Tom Vander Ark
On a recent visit to Energy Institute High School in Houston, students were contemplating the impact of robots and artificial intelligence (AI) on their community.
Artificial intelligence, big data, and a set of enabling technologies like robotics are rapidly changing the employment landscape, but this was the first time I've seen this important conversation discussed in high school. AI will be the single most important change driver over the next two decades. Like these Houston Energy pioneers, very high school student should have the opportunity to study artificial intelligence and its influence on their life and work.
AI–the notion that machines could exhibit human intelligence–was conceived in the 1950s but it became a really big deal with the recent explosion of big data powered by cheap computing and storage (Moore’s Law) and lots of devices, sensors, cameras and RFID tags (the Internet of Things).
AI is a growing web of related technologies that, given ubiquitous use, broke through to the popular press in 2016. When Google’s DeepMind beat the world champion Go player in March and self-driving cars showed up in Pittsburgh in September, it became obvious that this new cluster of technologies was moving fast and had broad implications.
In the early 2000s, Bill Gates aimed Microsoft researchers at speech recognition. By the end of the decade, they were making progress with deep stacks of neural networks. In the last few years, the use of deep learning algorithms has produced accurate speech and image recognition–in some cases better than experts. AI routinely beats radiologists at tumor detection.
As illustrated above (image from Michael Copeland on blog.nvidia.com) from a blog by tech journalist Michael Copeland, deep learning is a subset of machine learning. If AI is forms of human intelligence exhibited by machines:
• Machine Learning, a subset of AI, is using algorithms to learn from data and then make a determination or prediction.
• Neural networks, a subset of machine learning, were inspired by the connections of the human brain. But unlike the brain, neural nets have discrete layers that direct the data flows. They’ve been around since the early days but were computationally intense
• Deep Learning: While at Google in 2012, Andrew Ng put the “deep” in deep learning by adding layers of neural networks and then running massive amounts of data through the system to train it. (For more, listen to this Frank Chen video)
CEO Sundar Pichai has made AI central to the Google strategy, marking a shift from search to suggestion. In the “AI-first” era, Google products will help people accomplish tasks in increasingly sophisticated, even anticipatory ways.
The Venn diagram above illustrates how deep learning is a subset of AI and how, when combined with big data, can inform enabling technologies in many sectors. For examples, to AI and big data add:
• Robotics, and you have industry 4.0.
• Cameras and a sensor package, and you have self-driving cars.
• Sensors and bioinformatic maps, and you have precision medicine.
• CRISPR, and you have genomic editing.
• Chatbots, and you have personalized retail and music.
The profound change is that rather than hard coding a solution, you can feed large datasets into a machine learning application and it can learn how to perform a task better and quicker than expert humans. The combination of deep learning and big data has resulted in impressive accomplishments in the past year–in addition to beating the world champion Go player (after analyzing millions of professional games and playing itself millions of times), also playing dozens of Atari video games better than humans and reading and comprehending news articles.
AI Transforming Industries
MIT’s Eric Lander said in a few years every biologist will be computational. It looks like the same will be true for doctors, mechanics, economists, water managers and soldiers–nearly every field is being transformed by the combination of AI, big data and enabling technologies.
CB Insights illustrates the explosion of AI startups transforming every industry in the graphic below:
A September Stanford study identified profound impacts in eight domains where AI is already having or is projected to have the greatest impact: transportation, healthcare, education, low-resource communities, public safety and security, employment and workplace, home/service robots and entertainment.
Life With Smart Machines
Back to those high school students contemplating futures with smart machines. Given the opportunity for a deep dive, they are likely to draw six conclusions:
1 Automation will change the nature of work for several billion people—enabling (and requiring) them to work with smart machines while increasing skill requirements and extending individual contributions.
2 Waves of job losses over the next decade will impact hundreds of millions of people, as roles based on repetitive rules application are likely to be phased out.
3 High skill jobs will be created in Smart Cities that skill up around emerging opportunities like custom manufacturing.
4 Human judgment becomes more valuable as machine intelligence makes predictions cheap. Empathy and social interaction, creativity and design thinking, and an innovation mindset will be increasingly in demand.
5 Income inequality is likely to grow with a divide between those who can code and leverage smart tools and those performing nonrepetitive service jobs. Narrowing the divide will require a new social contract that may include a guaranteed income.
6 Ethical issues, such as genomic editing, security and privacy, and biases (taught and learned) will outstrip civic problem-solving capacity.
It’s Time To #AskAboutAI
An October White House report suggested that AI has the potential to solve some of the world’s greatest challenges and inefficiencies, specifically in education, healthcare, energy and the environment. On the other hand, AI is rapidly reshaping the employment landscape and surfacing mind-bending ethical issues like genomic editing. Given the opportunities and challenges, it is a topic every school community should be discussing–we think it’s time to #AskAboutAI.
We have four goals for this thought leadership campaign:
1 Predict labor market impacts including types of jobs and job competencies by 2030.
2 Identify emerging ethical and social issues that educators, parents and policymakers should begin addressing.
3 Advise educators, parents and policymakers on knowledge, skills and dispositions likely to be important in the automation economy.
4 Illustrate new impact pathways that combine domain expertise with data science (we call it cause + code)
We welcome your questions, comments and contributions to this campaign. The future is ours to shape–but it’s coming at us faster than ever.
For more, see:
• Want to Solve a Problem? Get Smart, Build a Dataset, Apply Smart Tools
• The Rise of AI Demands Project-Based Learning
• Tell Kids to Get Good at Stuff Smart Machines Can’t Do (Yet)
• 3 Reasons To Expect the Unexpected…and What To Do About It
• Novelty & Complexity: 13 Youth Onramps
• Smart Machines Will Eat Jobs—Except Where Smart People Create Them
Senior Partner and Brand Specialist
Pepsi just released one of the most tone-deaf, vapid, reaching commercials I’ve seen in my lifetime. Not just because it’s pathetic, pandering, and preposterous, but because it misses the mark in so many ways I lost count.
In the pantheon of offensive media, this is the holy grail. The Magnum opus. A love letter to disconnectedness. This is the Philosopher's Stone of crap media. They turned gold back into lead. As a millennial, I found myself frustrated. As an African American, I found myself watching mouth agape as Pepsi reduced very real challenges that we experience as a community to ‘a couple of guys in need of a Pepsi.' When it ended, my business partner and I just sat in silence for about 30 seconds trying to piece together what we saw. Then we watched it again to make sure we were not overreacting.
As a storyteller and brand strategist, there are lessons in this. But as human beings, we must fight for more understanding. So to those points, let’s break down where Pepsi went wrong.
The Anatomy of a Train Wreck
Firstly, the Kardashian family are the poster children of modern cultural appropriation. From “boxer braids” or the sudden acceptance of curves and full lips, the Kardashians have made millions off of features that African American and Hispanic people had previous been made to feel ashamed of. To make Kendall Jenner the face of, largely ethnic, protests is yet another slap in the face. A caucasian, blonde, classically beautiful, affluent, kid born into celebrity probably isn’t the person you need to represent struggle and civil unrest.
Here we have Kendell Jenner, just trying to enjoy her photoshoot. She finds herself mildly intrigued, but hardly moved by the hundreds (if not thousands) of protesters fighting for their rights, civil liberties, and in many cases, their rights to live. Unfazed, she continues to be as cute as possible, as not to let this small distraction pull her away from her more important duties.
This is the first, but certainly not the last, haphazardly shoehorned in product shot of Pepsi. Forced into our gaze by yet another unfazed citizen. The crowd of freedom fighters is not enough to stop her from enjoying her fresh, crisp, cold Pepsi. No siree-bob. It’s Pepsi o’clock. Who has time for a revolution?
It was at this moment we realize that no one that contributed to this production has ever been to a protest or felt the tension that hangs in the air when lives are at stake. There are literally people behind these two young ladies, calling for respect and attention. Instead, they get glammed up, grab an onlooker and pose for a beauty shot. "Who needs change when we’ve got eyeliner and hashtags!?"
In a photography studio, we find the only person with an ounce of negative emotion. She’s sufficiently ethnic and driven into a state of rage by not being able to find the perfect inspiration for her photos. Incidentally, she has the same face most of us will after watching this commercial. Foreshadowing? Maybe.
Ah yes, here we go. The only thing that can compel Kendall to join the fight for equal rights and lives. A cute guy. He’s just a little rough around the edges but absolutely cute enough to risk your life over.
Beauty shot! The graphics go into high gear and Kendall magically becomes a little more ethnic -- for dramatic effect of course.
After a few more congratulatory head nods and fist bumps from men of various brown hues, she channels the spirit of Ieshia Evans, who heroically risked her life to stand up to the Swat teams bearing down on protesters in Baton Rogue. This is certainly the same sort of thing.
If you are going to market to millennials, remember that you’re going into an open forum. This is not a one-way conversation. This generation is especially brutal when it comes to being patronized or talked down to. The narrative of a young person being compelled into action by the passion of her peers and empathy for the challenges experienced by others could have been amazing. The story of a young girl, lightly encouraged by a cute guy into handing a Pepsi to a police officer as a sign of “peace we can buy.” Not nearly the same thing. You could almost hear the brand managers at Pepsi whispering into the director's ear,
“...show more Pepsi”
Honestly, If we are going to move toward ethical business practices and compassionate marketing then we have to realize taglines, Instagram models, and big spend ad buys are not going to do it. True cultural sensitivity and self-awareness is the only way. That can only be done by diversifying our leadership and giving opportunities to new talent from all across the global and socio-economic ladder. Either that or we’ll just have a Coke instead.
In a shocking turn of events, Pepsi actually pulled their ad. In another revelation, they released an apology that I'm actually a fan of.
"Pepsi was trying to project a global message of unity, peace and understanding. Clearly we missed the mark, and we apologize. We did not intend to make light of any serious issue. We are removing the content and halting any further rollout. We also apologize for putting Kendall Jenner in this position."
It's very direct, they accept responsibility, and they acknowledge missing the mark. Pepsi even takes the heat off of poor Kendall Jenner who is painted as a casualty of a misguided attempt at "unity through advertising." The swift hand of internet justice strikes again.
The sharing economy Boom and backlash Consumers and investors are delighted by startups offering spare rooms or rides across town. Regulators and competitors are not so sure
AT LYFT’S base in Clara Street, in San Francisco, all is bustle. New staff are being shown the ropes. At least three dogs are tucked under desks or following their owners around. At 15,000 square feet (1,390 square metres), the place is almost four times as big as the old office, but it is already cramped. Lyft is about to move again, to a space of 60,000 square feet.
Lyft is a darling of the “sharing economy”, which uses the internet to bring together people with underused assets—anything from spare rooms to spare time—and others who might like to rent them. Lyft’s stock-in-trade is seats in cars: it registers and vets drivers who are willing to offer a ride in return for a “donation” and to place Lyft’s trademark fluffy pink moustache on the front of their vehicles; passengers request a Lyft, and pay, via a smartphone app. The two parties rate each other afterwards, also through the app, which is a common practice in the sharing economy. Fifteen months ago the service operated only in San Francisco. Now it is in over 30 American cities and entering more by the week. This month it raised $250m from venture capitalists.
It is not travelling alone. SideCar, a similar San Francisco startup, has spread to ten cities. Uber, backed by Google and best known for sleek black limousines, also offers ride-sharing services in both America, under the name of UberX, and Europe, as UberPOP. RelayRides, which lets motorists loan out their cars when they are not using them, is also found across America.
Along with transport, the market most affected by sharing has been accommodation, in which Airbnb, yet another San Francisco company, is the most prominent—and the sharing economy’s brightest star. Its “hosts” offer rooms, flats or houses for short stays in 34,000 cities. On April 18th Airbnb reportedly raised between $450m and $500m in a venture-financing round that valued it at $10 billion.
Not everyone is as delighted by the rise of the sharing economy as its participants and investors. Taxi drivers on both sides of the Atlantic have complained loudly (and, at least in Milan and Paris, violently) about the intruders who, they say, not only undercut their fares but are poorly vetted and underinsured. They have found ready listeners among officials and judges.
On April 15th a court in Brussels prohibited drivers from accepting passengers through UberPOP, on pain of a €10,000 ($13,800) fine. Last month Seattle’s council declared that Lyft, SideCar and UberX should be limited to 150 drivers each at a time—though a petition has gained enough signatures to put this requirement on hold. A judge has already told Lyft to apply the brakes in St Louis, only a few days after it rolled into town. RelayRides shut down in New York almost a year ago, because it fell foul of the state’s insurance laws. In other states, explains Andre Haddad, the chief executive, the company’s insurance policy kicks in once a car is rented out. New York law, however, insists that the owner remains liable.
At its latest valuation, Airbnb is purportedly worth more than all but the biggest hotel chains. Hoteliers do not welcome the competition either, though they claim it has not affected them much. In most cities Airbnb and others have not yet taken much of their business, though this may change, especially at the cheaper end of the market (see article).
Authorities have been gunning for Airbnb anyway. In particular, it has been caught by rules, notably in New York and San Francisco, that outlaw short-term renting to different degrees. In both cities, housing is pricey, if it is not rent-controlled. The idea is to stop homes being turned, in effect, into hotels—and unlicensed, untaxed hotels at that. (Separately, subletting may also break the terms of a lease, putting tenants in hot water with their landlords.)
Airbnb has thus come under fire from Eric Schneiderman, New York’s attorney-general. He is demanding that the company hand over information about hosts with more than one property listed on the site. According to Skift, a travel-industry website, there are 1,849 of these, accounting for 30% of Airbnb’s New York listings; 102 have seven properties or more. This week Airbnb removed 2,000 hosts from its site, but it is resisting Mr Schneiderman’s demands, on privacy grounds. It portrays the attorney-general as persecuting ordinary New Yorkers who want to earn a few extra dollars by renting out their home for a couple of nights. He retorts that some, especially those offering multiple properties, are making a business out of short-term lets, and that these are his only targets. The two sides were in court on April 22nd, but no verdict was reached.
Some sharing-economy businesses have managed to avoid regulatory speedtraps. One such is BlaBlaCar, a French ride-sharing company operating in several European countries. Its users share only intercity rides, and so do not annoy urban cabbies, even though a lift from Nantes to Rennes, more than 100km away, costs no more than a short taxi ride in Paris, according to Frédéric Mazzalla, one of BlaBlaCar’s founders. And drivers merely cover their costs, so they do not trouble the taxman either. “It’s very clear that our drivers don’t make any profit,” Mr Mazzalla says.
Even where companies and regulators have been in conflict, there are signs of peace breaking out. Airbnb has said it is willing to collect hotel taxes in New York, Portland and San Francisco. It has recently revised its terms and conditions, spelling out in greater detail its hosts’ obligations to declare what they earn, as well as to honour their leases. San Francisco is considering the legalisation of some short-term letting. Hosts must live in the property at least three-quarters of the time, register with the city and pay the 14% hotel tax.
Corey Owens, head of public policy at Uber, says that in his industry local authorities can be put into three “buckets”. In the first are those with strict rules that they intend to keep, such as Austin, London, New York and Philadelphia. In the second are places where the future is ambiguous: here he puts Baltimore, Brussels, Paris and Washington, DC. Authorities in the third bucket have recognised that the world is changing. California, where the taxi regulator adopted new rules for ride-sharers last year, is the “primary example”. The trend, Mr Owens thinks, is for regulators to shift from the second bucket to the third, as Washington’s watchdog has done. Alas, in some places—such as Brussels—they may be heading in the other direction.
Fifteen millions dollars to strengthen macroeconomic resilience and to improve competitiveness in Cabo Verde
WASHINGTON, May 1, 2014 - The World Bank’s Board of Executive Directors approved on April 22 a US$15.5 million credit to support the Government of Cabo Verde’s effort to strengthen the country’s macroeconomic resilience to external shocks. The Poverty Reduction Support Credit (PRSC-8) will promote structural reforms that improve competitiveness and productivity to ensure poverty reduction and to boost shared prosperity.
The PRSC 8 is the first in a series of three one-year operations to support the implementation of the Government’s Third Growth and Poverty Reduction Strategy (GPRSP 3). According to Vera Songwe, Country Director for Cabo Verde, “this operation reflects the World Bank’s support for Cabo Verde to adapt the country’s development model to its new economic and financial circumstances; to restore economic growth through structural reforms designed to raise productivity;, and improve the private investment climate”.
“The credit will assist the government in increasing domestic resources, improving the public-investment system to ensure high-quality ventures; and implementing a set of priority reforms focused on the performance of state-owned enterprises (SOEs)”, indicatedFernando Blanco, World Bank lead economist for the Africa Region and Team task leader.
“It will also support reforms to establish a more transparent, fair and flexible investment climate by reducing administrative barriers to trade, rationalizing the tax-incentive system, improving the management of infrastructure assets and conserving Cabo Verde’s natural assets which are vital to maintaining the competitiveness and sustainable tourism industry”,added Mr. Blanco.
On May 2012, the World Bank approved a US$12 million Poverty reduction support credit (PRSC 7) to support the transition between the Second and Third Growth and Poverty Reduction Strategies (GPRSP 2 and 3).
Demand collapse or credit crunch to firms ? evidence from the world bank's financial crisis survey in Eastern Europe
While there is a consensus that the 2008-2009 crisis was triggered by financial market disruptions in the United States, there is little agreement on whether the transmission of the crisis and the subsequent prolonged recession are due to credit factors or to a collapse of demand for goods and services. This paper assesses whether the primary effect of the global crisis on Eastern European firms took the form of an adverse demand shock or a credit crunch. Using a unique firm survey conducted by the World Bank in six Eastern European countries during the 2008-2009 financial crisis, the paper shows that the drop in demand for firms' products and services was overwhelmingly reported as the most damaging adverse effect of the crisis. Other "usual suspects," such as rising debt or reduced access to credit, are reported as minor. The paper also finds that the changes in firms' sales and installed capacity are significantly and robustly correlated with the demand sensitivity of the sector in which the firms operate. However, they are not robustly correlated with various proxies for firms' credit needs