FutureSource



FutureSource

The Atlantic Council’s Science and Policy Fellow presented early-stage research on how machine-learning techniques can help decision makers better understand the public’s perception of new technologies, with significant implications for future policymaking.

Dr. Conrad Tucker, an associate professor of computer science and engineering at the Pennsylvania State University, and a science and policy fellow in the Brent Scowcroft Center on International Security, showcased his current research project, Technology Phobia Readiness Condition (TEPHCON), during the second international InfoSymbiotics/DDDAS conference at the Massachusetts Institute of Technology.

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A gene-editing technology that has already shown tremendous medical breakthroughs has some wondering if cancer and HIV can be defeated by genetic engineering. But despite the optimistic headlines, the technique known as CRISPR is also becoming an emerging international security threat. CRISPR could someday enable U.S. adversaries to genetically-engineer bioweapons or even create “super soldiers” to dominate future battlefields.

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Not even the most United Kingdom-sceptic European could have imagined that just a year after the Brexit referendum Britain would appear to be teetering on the brink of disorder. Indeed, over the past year the group behind this scenario planning / train crash project analysed the various possibilities of danger to both the British state and the union of the United Kingdom; but even four months ago the dangers seemed no more than potentials, each contingent on quite a number of other causalities. These have largely been swept away, for three core reasons.

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Truth: What is it? Will societies ever come to a consensus on how to define it? If we cannot, how can we ever design machines that learn from it? A very important concept in the field of machine learning is a concept of “ground truth”. The Oxford Dictionary defines ground truth to be “A fundamental truth. Also: the real or underlying facts; information that has been checked or facts that have been collected at source.” From this definition, we see the term “fundamental”, which immediately sets the stage for controversy surrounding the definition of the term “truth”, for if truth were indeed pure and absolute, why the need for adjectives such as “fundamental” or “ground”? However, the focus of this article is not to philosophize about the semantics surrounding the term truth. Instead, this article seeks to explore the potential implications relating to i) who provides ground truth data for machines to learn from, ii) should “majority rule” be the policy decision on what is considered “truth”?

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The scourge of global corruption has been well documented, but less is known about how rampant graft affects international security. Democratic capacity-building efforts, an important tool in fighting insurgencies in Iraq and Afghanistan, have been hobbled by corruption for over a decade. States with violent extremist groups are often made even more unstable when the perception of corruption leads to public unrest and protests.

Through an investigation of this link between corruption and international security, it was found that online good governance initiatives in the West have also been implemented in fragile states and in the developing world. However, it may be too soon to determine whether government transparency technology can score decisive victories against corruption.

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In a fireside chat hosted by the Atlantic Council’s Foresight, Strategy, and Risks Initiative on June 14, Financial Times columnist and commentator Edward Luce discussed the many challenges facing liberal democracies and the impact these challenges have on Western hegemony and the state of the liberal international order at large.

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This blog is the first in a series exploring the implications of different policies on the development and deployment of artificial intelligence, machine learning, and cognitive systems.

The term “cognition” is defined as “of, relating to, being, or involving conscious intellectual activity”.1 Our world is surrounded by cognitive organisms that range in complexity from an ant to the most intellectually-capable cognitive organism that is known today – a human. A fundamental characteristic of cognitive organisms is their ability to form higher-level abstractions of cognition that mimic or surpass their individual levels of cognition.2 A cognitive system is a human-made system that is able to interact with their human counterparts and understand human expression mechanisms that are primarily delivered via visual, audial, and textual communication.3 For clarity, this article defines cognitive organisms as being nature made, and cognitive systems as being human-made (…for now). By understanding human tendencies, cognitive systems should therefore be able to anticipate human intent and either be prepared to respond instantly, or be proactive and respond preemptively.

Given the transient nature of humans, cognitive systems must be able to evolve their interactions with their human counterparts. For that to happen, they must learn from new input data, and augment their decision making models based on feedback from both humans and their environments. The need to learn about their environment through data presents a fundamental question; i.e., how do policy decisions pertaining to data acquisition, transmission, storage, and communication impact the ability of cognitive systems to learn and achieve their operational objectives?

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On June 8, the United Kingdom will vote in its second general election in just over two years. The last election in May 2015 resulted in a Conservative government, and led to the June 2016 national referendum on Britain’s membership in the European Union. Following the result in favor of Brexit, Prime Minister David Cameron—the leader of the unsuccessful Remain campaign—resigned, and former Home Secretary Theresa May took office.

May’s leadership has been dominated by Britain’s departure from the EU, and the implications for the country. In April, facing domestic opposition to this approach, including legal challenges, she called a snap general election. She argued this would help Britain have a stronger negotiating position in the talks with other EU member states, and would give her a clear mandate to go ahead with leaving the EU. Although Brexit is an important issue in the election, however, it is not the sole focus of the campaign. Health, education, welfare, immigration, and the environment feature heavily in the manifestos of the major parties.

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Conservative Prime Minister Theresa May and Labour leader Jeremy Corbyn, the front-runners in the British general election, have endured a volatile race punctuated by two terror attacks that have rocked Britain. With campaigning suspended twice after each incident and British pollsters’ failure to predict Brexit, FutureSource queried a data science firm to get its reading on the election that has challenged conventional forecasters.

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To use an old Thatcherite adage, the United States, United Kingdom and European Union are all living in cloud cuckoo land, seemingly vastly underestimating the medium- to long-term effects of Brexit: a dramatically weakened UK, an undermined EU, and fragmented transatlantic relations. Put another way: the transatlantic rift that has clearly already opened over NATO and now the US withdrawal from the Paris Climate Agreement could be just the start—made far worse by a bad Brexit.

Over the past few months, a group of Brits in Brussels has been working unofficially on Brexit scenario planning, attempting to delve into what the UK, EU, and transatlantic relations will be facing with Brexit. Laid out in such detail—which we will do in the next few weeks—is a veritable catalogue of daunting mountain-size challenges. While it’s true the UK faces some of the biggest knots to disentangle, the EU and transatlantic relations won’t be spared. Viewed all together, it is clear that breezy statements such as “Brexit means Brexit” hide a veritable catalogue of hurdles and hardships, mostly on the British side, but also for the EU.

This is the first of four blogs, examining key aspects of the divorce—in line with four core scenarios we believe possible, each of which we feel to be a train crash.

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