Tag Archives: US White House

Socially responsible AI—it’s time says University of Manchester (UK) researchers

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A May 10, 2018 news item on ScienceDaily describes a report on the ‘fourth industrial revolution’ being released by the University of Manchester,

The development of new Artificial Intelligence (AI) technology is often subject to bias, and the resulting systems can be discriminatory, meaning more should be done by policymakers to ensure its development is democratic and socially responsible.

This is according to Dr Barbara Ribeiro of Manchester Institute of Innovation Research at The University of Manchester, in On AI and Robotics: Developing policy for the Fourth Industrial Revolution, a new policy report on the role of AI and Robotics in society, being published today [May 10, 2018].

Interestingly, the US White House is hosting a summit on AI today, May 10, 2018, according to a May 8, 2018 article by Danny Crichton for TechCrunch (Note: Links have been removed),

…

Now, it appears the White House itself is getting involved in bringing together key American stakeholders to discuss AI and those opportunities and challenges. …

Among the confirmed guests are Facebook’s Jerome Pesenti, Amazon’s Rohit Prasad, and Intel’s CEO Brian Krzanich. While the event has many tech companies present, a total of 38 companies are expected to be in attendance including United Airlines and Ford.

AI policy has been top-of-mind for many policymakers around the world. French President Emmanuel Macron has announced a comprehensive national AI strategy, as has Canada, which has put together a research fund and a set of programs to attempt to build on the success of notable local AI researchers such as University of Toronto professor George Hinton, who is a major figure in deep learning.

But it is China that has increasingly drawn the attention and concern of U.S. policymakers. The country and its venture capitalists are outlaying billions of dollars to invest in the AI industry, and it has made leading in artificial intelligence one of the nation’s top priorities through its Made in China 2025 program and other reports. …

In comparison, the United States has been remarkably uncoordinated when it comes to AI. …

That lack of engagement from policymakers has been fine — after all, the United States is the world leader in AI research. But with other nations pouring resources and talent into the space, DC policymakers are worried that the U.S. could suddenly find itself behind the frontier of research in the space, with particular repercussions for the defense industry.

…

Interesting contrast: do we take time to consider the implications or do we engage in a race?

While it’s becoming fashionable to dismiss dichotomous questions of this nature, the two approaches (competition and reflection) are not that compatible and it does seem to be an either/or proposition.

A May 10, 2018 University of Manchester press release (also on EurekAlert), which originated the news item, expands on the theme of responsibility and AI,

Dr Ribeiro adds because investment into AI will essentially be paid for by tax-payers in the long-term, policymakers need to make sure that the benefits of such technologies are fairly distributed throughout society.

She says: “Ensuring social justice in AI development is essential. AI technologies rely on big data and the use of algorithms, which influence decision-making in public life and on matters such as social welfare, public safety and urban planning.”

“In these ‘data-driven’ decision-making processes some social groups may be excluded, either because they lack access to devices necessary to participate or because the selected datasets do not consider the needs, preferences and interests of marginalised and disadvantaged people.”

On AI and Robotics: Developing policy for the Fourth Industrial Revolution is a comprehensive report written, developed and published by Policy@Manchester with leading experts and academics from across the University.

The publication is designed to help employers, regulators and policymakers understand the potential effects of AI in areas such as industry, healthcare, research and international policy.

However, the report doesn’t just focus on AI. It also looks at robotics, explaining the differences and similarities between the two separate areas of research and development (R&D) and the challenges policymakers face with each.

Professor Anna Scaife, Co-Director of the University’s Policy@Manchester team, explains: “Although the challenges that companies and policymakers are facing with respect to AI and robotic systems are similar in many ways, these are two entirely separate technologies – something which is often misunderstood, not just by the general public, but policymakers and employers too. This is something that has to be addressed.”

One particular area the report highlights where robotics can have a positive impact is in the world of hazardous working environments, such a nuclear decommissioning and clean-up.

Professor Barry Lennox, Professor of Applied Control and Head of the UOM Robotics Group, adds: “The transfer of robotics technology into industry, and in particular the nuclear industry, requires cultural and societal changes as well as technological advances.

“It is really important that regulators are aware of what robotic technology is and is not capable of doing today, as well as understanding what the technology might be capable of doing over the next -5 years.”

The report also highlights the importance of big data and AI in healthcare, for example in the fight against antimicrobial resistance (AMR).

Lord Jim O’Neill, Honorary Professor of Economics at The University of Manchester and Chair of the Review on Antimicrobial Resistance explains: “An important example of this is the international effort to limit the spread of antimicrobial resistance (AMR). The AMR Review gave 27 specific recommendations covering 10 broad areas, which became known as the ‘10 Commandments’.

“All 10 are necessary, and none are sufficient on their own, but if there is one that I find myself increasingly believing is a permanent game-changer, it is state of the art diagnostics. We need a ‘Google for doctors’ to reduce the rate of over prescription.”

The versatile nature of AI and robotics is leading many experts to predict that the technologies will have a significant impact on a wide variety of fields in the coming years. Policy@Manchester hopes that the On AI and Robotics report will contribute to helping policymakers, industry stakeholders and regulators better understand the range of issues they will face as the technologies play ever greater roles in our everyday lives.

As far as I can tell, the report has been designed for online viewing only. There are none of the markers (imprint date, publisher, etc.) that I expect to see on a print document. There is no bibliography or list of references but there are links to outside sources throughout the document.

It’s an interesting approach to publishing a report that calls for social justice, especially since the issue of ‘trust’ is increasingly being emphasized where all AI is concerned. With regard to this report, I’m not sure I can trust it. With a print document or a PDF I have markers. I can examine the index, the bibliography, etc. and determine if this material has covered the subject area with reference to well known authorities. It’s much harder to do that with this report. As well, this ‘souped up’ document also looks like it might be easy to change something without my knowledge. With a print or PDF version, I can compare the documents but not with this one.

US White House’s grand computing challenge could mean a boost for research into artificial intelligence and brains

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An Oct. 20, 2015 posting by Lynn Bergeson on Nanotechnology Now announces a US White House challenge incorporating nanotechnology, computing, and brain research (Note: A link has been removed),

On October 20, 2015, the White House announced a grand challenge to develop transformational computing capabilities by combining innovations in multiple scientific disciplines. See https://www.whitehouse.gov/blog/2015/10/15/nanotechnology-inspired-grand-challenge-future-computing The Office of Science and Technology Policy (OSTP) states that, after considering over 100 responses to its June 17, 2015, request for information, it “is excited to announce the following grand challenge that addresses three Administration priorities — the National Nanotechnology Initiative, the National Strategic Computing Initiative (NSCI), and the BRAIN initiative.” The grand challenge is to “[c]reate a new type of computer that can proactively interpret and learn from data, solve unfamiliar problems using what it has learned, and operate with the energy efficiency of the human brain.”

Here’s where the Oct. 20, 2015 posting, which originated the news item, by Lloyd Whitman, Randy Bryant, and Tom Kalil for the US White House blog gets interesting,

 While it continues to be a national priority to advance conventional digital computing—which has been the engine of the information technology revolution—current technology falls far short of the human brain in terms of both the brain’s sensing and problem-solving abilities and its low power consumption. Many experts predict that fundamental physical limitations will prevent transistor technology from ever matching these twin characteristics. We are therefore challenging the nanotechnology and computer science communities to look beyond the decades-old approach to computing based on the Von Neumann architecture as implemented with transistor-based processors, and chart a new path that will continue the rapid pace of innovation beyond the next decade.

There are growing problems facing the Nation that the new computing capabilities envisioned in this challenge might address, from delivering individualized treatments for disease, to allowing advanced robots to work safely alongside people, to proactively identifying and blocking cyber intrusions. To meet this challenge, major breakthroughs are needed not only in the basic devices that store and process information and the amount of energy they require, but in the way a computer analyzes images, sounds, and patterns; interprets and learns from data; and identifies and solves problems. [emphases mine]

Many of these breakthroughs will require new kinds of nanoscale devices and materials integrated into three-dimensional systems and may take a decade or more to achieve. These nanotechnology innovations will have to be developed in close coordination with new computer architectures, and will likely be informed by our growing understanding of the brain—a remarkable, fault-tolerant system that consumes less power than an incandescent light bulb.

Recent progress in developing novel, low-power methods of sensing and computation—including neuromorphic, magneto-electronic, and analog systems—combined with dramatic advances in neuroscience and cognitive sciences, lead us to believe that this ambitious challenge is now within our reach. …

This is the first time I’ve come across anything that publicly links the BRAIN initiative to computing, artificial intelligence, and artificial brains. (For my own sake, I make an arbitrary distinction between algorithms [artificial intelligence] and devices that simulate neural plasticity [artificial brains].)The emphasis in the past has always been on new strategies for dealing with Parkinson’s and other neurological diseases and conditions.