- August 15, 2017
- Posted by: Trevor Jones
- Category: Big Data, Mapping, and Technology
Until recently, methods to identify global risks with data have been misunderstood and underutilized. Using data visualization and artificial intelligence to provide predictive analytics is now possible because of advances in both technology and new understandings of threat and risk. The resulting product helps NGO’s, businesses and governments create conditions for people to live secure, healthy, and fulfilled lives.
Global risks have become increasingly complex for organizations due to rapid changes in society and technology. These challenges are further complicated by worldwide issues like climate change, mass migration, food and water security. Threats to business and government are now stacked in complex ways. Easy visualizations are needed to help decision-makers cut through the noise.
Complex Global Challenges
Businesses and governments alike are increasingly concerned about issues of disruption and violence. Conditions forglobal conflict are now more volatile, due to complex interactions between society, technology, the environment, and political factors. The immensity of these global challenges affects organizations in many ways. Supply chains are disrupted, global trade becomes distressed, and organizational continuity is challenged.
Although conflict and threat are on the rise, and made worse by complex factors such as climate change and human trafficking, the world has made incredible strides in technology. While the capability wrought by advances computing and artificial intelligence (A.I.) were thought to be vast, it has been un-clear how these faculties could begin assessing such dire challenges. Until now.
To understand how this is possible, it is important to understand how A.I. capabilities have evolved in recent years.
We may think of A.I. machine learning applications such as Siri and Alexa, or the autopilot systems within self-driving cars. These incorporate aspects of A.I., but the meaning of ‘artificial intelligence’ is far more complex. Rather than teaching rules to computers, as humans have done since their invention, A.I. is capable of learning from computation, and adjusting programming accordingly. Algorithms adapt and adjust dynamically based upon changes the human behavior it encounters. Our understanding of conflict has also changed, and quantitative analysis of instability and global conflict is not a new concept. Researchers have sought for years to develop quantitative models combined with qualitative insights to predict security concerns, to little avail. Implementing A.I. within this process opens innovative doors for global capability. By learning from deviation from standard modeling practices, A.I. systems begin to learn when and how emergent trends lead to terroristattacks, social unrest, or supply chain disruption. These are just a few examples of the scenarios that can be explored.
Data is quite literally all around us, and is growing in complexity and size due to sensors connected to the Internet of Things (IoT). The problem has always been, and will continue to be, what to do with such a vast amount of information.
“Computer power is growing,
algorithms and A.I. models
are becoming more
sophisticated, and, perhaps
most important of all, the
world is generating once unimaginable
volumes of the
fuel that powers A.I. data.
Billions of gigabytes every
day, collected by networked
devices ranging from web
browsers to turbine sensors.”
Selected Risk Types
The following is a sample of the type of risk that can be visualized:
-Political: Policy changes that affect organizational continuity stemming from elections, riots, public unrest and abrupt legislative changes.
-Economics Tariffs and non-tariff barriers, compliance, legal and logistic risks.
-Social: Reputational risk, populism, fake-news.
-Environmental: Climate change, pollution, soil salinity, drought, deforestation.
-Human Life: Food insecurity, water, insecurity, human rights abuses, and human trafficking.
-Security: Terrorism, Counter Violent, Extremism Sentiment Monitoring, threats to people, property and infrastructure.
Data Visualization and A.I. Solutions
Most existing work in A.I. and risk has been done in the context of cyber threats and enterprise security. While this is certainly a useful part of understanding how companies stay safe, it underestimates the capability of combinations of systems to tackle more complex issues.
For example, the widespread use of social media provides an ideal source for gathering context and sentiment. Natural language processing can be used to assimilate and compile the sentiment of social messaging. One can imagine how useful this tool might be to supply chain procurement managers, or chief risk officers. When factors like drought cause social unrest, they in turn disrupt supply chains and put human lives in danger. The complexity of this new landscape for risk managers and analysts requires methods that strengthen human analysis.
A.I. shows promise in solving this issue by learning baseline facts about people, places, and things. Learning by artificial intelligence occurs by combining readily accessible, structured and unstructured data inputs. Subsequently, the A.I. learns the nuances of the sentiment being expressed on social media by observing deviations from the baseline, and new methods of analysis are derived. The insights that result are of high value to those responsible for mitigating risk inside an organization.
Data Source Categories
- Internal Organization Data
2. Open Source Political Risk, Economic, Other External Data
3. Social Media Sentiment and Web Scraping
Sample A.I. Solutions
-Supply Chain Procurement Officers
make decisions based on the rapid
visualization of vast amounts of
-Global Operations Directors see
granular detail around local
sentiment and risk.
-The Intelligence Community
assesses emerging threats by rapidly
compiling and coordinating the
analysis of many hundreds of
thousands of documents at once,
like speeches, newspapers and press
-Humanitarian Organizations quickly
understand the drivers of local
grievances by monitoring social
media sentiment and food and
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“ground truth” analysis and helping clients mitigate risk. Based on insightful and diverse
analytical models and social media intelligence, Lynx illuminates risk and opportunities. Lynx
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promoting human dignity and security.
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