be put into the wild in society, we should answer the question, collectively, how much risk are we willing to take.

And Silicon Valley denizens real and fictional no longer think it’s OK to just say sorry afterwards. Says Schmidt:

“When you ask Facebook about various scandals, how can they still say ‘We are very sorry; we have a lot of learning to do.’ This kind of naiveté stands out of proportion to the power tech companies have. With great power should come great responsibility, or at least modesty.”

Schaake argued:

“We need more guarantees, institutions, and policies than stated good intentions. It’s about more than promises.”

Fictional CEO Hendricks thinks saying sorry is a cop-out as well. In the episode, a developer admits that his app collected user data in spite of Hendricks assuring Congress that his company doesn’t do that:

“You didn’t know at the time,” the developer says. “Don’t beat yourself up about it. But in the future, stop saying it. Or don’t; I don’t care. Maybe it will be like Google saying ‘Don’t be evil,’ or Facebook saying ‘I’m sorry, we’ll do better.’”

Hendricks doesn’t buy it:

“This stops now. I’m the boss, and this is over.”

(Well, he is fictional.)

How can government, the tech world, and the general public address this in a more comprehensive way? Out in the real world, the “what to do” discussion at Stanford HAI surrounded regulation—how much, what kind, and when.

Says the European Parliament’s Schaake:

“An often-heard argument is that government should refrain from regulating tech because [regulation] will stifle innovation. [That argument] implies that innovation is more important than democracy or the rule of law. Our problems don’t stem from over regulation, but under regulation of technologies.”

But when should that regulation happen. Stanford provost emeritus John Etchemendy, speaking from the audience at the HAI conference, said:

“I’ve been an advocate of not trying to regulate before you understand it. Like San Francisco banning of use of facial recognition is not a good example of regulation; there are uses of facial recognition that we should allow. We want regulations that are just right, that prevent the bad things and allow the good things. So we are going to get it wrong either way, if we regulate to soon or hold off, we will get some things wrong.”

Schaake would opt for regulating sooner rather than later. She says that she often hears the argument that it is too early to regulate artificial intelligence—as well as the argument that it is too late to regulate ad-based political advertising, or online privacy. Neither, to her, makes sense. She told the HAI attendees:

“We need more than guarantees than stated good intentions.”

U.S. Chief Technology Officer Michael Kratsios would go with later rather than sooner. (And, yes, the country has a CTO. President Barack Obama created the position in 2009; Kratsios is the fourth to hold the office and the first under President Donald Trump. He was confirmed in August.) Also speaking at the HAI conference, Kratsios argued:

“I don’t think we should be running to regulate anything. We are a leader [in technology] not because we had great regulations, but we have taken a free market approach. We have done great in driving innovation in technologies that are born free, like the Internet. Technologies born in captivity, like autonomous vehicles, lag behind.”

In the fictional world of HBO’s Silicon Valley, startup founder Hendricks has a solution—a technical one of course: the decentralized Internet. He tells Congress:

“The way we win is by creating a new, decentralized Internet, one where the behavior of companies like this will be impossible, forever. Where it is the users, not the kings, who have sovereign control over their data. I will help you build an Internet that is of the people, by the people, and for the people.”

(This is not a fictional concept, though it is a long way from wide use. Also called the decentralized Web, the concept takes the content on today’s Web and fragments it, and then replicates and scatters those fragments to hosts around the world, increasing privacy and reducing the ability of governments to restrict access.)

If neither regulation nor technology comes to make the world safe from the unforeseen effects of new technologies, there is one more hope, according to Schaake: the millennials and subsequent generations.

Tech companies can no longer pursue growth at all costs, not if they want to keep attracting the talent they need, says Schaake. She noted that, “the young generation looks at the environment, at homeless on the streets,” and they expect their companies to tackle those and other issues and make the world a better place. Continue reading

Posted in Human Robots