Daily Archives: July 20, 2017

Artificial intelligence poses an existential risk to human civilization, Elon Musk (right) told the National Governors Association meeting Saturday in Providence, R.I. Stephan Savoia/AP hide caption

Artificial intelligence poses an existential risk to human civilization, Elon Musk (right) told the National Governors Association meeting Saturday in Providence, R.I.

Elon Musk is warning that artificial intelligence is a "fundamental existential risk for human civilization," and Colorado Gov. John Hickenlooper is looking into how states can respond.

Musk, the Tesla and SpaceX CEO, made the remarks over the weekend at the National Governors Association meeting in Rhode Island. He has long warned of the threats he believes artificial intelligence will pose, from automation to apocalypse. Bill Gates, Stephen Hawking and others have also sounded warnings over AI.

"Of all the things that I heard over this weekend with the National Governors Association, this was the one that I've spent more time thinking about," says Hickenlooper, a Democrat.

Not everyone at the NGA meeting received Musk's comments as warmly as Hickenlooper. Republican Gov. Doug Ducey of Arizona told Musk: "As someone who's spent a lot of time in [my] administration trying to reduce and eliminate regulations, I was surprised by your suggestion to bring regulations before we know exactly what we're dealing with."

Colorado Gov. John Hickenlooper suggests that governors need to work together on possible solutions to problems like the potential threats posed by artificial intelligence. Brennan Linsley/AP hide caption

Colorado Gov. John Hickenlooper suggests that governors need to work together on possible solutions to problems like the potential threats posed by artificial intelligence.

Other Silicon Valley thinkers are skeptical of Musk's doomsday prophesying. Yann LeCun, the head of AI at Facebook, told NPR's Aarti Shahani that humans are projecting when we predict Terminator-style robot takeovers. He says the "desire to dominate socially is not correlated with intelligence"; it's correlated with testosterone, "which AI systems won't have."

Hickenlooper spoke to NPR on Tuesday evening. Here are highlights from that interview.

On the mood in the room while Musk was speaking

You could have heard a pin drop. A couple of times he paused and it was totally silent. I felt like I think a lot of us felt like we were in the presence of Alexander Graham Bell or Thomas Alva Edison ... because he looks at things in such a different perspective.

On the threat that AI could pose

Right now we worry about cybersecurity and issues like that, but when you really have artificial intelligence at a great level, the weaponry and the ability to shut down whole parts of our cities, the ability to create such damage by turning off the electricity, or making sure there's no water ... everyone was spellbound I mean no one knew what to say.

On when government needs to step in

Usually what happens is something gets a little out of hand and then government begins to regulate. And [Musk] said, in this case, with artificial intelligence we need to get the regulations out well ahead of the problems appearing. Because it's going to happen so quickly that we need to have that anticipation and be working on it, because once you get to regulating something, everyone's got a self-interest, and it means taking away something from somebody who's already got it.

On how states can tackle such a big problem

Oftentimes, I think with the really difficult problems and we're trying to do this with health care now is to look at getting a number of state governors, both Republicans and Democrats, to come together around a specific issue and what the possible solutions are and have the governors work through possible solutions, because so often we're the ones where the solution gets implemented.

Dave Blanchard is an editor with Morning Edition. You can follow him @blanchardd.

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Musk's Warning Sparks Call For Regulating Artificial Intelligence - NPR

Facebook showed off some artificial intelligence at its F8 event.

The United Kingdom's government has some questions about artificial intelligence.

On Wednesday, the House of Lords announced a public call for experts to weigh in on issues surrounding AI, including its ethical, economic and social effects as the technology becomes more prevalent.

When you think about all the crazy things that AI can accomplish, like a sex robot with a "brain," yeah, we've got some questions too.

AI is already poised to take over jobs, as it has for an insurance company in Japan, but Britain's Parliament has concerns from all sides. Members of Parliament want to know who AI is helping the most, who it's hurting, what role the government should play, and how AI will look in the next 20 years.

"The Committee wants to use this inquiry to understand what opportunities may exist for society in the development and use of artificial intelligence, as well as what risks there might be," Lord Clement-Jones, chairman of the committee on AI, said in a statement.

Experts can submit their testimonies here. The deadline for entries is on Sept. 6.

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UK government launches artificial intelligence inquiry - CNET

Its hard to open a newspaper these days without encountering an article on the arrival of artificial intelligence. Predictions about the potential of this new technology are everywhere.

Media hype aside, real evidence shows that artificial intelligence (AI) already drives a major shift in the global economy. You now use it in your day-to-day life, as you look to Netflix to recommend your next binge or ask Alexa to play music in your home. And the benefits of AI are driving the technologies into every corner of the global economy. Look, for example, at the number of times the largest U.S. companies mention artificial intelligence in their 10-K filings. (See chart below, which measures mentions of "artificial intelligence" and related worlds in 10-K filings of S&P companies, from 2011 to 2016.)

For all of the debate about the dawn of artificial intelligence, there is little talk about what AI means for sustainability.

Will AI mean a massive technological boost to sustainability priorities? Or will the rapid changes associated with AI give us a net negative sustainability outcome? By mining the narrative disclosures that companies make about their CSR activities, we can derive some insights into how AI is transforming corporate sustainability activity. Using keyword searches in ESG Trends, a dataset of corporate sustainability disclosures, we looked across thousands of CSR reports and CDP disclosures from large, global companies to see what, if anything, companies are disclosing about the impact of artificial intelligence. This analysis below, which measures mentions of AI in corporate sustainability reports and CDP filings, can help us start to answer the question: What does AI mean for sustainability?

What we see is that AI is already having an impact on corporate sustainability activity. Companies already are making use of AI to achieve step changes in, for example, efficiency and emissions reductions, and to innovate new products and services. These AI applications for sustainability are not widespread, and they are early stage, but the data suggests that AI can bring significant benefits for sustainability in the medium term. What we dont see, however, is much evidence that companies are understanding the numerous and serious risks that AI presents.

The vast majority of the mentions of artificial intelligence in CSR reports and CDP filings relate to how AI presents opportunities for companies. AI is helping the next generation of companies reduce their environmental and social impact by improving efficiency and developing new products.

We can look first at utility company Xcel Energy. When the company creates electricity from burning coal at its two plants in Texas, one major byproduct is a potent greenhouse gas called nitrous oxide. Nitrous oxide emissions contribute to climate change, as well as harming the ozone layer.

Recently, the company has received a little extra help in reducing its emissions from artificial intelligence. Xcel has equipped its smokestacks in Texas with neural networks, an advanced artificial intelligence that simulates a human brain. The neural network quickly can analyze the data that results from the complex dynamics of coal combustion. It then can make highly accurate recommendations about how to adjust the plants operations to reduce nitrous oxide emissions and operate at peak efficiency. Neural networks have helped Xcel Energy and over a hundred other companies around the world reduce their nitrous oxide emissions.A report from the International Energy Agency estimated that artificial intelligence control systems such as Xcel Energys neural networks could reduce nitrous oxide emissions by 20 percent.

AI applications for sustainability are early stage, but the data suggests they can bring significant benefits in the medium term.

Another example is Google. The search giant recently hit a wall in improving data center efficiency. The company had optimized its data center energy use to a point where engineers felt it could not be improved much more. Then one of its engineers had an idea to deploy a machine learning model developed for another application to assist in optimizing efficiency in its data centers.

Google deployed the artificial model to "learn" when and why certain processes occurred in the data center. Based on this data, Googles algorithms were able to identify options for significant additional savings. Googles application of AI has helped to reduce the amount of energy used for cooling data centers by 40 percent good for the companys bottom line, and good for the planet.

Artificial intelligence is also enabling companies to develop new products and services that were unthinkable just a few years ago. In some of these cases, companies are deploying artificial intelligence directly to help them make progress on tough environmental and social challenges.

IBM, for example, is using its artificial intelligence expertise to improve weather forecasting and renewable energy predictions. The system, known as SMT, "uses machine learning, big data and analytics to continuously analyze, learn from and improve solar forecasts derived from a large number of weather models." Through the application of artificial intelligence and "cognitive computing," IBM can generate demand forecasts that are 30 percent more accurate. This type of forecasting can help utilities with large renewable installations better manage their energy load, maximize renewable energy production and reduce greenhouse gas emissions.

One of the best-known examples of artificial intelligence in action is in autonomous vehicles. Cars that drive themselves may offer a promising sustainability future: currently one-quarter of U.S. greenhouse gas emissions come from transportation. Machines will be more efficient at driving than humans. Engines in machine-driven cars can be smaller, using less gasoline. And autonomous vehicles can platoon together just inches from one another, improving efficiency and leaving more space on the road for cyclists, public transport or pedestrians. Google, Uber, Tesla, Ford, Nissan and other companies are working hard to develop self-driving cars.

It is not just tech companies that see report sustainability-related opportunities from AI. Interserve, for example, a FTSE-listed construction company, builds and manages sensitive facilities, including schools, hospitals and clinical facilities, where operational safety is critical. The company uses real-time data to alert personnel when dangerous, waterborne pathogens such as Legionnaires bacteria develop. The company reported that it is exploring artificial intelligence to predict when these diseases will occur so it can fix issues before they develop, increasing safety and saving on maintenance costs.

Interserves work, alongside that of Xcel Energy, Google, IBM and other companies, shows that AI has the potential to provide a major technological boost to help companies achieve sustainability goals.

However, AI applications for sustainability are in their infancy. Only a small percentage of the thousands of companies we analyzed mention artificial intelligence at all in their CSR disclosures. And as AI scales to create more sustainability opportunity, companies also will have to navigate the risks.

Judging from their official disclosures, companies are eager to embrace the opportunities presented by AI. They also appear remarkably unconcerned about the risks. In a review of more than 8,000 CSR reports and CDP disclosures over the last two years, we failed to find more than a handful of mentions of the risks to companies that AI poses.

One sustainability-related risk that AI poses is automated bias. Bias can happen when the machine learns to identify patterns in data and make recommendations based on, for example, race, gender or age.As AI algorithms do more analysis, companies must be diligent in ensuring that their algorithms analyze data and make predictions in a fair way.

One sustainability-related risk that AI poses is automated bias.

For example, credit scoring companies such as TransUnion use artificial intelligence to analyze a variety of data points to determine credit worthiness. Undiagnosed bias in such algorithms could lead to poor credit scores for groups of people based in part on gender or race, which is expressly prohibited by law and could expose the company to legal claims. What is a companys policy toward algorithmic decisions? Are the companys algorithms certified by a third-party to be bias-free? These are essential questions that companies should begin assessing and disclosing now.

Another risk from AI is that the sustainability benefits that companies tout such as major efficiency breakthroughs and clean, self-driving cars may not materialize, or may be offset by other consequences of AI.

For example, some studies suggest that the environmental benefits from self-driving cars may turn out to be mixed at best. Machines driving our cars, for example, may lead to people making more trips, which could lead to increases in emissions, not decreases.

Another major risk for the planet is that large-scale implementation of artificial intelligence may eat all of our jobs, leading to widespread unemployment. A recent report estimated that automation will replace 6 percent of U.S. jobs by 2021, with further job reductions coming in the medium term. A world without jobs presents a host of new, uncharted challenges for sustainability, few of which we can predict.

Artificial intelligence is already here. It will continue to gain in complexity and sophistication. It presents excellent opportunities for efficiencies and innovation, many of which were unthinkable just a few years ago.

Many of these innovations will allow us to make significant progress on the most difficult environmental and social problems facing humans. At the same time, these same efficiencies and innovations bring with them new risks, such as automated bias and large-scale job losses. More companies quickly must come to grips with both the sustainability opportunities and risks that AI brings.

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What artificial intelligence means for sustainability - GreenBiz

Apple is lifting the veil on some of its work in the red-hot field of artificial intelligence.

The consumer technology giant debuted Wednesday a website that highlights the companys various AI-related research projects. Named the Apple Machine Learning Journal, the tech giant is pitching it as a way for people to read about the work of its various engineers working on cutting-edge AI techniques like deep learning.

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Ruslan Salakhutdinov, Apples director of AI research, announced the debut of the website via Twitter. Apple hired Salakhutdinov, who is also a Carnegie Mellon University associate professor specializing in machine learning, in October amid an increasing push by big tech companies like Google that are hiring AI experts from academia.

Apple currently lists only one research project on the new website that appears to be a re-written version of a research paper published in fall. Unlike the original research paper, Apple has removed the names of the researchers who worked on the paper for the revised version now posted on the Apple Machine Learning Journal.

The websites first post shows how Apple is researching how to teach computers to recognize faces by training them on images of computer-generated faces rather than pictures of actual human faces. Apple, which has stricter user privacy rules than companies like Google and Facebook , could benefit from this research if it could create AI systems do not require as much personal data for training.

With the new website, Apple joins other big tech companies like Google ( goog ) , Facebook ( fb ) , and Microsoft ( msft ) that maintain blogs highlighting how they are researching or using AI technologies in their products.

Besides functioning as a way to publicly demonstrate that these companies are using cutting-edge tech, these research blogs also function as recruiting tools for machine-learning specialists.

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Apple Just Got More Public About Its Artificial Intelligence Plans - Fortune

Nvidia Corp. (NVDA) is set to face a much tougher competitive environment in the white-hot market for server co-processors used to power artificial intelligence projects, as the likes of Intel Corp. (INTC) , AMD Inc. (AMD) , Fujitsu and Alphabet Inc./Google (GOOGL) join the fray. But the ecosystem that the GPU giant has built in recent years, together with its big ongoing R&D investments, should allow it to remain a major player in this space.

This column originally appeared on Real Money, our premium site for active traders. Click here to get great columns like this.

It's a basic rule of economics that when a market sees a surge in demand that leads to a small number of suppliers amassing huge profits, more suppliers will enter in hopes of getting a chunk of those profits. That's increasingly the case for the server accelerator cards used for AI projects, as a surge in AI-related investments by enterprises and cloud giants contribute to soaring sales of Nvidia's Tesla server GPUs.

Thanks partly to soaring AI-related demand, Nvidia's Datacenter product segment saw revenue rise 186% annually in the company's April quarter to $409 million, after rising 205% in the January quarter. Growth like that doesn't go unnoticed. Over the last 12 months, several other chipmakers and one cloud giant have either launched competing chips or announced plans to do so.

To understand why some of these rival products could be competitive with Tesla GPUs on a raw price/performance basis, it's important to understand what made Nvidia's chips so popular for AI workloads in the first place. Whereas server CPUs, like their PC and mobile counterparts, feature a small number of relatively powerful CPU cores -- the most powerful chip in Intel's new Xeon Scalable server CPU line has 28 cores -- GPUs can feature thousands of smaller cores that work in parallel, and which have access to to blazing-fast memory.

That gives GPUs a big edge for projects that involve a subset of AI known as deep learning. Deep learning involves training models that attempt to function much like how neurons in the human brain do to detect patterns in content such as voice, text and images, with the algorithms used by the models (like the human brain) getting better at both understanding these patterns as they take in more content and applying what they've learned to future tasks. Once an algorithm has gotten good enough, it can be used against real-world content in an activity known as inference.

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Nvidia Faces Much Tougher Competition in Artificial Intelligence, but Will Still Be OK - TheStreet.com