Las Vegas bets on Elon Musk for tunnel transit system
By REGINA GARCIA CANO
Thursday, March 7
LAS VEGAS (AP) — Entrepreneur Elon Musk’s dream of an express tunnel transit system could finally become a reality in Las Vegas after major setbacks in other cities.
Las Vegas’ tourism agency announced Wednesday it is recommending that an enterprise backed by the divisive billionaire receive a contract to build and operate an underground tunnel system through which autonomous electric vehicles would whisk people around a mega convention center, and in the future, possibly the city’s famous casino-filled corridor.
If approved, the system of just over a mile (1.6 kilometer) long would debut by January 2021 at the Las Vegas Convention Center, which hosts more than 1 million people every year. The Musk-owned The Boring Company would build the project costing from $35 million to $55 million.
It’s different from his beleaguered efforts to build underground tunnel systems in other cities because Musk will be paid for it if the contract is approved. Projects in Los Angeles and Chicago have drawn opposition and skepticism from residents and officials about whether they will actually open.
Musk has faced recent blow back because of his behavior and tweeting habits. He has had dust-ups with stock market regulators and agreed last year to step down as chairman of the board of Tesla, his electric car company.
But Las Vegas tourism officials are ready to get on board with a Musk project.
“It’s really innovative. I think it will be an attraction in and of itself, frankly,” Steve Hill, president and CEO of the Las Vegas Convention and Visitors Authority, told The Associated Press.
Details of the project have not been finalized. But Hill said the system will probably have three or four stations, each situated at entrances to the convention center’s halls. People would be carried to the hall of their choice in electric vehicles moving through parallel tunnels, each running in one direction.
The fleet could include Tesla’s Model X and Model 3 and a vehicle with capacity for about 16 people. All vehicles would be fully autonomous, meaning they won’t have drivers.
Hill said the authority is looking at options that would allow 4,400 to 11,000 people to use the system per hour. That passenger volume would depend on the size of the stations and number of vehicles — estimated between 90 and 140 — moving through the tunnels.
The Las Vegas Convention Center, which attracts worldwide gatherings including the premier Consumer Electronics Show, is undergoing an expansion. When finished, convention attendees could log about two miles (3.2 kilometers) walking from one end to the other. The distance led officials to look for a transportation solution.
The service within the convention center is expected to be free for people attending events.
The convention center is operated by the authority, which is funded by a county room tax and is responsible for promoting the destination around the world. The tourism agency is governed by a board of directors.
The authority is expected to present to the board the recommendation to select Musk’s company March 12. If approved, Hill said the agency hopes to return to the board with a full design and proposed contract by June.
Musk in December unveiled a test tunnel built under a Los Angeles suburb, allowing reporters and guests to take rides. It came almost two years to the day after Musk announced on Twitter that “traffic is driving me nuts” and he was “going to build a tunnel boring machine and just start digging.”
“I am actually going to do this,” he added in response to initial skepticism. Soon after, he began The Boring Company, tongue in cheek intentional.
The skepticism has not subsided. The Boring Company in November canceled its plans for another test tunnel in the Los Angeles area after a neighborhood group filed a lawsuit over concerns about traffic and disruptions from trucks hauling out dirt during the boring process.
Now plans for a project in Chicago appear to be in jeopardy. Neither mayoral candidate approves of plans announced in June that called for a system similar to the one proposed for Las Vegas. It would carry people between Chicago’s downtown and O’Hare International Airport at speeds of up to 150 mph (241.4 kph) through underground tunnels.
Hill said he does not expect permitting processes in the Las Vegas area to put the project behind schedule should it be approved, because the city is “committed to innovation.”
“Look at everything that we have built in Las Vegas, and this city and everybody who has built it found ways to make that happen,” he said. “As long as this continues to make sense, I believe that we will figure out how to make it happen.”
Hill acknowledged the technology that will be used in the project has not been used commercially, but he said the company has the talent to make the project a reality.
The confidence in The Boring Company is such that the authority already has optional routes for the tunnel system to expand to connect to the Las Vegas Strip, the city’s downtown and McCarran International Airport. An expansion of that magnitude could be a solution to the congestion affecting the Strip and nearby areas.
“We do see it as a real opportunity and something we would like to pursue,” Hill said.
Steve Davis, president of The Boring Company, said the speed at which the vehicles will move inside the convention center’s tunnels will depend on the number of stations built. The technology involved in the project is being tested every day in the tunnel in Hawthorne, California, he said.
The company believes it will be able to deliver the project by the 2021 deadline, just before that year’s edition of the CES tech gadget gathering. It is also eyeing the expansion possibility.
“If the community likes it, and they come, they ride at the convention center and they say ‘This is great. It’s comfortable. It’s fast. It’s awesome.’ Well, there are other places it can go,” Davis said.
Follow Regina Garcia Cano on Twitter at https://twitter.com/reginagarciakNO
How to prevent the ‘robot apocalypse’ from ending labor as we know it
March 7, 2019
Thomas Kochan, Professor of Management, Co-Director of the MIT Sloan Institute for Work and Employment Research, MIT Sloan School of Management
Elisabeth Reynolds, Executive Director of MIT Industrial Performance Center and Work of the Future, Massachusetts Institute of Technology
Disclosure statement: The authors do not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and have disclosed no relevant affiliations beyond their academic appointment.
It seems not a day goes by without the appearance of another dire warning about the future of work.
Some alarmists fear a “robot apocalypse,” while others foresee the day of “singularity” coming when artificial intelligence exceeds human intelligence. Still others warn that income inequality will continue to rise as owners of capital capture more of the benefits of innovations than those who labor for a living.
Yet there is also a counter-trend emerging: Groups as diverse as the World Economic Forum and the International Labor Organization are beginning to argue that it’s up to society to shape the future of work. What’s needed is action today to harness and channel technological changes, prepare the workforce for new demands and opportunities, strengthen their voices and built a new social contract that includes leaders in business, education, labor and government.
These are some of the issues we’ll be discussing in an online course that draws on some of the best experts in AI, robotics, economics and employment relations at MIT and around the world. Our main point is that avoiding apocalyptic outcomes requires bold actions and a collaborative approach.
How to shape change
Virtually every technological revolution has inspired workers to fear for their jobs. And for good reason.
Each one resulted in the creation of new jobs alongside the elimination of others. At the same time, new technologies changed the way work is done within most occupations.
But fighting technology-inspired changes, as the Luddites of the early 19th century did, rarely works – and can in fact have disastrous consequences. The Luddites, textile workers and weavers who feared the advent of automated looms in England, destroyed machines and burned factories, hoping to arrest their advance. The government eventually quashed the unrest, killing some workers and jailing many others.
The new technologies that transformed the textile industry continued unabated. While many weavers lost their jobs, it created new ones for mechanics and other industrial workers and increased overall productivity.
The important lesson from this episode is that the transition from an agricultural to an industrial economy occurred in the absence of updated policies to govern the transition, which led to more pain for those who were displaced than was necessary.
So as today’s workers in dozens of occupations face down the robot apocalypse, what’s needed aren’t more battle cries but concerted action by leaders in business, education, government and, of course, labor. And if, as predicted, AI and robotics do transform nearly half of jobs requiring new skill sets for workers, the current challenge may be greater than ever, making it even more important that we create a vision and a path forward that everyone can support.
Giving ‘wisdom to the machines’
Let’s start with business leaders since they buy and implement most new technologies.
The dominant business motivation for introducing new technology is to reduce human labor and the costs associated with it. Robots, or more broadly software, don’t leave for another job, go on strike or need bathroom breaks – let alone a paycheck or benefits.
But there is ample historical and current evidence that simply viewing technology as a labor cost saving tool leads to over investment and weak returns.
Just ask General Motors what it got for its nearly US $50 billion in robots in the 1980s in its futile effort to catch up with Toyota’s more efficient production and labor relations systems. The answer is not much.
Instead, GM eventually learned from Toyota via a joint venture that the highest return on investments came by integrating new technology with new work practices, which allowed workers to help “give wisdom to the machines.”
The key lesson for business is that it needs to engage workers in designing and deploying new technologies to get the greatest productivity gains.
Learning for life
Lifelong learning is the new buzz phrase when it comes to discussions of work. Transforming this from rhetoric to reality will require fundamental changes in educational institutions and teaching methods.
It starts with the children in schools today who will likely be most affected by the AI revolution in coming decades. And while in the past the focus was on the STEM disciplines – science, technology, engineering and math – industry leaders these days say they need tomorrow’s workforce to be filled with people who can think analytically and creatively, work well together in teams and can adapt readily to near-constant change.
In other words, workers need to be inculcated from an early age with more behavioral and analytic skills, such as teamwork, communications and problem-solving with data.
Even after people are in the workforce, learning new skills and acquiring new knowledge will continue throughout their careers. That means businesses and universities will need to form new partnerships that ensure the workforce can continue to adapt.
A new social contract
A key way government can contribute is by revisiting the legislative framework that supports labor.
The New Deal was a series of programs, projects and reforms that helped shift the U.S. from a primarily agricultural to industrial economy. It established collective bargaining rights, created Social Security and unemployment insurance, and set minimum wages and labor standards.
With the rise of the gig economy and the changing nature of the employer-employee relationship, a new social contract is necessary to support workers in this new reality. Benefits should be portable so workers can easily move from job to job without losing health insurance and other benefits now tied to a specific employer. Post-secondary education needs to be more affordable.
Labor law should make it easier so different kinds of workers, from professionals, to low wage workers, to independent contractors, can all have their voices heard. And safety nets need strengthening to support those displaced or whose career has been downgraded by all the seismic changes coming our way.
Workers need a seat
As for labor leaders, they need to make sure they’re at the table with business, education and government to ensure workers aren’t left behind by new technologies.
Training needs to be at the top of union bargaining agendas with business so that organized labor can be a champion of lifelong learning for workers. One important way is by building, expanding and modernizing apprenticeships.
In addition, they can’t just wait to be invited by companies to participate in discussions about implementing new tech. The union representing hotel workers is showing how to get engaged by actively negotiating new agreements with big casinos in Las Vegas and large chains like Marriott to ensure workers are heard in the process and are fairly compensated along the way.
The key point is that none of these groups can meet the coming challenges on its own. Just as we’ll be doing in our class in coming weeks, people from all walks of life and segments of society should be discussing these issues so everyone can participate in shaping the future of work.
Joe Dirk: Perhaps some day humans will learn to sit back, relax, and let their machines do the work for them. Reminds me of an old Loony Tunes with Goofy: (paraphrased) Humans were bored – and then they discovered their thumbs.
New AI art has artists, collaborators wondering: Who gets the credit?
March 7, 2019
Author: Aaron Hertzmann, Affiliate Faculty of Computer Science, University of Washington
Disclosure statement: Aaron Hertzmann works for Adobe Research, however, opinions expressed here are solely his own.
Partners: University of Washington provides funding as a member of The Conversation US.
Over the past few years, many artists have started to use what’s called “neural network software” to create works of art.
Users input existing images into the software, which has been programmed to analyze them, learn a specific aesthetic and spit out new images that artists can curate. By manipulating the inputs and parameters of these models, artists can produce a range of interesting and evocative images.
This work has gained widespread recognition through gallery shows, media coverage and two high-profile art auctions.
As an academic researcher, developer of artistic technology and amateur artist, seeing artists embrace new technology to create new forms of expression always thrills me.
But, like previous groundbreaking art movements, neural network art raises difficult questions: How do we think of authorship and ownership when these artworks come from the contributions of so many different creative individuals and algorithms? How do we ensure that all the artists involved are treated fairly?
A movement is born
The vibrant neural network art world arose in the past few years, in part, from developments in computer science.
It began in 2015 with a program called DeepDream, which was developed accidentally by a Google engineer. He wanted to find a way to visualize the workings of a neural network system designed to analyze images. To do this, he gave it an input photograph and asked it to increase the number of object parts detected in the image. The result was a panoply of weird and evocative images.
He shared his method online, and artists immediately began to experiment with it. The first gallery show of DeepDream art occurred less than a year later.
Because this software is all freely shared online, digital artists can experiment with these models, and then share their own results and modifications.
There’s an active creative community of neural network artists on Twitter who discuss the results of their experiments, along with the latest developments and controversies. And major mainstream artists have also embraced these tools, with major shows and commissions by artists like Trevor Paglen, Refik Anadol and Jason Salavon.
Nonetheless, this open sharing challenges the ways we think about art. Christie’s sale of the image “Edmond de Belamy, from La Famille de Belamy” in November 2018 for nearly US$500,000 indicated that something was awry.
Why? To make this image, the artist group Obvious used the source code and data that another artist, Robbie Barrat, had shared freely on the web.
Obvious had every right to use Barrat’s code and claim authorship of the work. Nonetheless, many criticized Christie’s for elevating the artists who played only a small part in the creation the work. This was generally read as a failure of Christie’s, particularly in the misleading way it promoted the work, rather than a need to rethink authorship of AI art.
The emergence of Ganbreeder
These issues really become unavoidable in Ganbreeder, a beguiling new website for creating images with neural networks.
Ganbreeder is an endless source of inspiring, intriguing, weird and fascinating imagery. Unlike the images that emerge from DeepDream, which quickly become repetitive, it seems like no single human mind could ever be capable of producing Ganbreeder’s diverse range of original imagery.
Ganbreeder was launched last November by Joel Simon. Each Ganbreeder image is created with input parameters that you choose by modifying the parameters of other images on the site. The site stores the lineage of each image, so that you can see all who contributed to a final image.
If you like an image you’ve found or created, you can order a custom print on wood from an entrepreneur and artist named Danielle Baskin. She touches up the print with paint, but instead of signing it, labels the back of the work with a QR code that points to image’s unique lineage.
She does this because each image is the result of many people’s contributions, which makes it difficult to attach the name of any one sole artist to each new artwork.
Giving credit where credit’s due
A sole artist, however, has already taken credit.
When Alexander Reben exhibited paintings he’d made of Ganbreeder images, Baskin accused him of stealing, since she and others had spent hours on the Ganbreeder site to make the images. To defend himself, Reben pointed out that Ganbreeder works were anonymous when he selected his images; user logins and attribution were only added in February.
Existing laws and conventions already address cases in which artwork is created in some form of collaboration or remix. It’s generally accepted that an artist can claim authorship simply by selecting a final image, though they should be upfront about the sources, when possible. The accusations of stealing seem to mimic those lobbed against conventional appropriation artists like Andy Warhol and Richard Prince, who famously enlarged and modified Instagram posts made by other users.
However these neural network works seem to be a different sort of work. The contributions of the neural network model and the other users of the site are all inseparable from the result. No one contributor seems to be “the artist.”
One possible way to view these new works of art is to think of them like open source software. Open source is a model for software development in which anyone can contribute to or use open software packages. It has led to the creation of major software tools, like Linux and major neural network software, that could not have been developed otherwise. Likewise, the new neural network artworks could not have been created without open sharing of software and data.
Open source projects specify clear rules for how the software may be used and credited: Some software may be extended and sold, while other projects must always be distributed for free. Each programmer’s contributions are recorded; how they are credited also depends on the individual project.
Like open source software, sites like Ganbreeder could establish clear rules for artistic authorship and credit. The guidelines should establish how to claim credit for a work, who else must be credited, and when a work can be sold or copyrighted.
Payment is a tricky issue. What happens when Ganbreeder images are used for commercial work – say, book covers or film production? For more mundane contributions, Baskin has suggested that payment could be shared among the work’s many contributors. This could become profitable; the royalties from a single major advertising campaign could pay for a lot of artists’ meals.
A ‘photography of imaginary things’
Then there’s the issue of value and intent. Can these works ever rise to the status of great art?
Some of an artwork’s value simply lies in its intrinsic aesthetic properties, the way a mountain might be beautiful. But we also value work because it emerged out an artist’s vision, intention and skill.
An open source artwork lies somewhere in the middle. This imagery represents the outcome of many human minds making deliberate artistic selections. But where was the intent? Surely, an early contributor had no idea how their work would be used.
Is it like asking for the intent behind a beautiful mountain? Or is the artist making the final choice the sole source of intent?
Previous art technology raised similar questions, notably with the invention of photography. When the medium first emerged, many claimed that photography could not be art at all. After all, they argued, it’s the machine that’s doing all the work – a sentiment now echoed in today’s misguided claims that “AI creates its own art.”
It took a while, but photography was eventually recognized as its own artistic medium. Moreover, it catalyzed the modern art movement by forcing artists to stop placing realism on a pedestal. Because they could never match the realism of the camera, they needed to figure out a way to create works that no mere machine could replicate.
Neural network art is now a kind of photography of imaginary things.
Like photography, neural art can create a seemingly infinite set of images, none of which seem to have much value on their own. The value comes from the unique way in which the artist uses these tools – how they set parameters, select subjects, adjust image details or curate a set of images that make a larger point.
With new neural models being released at a staggering pace, these issues will only become more urgent as more wonderful, weird and inspiring imagery emerges.