AI in Military

Putin: Leader in artificial intelligence will rule world

Putin, speaking Friday at a meeting with students, said the development of AI raises “colossal opportunities and threats that are difficult to predict now.”

[He] warned that “it would be strongly undesirable if someone wins a monopolist position” and promised that Russia would be ready to share its know-how in artificial intelligence with other nations.

The Russian leader predicted that future wars will be fought by drones, and “when one party’s drones are destroyed by drones of another, it will have no other choice but to surrender.”

Source: Washington Post

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Teaching an Algorithm to Understand Right and Wrong

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Aristotle states that it is a fact that “all knowledge and every pursuit aims at some good,” but then continues, “What then do we mean by the good?” That, in essence, encapsulates the ethical dilemma.

We all agree that we should be good and just, but it’s much harder to decide what that entails.

“We need to decide to what extent the legal principles that we use to regulate humans can be used for machines. There is a great potential for machines to alert us to bias. We need to not only train our algorithms but also be open to the possibility that they can teach us about ourselves.” – Francesca Rossi, an AI researcher at IBM

Since Aristotle’s time, the questions he raised have been continually discussed and debated. 

Today, as we enter a “cognitive era” of thinking machines, the problem of what should guide our actions is gaining newfound importance. If we find it so difficult to denote the principles by which a person should act justly and wisely, then how are we to encode them within the artificial intelligences we are creating? It is a question that we need to come up with answers for soon.

Cultural Norms vs. Moral Values

Another issue that we will have to contend with is that we will have to decide not only what ethical principles to encode in artificial intelligences but also how they are coded. As noted above, for the most part, “Thou shalt not kill” is a strict principle. Other than a few rare cases, such as the Secret Service or a soldier, it’s more like a preference that is greatly affected by context.

What makes one thing a moral value and another a cultural norm? Well, that’s a tough question for even the most-lauded human ethicists, but we will need to code those decisions into our algorithms. In some cases, there will be strict principles; in others, merely preferences based on context. For some tasks, algorithms will need to be coded differently according to what jurisdiction they operate in.

Setting a Higher Standard

Most AI experts I’ve spoken to think that we will need to set higher moral standards for artificial intelligences than we do for humans.

Major industry players, such as Google, IBM, Amazon, and Facebook, recently set up a partnership to create an open platform between leading AI companies and stakeholders in academia, government, and industry to advance understanding and promote best practices. Yet that is merely a starting point.

Source: Harvard Business Review

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China has now eclipsed U.S. in AI research

As more industries and policymakers awaken to the benefits of machine learning, two countries appear to be pulling away in the research race. The results will probably have significant implications for the future of AI.

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What’s striking about it is that although the United States was an early leader on deep-learning research, China has effectively eclipsed it in terms of the number of papers published annually on the subject. The rate of increase is remarkably steep, reflecting how quickly China’s research priorities have shifted.

quality-deep-learning-researchThe quality of China’s research is also striking. The chart below narrows the research to include only those papers that were cited at least once by other researchers, an indication that the papers were influential in the field.

Compared with other countries, the United States and China are spending tremendous research attention on deep learning. But, according to the White House, the United States is not investing nearly enough in basic research.

“Current levels of R&D spending are half to one-quarter of the level of R&D investment that would produce the optimal level of economic growth,”
a companion report published this week by the Obama administration finds.

Source: The Washington Post

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CIA using deep learning neural networks to predict social unrest

man-looking-big-data-analytics-ciaIn October 2015, the CIA opened the Directorate for Digital Innovation in order to “accelerate the infusion of advanced digital and cyber capabilities” – the first new directorate to be created by the government agency since 1963.

“What we’re trying to do within a unit of my directorate is leverage what we know from social sciences on the development of instability, coups and financial instability, and take what we know from the past six or seven decades and leverage what is becoming the instrumentation of the globe.”

In fact, over the summer of 2016, the CIA found the intelligence provided by the neural networks was so useful that it provided the agency with a “tremendous advantage” when dealing with situations …

Source: IBTimes

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Should we be afraid of AI? The military wants a real answer by the end of 2015

The Military’s New Year’s Resolution for Artificial Intelligence

In November, Undersecretary of Defense Frank Kendall quietly issued a memo to the Defense Science Board that could go on to play a role in history.

defense-large for blog on socializing AIThe calls for a new study that  would “identify the science, engineering, and policy problems that must be solved to permit greater operational use of autonomy across all war-fighting domains…Emphasis will be given to exploration of the bounds-both technological and social-that limit the use of autonomy across a wide range of military operations. The study will ask questions such as: What activities cannot today be performed autonomously? When is human intervention required? What limits the use of autonomy? How might we overcome those limits and expand the use of autonomy in the near term as well as over the next 2 decades?”

A Defense Department official very close to the effort framed the request more simply. “We want a real roadmap for autonomy” he told Defense One. What does that mean, and how would a “real roadmap” influence decision-making in the years ahead? One outcome of the Defense Science Board 2015 Summer Study on Autonomy, assuming the results are eventually made public, is that the report’s findings could refute or confirm some of our worst fears about the future of artificial intelligence.

Source: Defense One

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