Monthly Archives: August 2017

Under President Obamas leadership, America continues to be the worlds most innovative country, with the greatest potential to develop the industries of the future and harness science and technology to help address important challenges. Over the past 8 years, President Obama has relentlessly focused on building U.S. capacity in science and technology. This Thursday, President Obama will host the White House Frontiers Conferencein Pittsburgh to imagine the Nation and the world in 50 years and beyond, and to explore Americas potential to advance towards the frontiers that will make the world healthier, more prosperous, more equitable, and more secure.

Today, to ready the United States for a future in which Artificial Intelligence (AI) plays a growing role, the White House is releasing a report on future directions and considerations for AI called Preparing for the Future of Artificial Intelligence. This report surveys the current state of AI, its existing and potential applications, and the questions that progress in AI raise for society and public policy. The report also makes recommendations for specific further actions. A companion National Artificial Intelligence Research and Development Strategic Plan is also being released, laying out a strategic plan for Federally-funded research and development in AI.

Preparing for the Future of Artificial Intelligence details several policy opportunities raised by AI, including how the technology can be used to advance social good and improve government operations; how to adapt regulations that affect AI technologies, such as automated vehicles, in a way that encourages innovation while protecting the public; how to ensure that AI applications are fair, safe, and governable; and how to develop a skilled and diverse AI workforce.

The publication of this report follows a series of public-outreach activities spearheaded by the White House Office of Science and Technology Policy (OSTP) in 2016, which included five co-hosted public workshopsheld across the country, as well as a Request for Information(RFI) in June 2016 that received 161 responses. These activities helped inform the focus areas and recommendations included in the report.

Advances in AI technology hold incredible potential to help America stay on the cutting edge of innovation. Already, AI technologies have opened up new markets and new opportunities for progress in critical areas such as health, education, energy, and the environment. In recent years, machines have surpassed humans in the performance of certain specific tasks, such as some aspects of image recognition. Although it is very unlikely that machines will exhibit broadly-applicable intelligence comparable to or exceeding that of humans in the next 20 years, experts forecast that rapid progress in the field of specialized AI will continue, with machines reaching and exceeding human performance on an increasing number of tasks.

One of the most important issues raised by AI is its impact on jobs and the economy. The report recommends that the White House convene a study on automation and the economy, resulting in a follow-on public report that will be released by the end of this year.

In the coming years, AI will continue contributing to economic growth and will be a valuable tool for improving the world in fields as diverse as health care, transportation, the environment, criminal justice, and economic inclusion. The Administration believes that it is critical that industry, civil society, and government work together to develop the positive aspects of the technology, manage its risks and challenges, and ensure that everyone has the opportunity to help in building an AI-enhanced society and to participate in its benefits.

To read the Future of AI report, click here.And tune-in for the White House Frontiers Conference on October 13 for more on the #FutureofAI, including discussions with leading experts on harnessing the potential of AI, including data science, machine learning, automation, and robotics to engage and benefit all Americans. Watch the conference live and learn more at: http://www.frontiersconference.org.

Ed Felten is a Deputy U.S Chief Technology Officer in the White House Office of Science and Technology Policy. Terah Lyons is a Policy Advisor to the U.S. Chief Technology Officer in White House Office of Science and Technology Policy.

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report on the future of artificial intelligence - whitehouse.gov

This post was adapted from a presentation at an AI Now symposium held on July 10 at the MIT Media Lab. AI Now is a new initiative working, in partnership with the ACLU, to explore the social and economic implications of artificial intelligence.

It seems to me that this is an auspicious moment for a conversation about rights and liberties in an automated world, for at least two reasons.

The first is that theres still time to get this right. We can still have a substantial impact on the legal and policy debates that will shape development and deployment of automated technologies in our everyday lives.

The second reason is Donald Trump. The democratic stress test of the Trump presidency has gotten everyones attention. Its now much harder to believe, as Eric Schmidt once assured us, that technology will solve all the worlds problems. Technologists who have grown used to saying that they have no interest in politics have realized, I believe, that politics is very interested in them.

By contrast, consider how, over the last two decades, the internet came to become the engine of a surveillance economy.

Silicon Valleys apostles of innovation managed to exempt the internet economy from the standard consumer protections provided by other industrialized democracies by arguing successfully that it was too early for government regulation: It would stifle innovation. In almost the same breath, they told us that it was also too late for regulation: It would break the internet.

And by the time significant numbers of people came to understand that maybe they hadnt gotten such a good deal, the dominant business model had become so entrenched that meaningful reforms will now require Herculean political efforts.

How smart can our smart cameras be if the humans programming them are this dumb?

When we place innovation within or atop a normative hierarchy, we end up with a world that reflects private interests rather than public values.

So if we shouldnt just trust the technologists and the corporations and governments that employ the vast majority of them then what should be our north star?

Liberty, equality, and fairness are the defining values of a constitutional democracy. Each is threatened by increased automation unconstrained by strong legal protections.

Liberty is threatened when the architecture of surveillance that weve already constructed is trained, or trains itself, to track us comprehensively and to draw conclusions based on our public behavior patterns.

Equality is threatened when automated decision-making mirrors the unequal world that we already live in, replicating biased outcomes under a cloak of technological impartiality.

And basic fairness, what lawyers call due process, is threatened when enormously consequential decisions affecting our lives whether well be released from prison, or approved for a home loan, or offered a job are generated by proprietary systems that dont allow us to scrutinize their methodologies and meaningfully push back against unjust outcomes.

Since my own work is on surveillance, Im going to devote my limited time to that issue.

When we think about the interplay between automated technologies and our surveillance society, what kinds of harms to core values should we be principally concerned about?

Let me mention just a few.

When we program our surveillance systems to identify suspicious behaviors, what will be our metrics for defining suspicious?

This is a brochure about the 8 signs of terrorism that I picked up in an upstate New York rest area. (My personal favorite is number 7: Putting people into position and moving them around without actually committing a terrorist act.)

How smart can our smart cameras be if the humans programming them are this dumb?

And of course, this means that many people are going to be logged into systems that will, in turn, subject them to coercive state interventions.

But we shouldnt just be concerned about false positives. If we worry only about how error-prone these systems are, then more accurate surveillance systems will be seen as the solution to the problem.

Im at least as worried about a world in which all of my public movements are tracked, logged, and analyzed accurately.

Bruce Schneier likes to say: Think about how you feel when a police car is driving alongside you. Now imagine feeling that way all the time.

Theres a very real risk, as my colleague Jay Stanley has warned, that pervasive automated surveillance will:

turn[] us into quivering, neurotic beings living in a psychologically oppressive world in which were constantly aware that our every smallest move is being charted, measured, and evaluated against the like actions of millions of other peopleand then used to judge us in unpredictable ways.

I also worry that in our eagerness to make the world quantifiable, we may find ourselves offering the wrong answers to the wrong questions.

The wrong answers because extremely remote events like terrorism dont track accurately into hard predictive categories.

And the wrong question because it doesnt even matter what the color is: Once we adopt this threat-level framework, we say that terrorism is an issue of paramount national importance even though that is a highly questionable proposition.

Think about how you feel when a police car is driving alongside you. Now imagine feeling that way all the time.

The question becomes how alarmed should we be? rather than should we be alarmed at all?

And once were trapped in this framework, the only remaining question will be how accurate and effective our surveillance machinery is not whether we should be constructing and deploying it in the first place.

If were serious about protecting liberty, equality, and fairness in a world of rapid technological change, we have to recognize that in some contexts, inefficiencies can be a feature, not a bug.

Consider these words written over 200 years ago. The Bill of Rights is an anti-efficiency manifesto. It was created to add friction to the exercise of state power.

The Fourth Amendment: Government cant effect a search or seizure without a warrant supported by probable cause of wrongdoing.

The Fifth Amendment: Government cant force people to be witnesses against themselves; it cant take their freedom or their property without fair process; it doesnt get two bites at the apple.

The Sixth Amendment: Everyone gets a lawyer, and a public trial by jury, and can confront any evidence against them.

The Eighth Amendment: Punishments cant be cruel, and bail cant be excessive.

This document reflects a very deep mistrust of aggregated power.

If we want to preserve our fundamental human rights in the world that aggregated computing power is going to create, I would suggest that mistrust should remain one of our touchstones.

Go here to see the original:

Artificial Intelligence at Any Cost Is a Recipe for Tyranny - ACLU (blog)

News healthcare

The Ethereum blockchain will be used to power deep learning artificial intelligence bots that can answer patient inquiries.

On August 24, 2017, artificial intelligence (AI) and blockchain startup doc.ai Incorporated released details of its language processing platform that timestamps datasets using an Ethereum blockchain-based system and AI tools.

The project is the result of collaboration between developers from Stanford and Cambridge Universities. According to the announcement, doc.ai can improve patient care by "creating the most advanced natural language dialog system that generates insights from combined medical data." The platform is built on the Ethereum blockchain, allowing for decentralized timestamping of datasets, and makes use of AI that is capable of deep learning on the edge of networks (a term for data processing near the data source on the network, thus reducing communication bandwidth between sensors and the datacenter) or on a mobile device. The AI can provide a 24-hour resource to patients by answering their questions specific to their personal health data and their physician's analysis. In addition, the AI uses the cumulative information gathered to learn about the patient's needs and to customize itself accordingly.

doc.ai plans to introduce, over the next year, three natural language processing models called Robo-Genomics, Robo-Hematology, and Robo-Anatomics, which will be made available to the medical industry. As described on doc.ais website, Robo-Genomics will provide users with decision support. Robo-Hematology is designed to answer any question on 400+ blood biomarkers. Robo-Anatomics uses a patent-pending Selfie2BMI module that uses a Deep Neural Network to predict a number of anatomic features from a photo of a face.

Walter De Brouwer, founder and chief executive officer of doc.ai, commented on the attributes of the platform:

"We are making it possible for lab tests to converse directly with patients by leveraging advanced artificial intelligence, medical data forensics, and the decentralized blockchain. We envision extensive possibilities for the use of this technology by doctors, patients, and medical institutions."

De Brouwer explained to ETHNews doc.ais motivation for using blockchain technology:

In an announcement on July 24, 2017, Deloitte Life Sciences and Healthcare and doc.ai will be working together to test the use of Robo-Hematology. Deloittes Rajeev Ronanki commented that "Platforms like these open new possibilities for patients and medical organizations by providing more personalized, intelligent healthcare. We are excited to collaborate with doc.ai and to be at the forefront of this technology."

The transition to AI and the Ethereum blockchain as a backbone for patient care is a significant step forward for the nascent technologies. We are very excited to bring these three worlds together in one: AI, blockchain and healthcare, said De Brouwer.

Jeremy Nation is a writer living in Los Angeles with interests in technology, human rights, and cuisine. He is a full time staff writer for ETHNews and holds value in Ether.

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Doc.ai's Ethereum Blockchain-Based Medical Solutions Bring Artificial Intelligence To Healthcare - ETHNews

Dive Brief:

CB Insights is putting the numbers behind what industry insiders have already been noticing: Artificial intelligence is hot in healthcare right now.

From a provider standpoint, many are just beginning to explore the possibilities and see how such capabilities can fit into the care delivery setting. Many providers are looking into patient readmissions as one area for a use case.

However, due to the infancy of the current clinical use cases, artificial intelligence receives a fair amount of skepticism in the healthcare space. For one, "artificial intelligence" has become a catch-all shorthand for some disparate topics such as predictive analytics and machine learning. CB defined artificial intelligence in the space as "startups leveraging machine learning algorithms to reduce drug discovery times, provide virtual assistance to patients or improve the accuracy of medical imaging and diagnostic procedures, among other applications."

Another issue that adds to the skepticism is the potential costs of new technology. Providers have felt burned before because of high-cost EHR systems that helped contribute to administrative burden across physician offices and health systems nationwide.

Still, companies are making a play for the space, as it's a market that's expected to grow.

[Hospitals] are very excited about [artificial intelligence] and are actually very bold about it, which is surprising because hospital systems dont tend to be usually bold.But theyre making investments, James Golden, managing director of PwC Health Advisory, told Healthcare Dive at HIMSS17 in February.This stuff is coming. Its coming fast. Its being viewed as a research project. In the next few years, it is not going to be a research project."

See the rest here:

Artificial intelligence experiencing record deals in healthcare - Healthcare Dive

As Artificial Intelligence (AI) and Machine Learning (ML) get set to take a giant leap in improving day-to-day life, the key is to democratise these new-age tools for all and benefit the communities of developers, users and enterprise customers, a top Google executive said here on Wednesday.

The concept of AI and ML came into existence long back but with the vast availability of data today, sectors like healthcare, banking and retail are adopting the technologies at a faster pace than before.

Google, a pioneer in AI, has been focusing on four key components computing, algorithms, data and expertise to organise all the data and make it accessible.

What it entails to democratise AI, we focus on these four core components. Computing is the backbone of AI technology. Google as a company has always been at the forefront of computing AI, Fei-Fei Li, Chief Scientist of Google Cloud AI and ML, told reporters during a media interaction here.

We want to make it all accessible to our customers, added Li, also Professor of Computer Science at Stanford University in the US.

Earlier this year, Google announced the second-generation Tensor Processing Units (TPUs) (now called the Cloud TPU) at the annual Google I/O event in the US.

We announced the Cloud TPU the second-generation of our processing unit and our intention is to make it available via Google Cloud, the top executive added.

The company offers computing power including graphics processing unit (GPUs), central processing units (CPUs) and tensor processing units (TPUs) to power machine learning.

The Shazam is one such app that uses GPUs on Google Cloud.

The application uses GPUs to match snippets of user audio fingerprints against their catalogue of over 40 million songs.

That means when a user Shazams a song, the algorithm uses GPUs to search the database until it finds a match for the audio snippet the person has recorded on the phone.

Li, however, said that AI still remains among the most complex and new fields.

To make it accessible for businesses and customers where they are required to gain access to the right tools, whether it is a ML library like TensorFlow or tapping into pre-trained models via API, Li added.

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We want to democratise artificial intelligence: Google - YourStory.com