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Internal Audit, Risk, Business & Technology Consulting FPO As organizations continue to evolve their risk governance practices, focused and relevant information about emerging risks is at a premium. The objective of Protiviti’s PreView newsletter is to provide an input for these efforts as companies focus on risks that are developing in the market. We discuss emergent issues and look back at topics we’ve covered to help organizations understand how these risks are evolving and anticipate their potential ramifications. As you review the topics in this issue, we encourage you to think about your organization and ask probing questions: How will these risks affect us? What should we do now to prepare? Is there an opportunity we should pursue? Our framework for evaluation of risks is rooted in the global risk categories designed by the World Economic Forum. Throughout this series, we use these categories to classify macro-level topics and the challenges they present. Inside This Issue 02 Nanotechnology: Tiny Particles, Big Shifts 05 The Global Water Crisis in Perspective 08 Artificial Intelligence: The Effects of Machine Learning 11 On the Radar 12 Where to Learn More 13 Continuing the Conversation EMERGING RISKS Economic Technological Environmental Societal Geopolitical PreView Protiviti’s View on Emerging Risks FEBRUARY 2017

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Page 1: PreView: Protiviti's View on Emerging Risksthe future of the technology. Among them: ... • The environment — The energy industry could experience huge advantages from applications

Internal Audit, Risk, Business & Technology Consulting

FPO

As organizations continue to evolve their risk governance practices, focused and relevant

information about emerging risks is at a premium. The objective of Protiviti’s PreView newsletter is

to provide an input for these efforts as companies focus on risks that are developing in the market.

We discuss emergent issues and look back at topics we’ve covered to help organizations understand

how these risks are evolving and anticipate their potential ramifications.

As you review the topics in this issue, we encourage you to think about your organization and

ask probing questions: How will these risks affect us? What should we do now to prepare? Is there an

opportunity we should pursue?

Our framework for evaluation of risks is rooted in the global risk categories designed by the World

Economic Forum. Throughout this series, we use these categories to classify macro-level topics and

the challenges they present.

Inside This Issue

02 Nanotechnology: Tiny Particles, Big Shifts

05 The Global Water Crisis in Perspective

08Artificial Intelligence: The Effects of Machine Learning

11 On the Radar

12 Where to Learn More

13 Continuing the Conversation

EMERGING RISKS

EconomicTechnological

Environmental

Societal Geopolitical

PreViewProtiviti’s View on Emerging Risks

FEBRUARY 2017

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Emerging Risk Categories: Technological, Environmental, Societal, Economic Industries Impacted: Government, Financial Services, Technology, Consumer Products & Services, Agriculture, Healthcare & Life Sciences, Industrial Products & Services

Nanotechnology involves the ability to see,

control and manufacture materials and devices

on the scale of individual atoms and molecules,

and even molecular subunits (supramolecular

level). Since everything on the planet consists

of atoms, the application of nanotechnology is

far-reaching. As scientists and engineers find

ways to manipulate materials at the nanoscale

to take advantage of enhanced properties, such

as higher strength or lighter weight, many

possible applications suggest themselves across

multiple industries.

Nanoscience has been evolving since 1959,

when physicist Richard Feynman introduced

the concept of manipulating atoms on an

infinitesimal scale of 10-9 meters (aka

nanoscale). Since then, scientists in all

fields — chemistry, biology, physics, material

science, engineering, etc. — have been designing

structures and systems to perform these

manipulations. Configurations on a larger

scale are constricted to certain properties of

atoms, such as weight, strength, reactivity and

response to light; however, at the nanoscale,

these structural properties can be altered to

increase a material’s usefulness, advancing

societal needs. These extremely small structures

can be used for anything, from increasing the

strength of sporting equipment to delivering

drugs to diseased cells in a person’s body.

Over the past several decades, nanotechnology

has become increasingly relevant. The

nanotechnology market is estimated to reach

US$12.83 billion by 2021, demonstrating the

promising nature of nanostructures. While

the U.S. is currently the largest market for

nanotechnology, the Asia-Pacific region, Brazil

and Canada are all poised for considerable

growth in the coming years due to favorable

microeconomic conditions and investments.

Nanotechnology: Tiny Particles, Big Shifts

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Nanoparticles Timeline

1959

1981

2000

2015

2021

1990s

2012

2016

A microscope for imaging matter at an atomic level is developed.1

President Clinton launches the National Nanotechnology Initiative to coordinate federal research and development efforts.

Nanotechnology market reaches $4.49 billion.3

The nanotechnology market is estimated at $12.83 billion.3

Richard Feynman gives the first lecture on nanotechnology and engineering at the atomic scale, presented at the annual meeting of the American Physical Society at CalTech.

First nanotechnology companies emerge.

The United States plans to spend nearly $2 billion on nanotechnology research.2

The Nobel Peace Prize in Chemistry is awarded to scientific discoveries in nanotechnology — the design and synthesis of molecular machines.4

1 https://www.britannica.com/technology/scanning-tunneling-microscope2 https://fas.org/sgp/crs/misc/RL34401.pdf3 http://www.prnewswire.com/news-releases/nanotechnology-market-to-reach-1283-billion-usd-by-2021---industryarc-

analysis-588366601.html4 http://www.nobelprize.org/nobel_prizes/chemistry/laureates/2016/

Key Considerations and ImplicationsAs with any rapidly evolving field, new appli-

cations for nanotechnology are appearing

constantly, along with considerations regarding

the future of the technology. Among them:

• Regulation — Due to the variety of nano-tech applications, supervision of nanotech research can be very complex and difficult to apply. Care must be taken not to strangle a burgeoning field with regulation, while providing a safe environment for beneficial research across many different fields.

• Transparency — Nanotechnology may be used in controversial applications, such as surveillance instruments, miniature guns and explosives, or weapons with the ability to attack physical structures or biological organisms at the molecular level. The tech-nology is not visible to the naked eye, raising concerns of the ability to easily monitor the use of these new applications and provide an appropriate quality control framework. On the sensational end of the spectrum, some have expressed concern that self-replicating nanobots can wreak havoc on Earth if they are not properly controlled.

• Privacy and consent — In healthcare, applications of nanotechnology may represent forms of invasive medicine, raising issues such as appropriate disclosures, patient consent and privacy. Such issues need to be considered early on, before widespread application of the technology in the medical field.

• The environment — The energy industry could experience huge advantages from applications of nanotechnology that can produce fossil fuels more efficiently, as well as spur the production of a number of “green” fuels. In addition, nanotech appli-cations in controlling water pollution could greatly alter environmental risk assess-ments, enabling approvals of oil extraction and other controversial projects. This, in turn, could shift the weight of environ-mental concerns from production methods and water pollution to other risks, such as carbon emissions.

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Nanotechnology is already being used by consumers in everyday products, such as stain-resistant clothing, stronger, thinner and lighter bottles and packaging, and stronger tennis balls and rackets. Below are examples of other applications across industries:

HEALTHCARE

Researchers have developed prototypes of nano-sized robots that can be used to deliver drugs to diseased cells or remove foreign objects in the human body. Drugs themselves can be produced on a nanoscale to allow for minute targeted doses, and DNA-delivering nanoparticles can alter the course of diseases such as cancer by attacking them on the cellular level, reducing dependence on more toxic treatments, such as radiation and chemotherapy. Additionally, the current wave of antimicrobial resistance could be combated if current research projects using nanotechnology prove successful.

ENERGY/FUELS

Shortages in diesel and gasoline can be mitigated using nanotechnology to produce fuel from raw materials more efficiently and at lower cost. Additionally, nanofibers can replace conventional electrodes to greatly improve the performance of hydrogen fuel cells in cars, paving the path for sustainable clean energy vehicles.

WATER TREATMENT

Nanoadsorbents, such as carbon nanotubes, are solid substances that can be used to remove both organic and inorganic pollutants from water. Nanometals can help reduce industrial contaminations caused by arsenic and heavy metals through a chemical reaction process, instead of traditional pumping and treatment of water. Other nanoparticles can act as membranes to remove virus cells, salt and metals from unsafe water to make it drinkable.

ELECTRONICS

Nanoelectronic devices can create better displays and memory chips, all while decreasing their size and power usage. Nanotechnology can also be applied to batteries to make them less flammable, more powerful and easier to charge. It can also extend shelf life dramatically by using nanomaterials to separate the liquid from the solid electrodes when the battery is not in use.

FOOD INDUSTRY

Nanotechnology in food packaging can be used to alert consumers to contaminated food by turning the package a different color once bacteria enters the package. Another food application is nanoencapsulation, a nanoscale-sized coating used to mask the taste and smell of certain additives to foods.

Spotlight: Industry Applications of Nanotechnology

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Emerging Risk Categories: Economic, Environmental, Geopolitical Industries Impacted: Agriculture, Energy & Utilities, Manufacturing, Consumer Products & Services

While oil is often first to come to mind in

discussions of natural resource scarcity and

competition, fresh water is quickly overtaking

oil as the world’s most precious commodity.

The increasingly strained supply of this

indispensable resource is approaching a level

of criticality worldwide that cannot be ignored.

At the present time, about 4 billion people,

comprising approximately two-thirds of the

world’s total population, experience severe

water shortages during at least one month

every year. Based on current trends, it is

estimated that by 2030, water demand will

exceed sustainable supply by 40 percent, a

gap that presents significant humanitarian,

economic and geopolitical concerns. As

policymakers, environmental scientists and

conservationists grapple with the best ways to

address this crisis, the continuous decline in

fresh water availability and quality warrants

attention as one of the leading global risks we

face today, and in the coming decades.

The Global Water Crisis in Perspective

The above graphic was created based on the World Resources Institute’s (WRI) Water Stress Projections report, which depicts the ratio between water withdrawals and total availability by country (year 2030, business-as-usual [BAU] tab). Higher percentages correspond to greater competition among water users.

Projected Water Stress by Country, 2030

Low (<10%)

Low to Medium (10-20%)

Medium to High (20-40%) Extremely High (>80%)

High (40-80%) No Data

Withdrawal-to-Supply Ratio

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Key Considerations and Implications • Urbanization — Along with increases in

overall global population, a key driver for the rising demand for fresh water is the rapid urbanization of developing countries, especially in Latin America, Africa and Asia. As these areas experience greater economic activity, sources of nearby freshwater are being taxed to meet the demand for improved living standards, the production of goods and services, energy generation and the expansion of irrigated agriculture. By 2050, the number of people living in urban areas will almost double to about 6.3 billion people, according to United Nations (U.N.) projections. This concentration is significant given World Bank forecasts that water availability in cities could decline by as much as two-thirds by 2050, largely as a result of climate change and competition from energy generation and agriculture.

• Climate change — As freshwater withdrawals continue to increase each year, the replenishment of these sources is threatened by the impacts of climate change. Along with more frequent and extended droughts in certain regions, rising sea levels can drive saltwater into freshwater reservoirs, requiring expensive desalination efforts to return this water to a usable form. Important freshwater reservoirs, such as the Florida Everglades, which are in close proximity to coastlines, are the most susceptible to this risk.

• Human migration — Global competition for access to fresh water will likely continue to intensify in the coming decades as shortages worsen, leading to population migration and an increased risk of geopolitical conflict. Many regions of the world that are subject to water insecurity, such as North Africa and the Middle East, already experience heightened levels of tension.

• Water quality — While access to steady supplies of fresh water presents an ongoing challenge for many regions, ensuring that this water meets essential quality standards presents another. The World Bank estimates that at least 663 million people lack access to safe drinking water. This raises a variety of health concerns, highlighted by the fact that about 675,000 people die prematurely every year due to poor sanitation, water and hygiene. Even with consistent access to reliable water sources, the cost to transport, purify and store this water is often too steep for many regions of the world.

The scarcity of fresh water poses not only

challenges but also opportunities for

governments and the private sector to invest

in fresh water projects (e.g., desalination,

water purification, centralized networks,

distributed water systems) as a means of

capitalizing on this emerging risk.

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Water is a fundamental input to nearly every industry of the global economy, and is present at virtually every stage of any given value chain, to the point that often it is taken for granted. As water scarcity increases, industry leaders will face a number of challenges with maintaining consistent access to quality water to meet business objectives and support operations. The following water-intensive industries highlight the importance of this precious natural resource:

AGRICULTURE

It is estimated that nearly 70 percent of the world’s current freshwater withdrawal is used for agriculture, largely for the growing of crops and the raising of livestock. As the global population continues to increase, albeit at a decreasing rate, water supplies will be stretched thin to support an increase in food consumption and the production of agriculture-dependent goods and services. According to the U.N., by 2050 the agricultural industry will need to produce an estimated 60 percent more food to sustain the growing global population. This projection underscores the importance of efficiency and conservation efforts aimed at reducing water losses and increasing crop productivity.

ENERGY

Energy production is the second-largest consumer of fresh water in the world, with approximately 98 percent of all generated power requiring water in some form. From the generation of electricity to the production of nuclear power, water serves as a critical input to achieve the energy levels required to support the larger economy. The development and adoption of renewable energy sources, such as wind and solar power, which require less amounts of water than traditional sources, will be key to mitigating this risk.

MANUFACTURING

The U.N. estimates that by 2050 the global water demand in the manufacturing industry will increase by 400 percent, with most of this demand coming from emerging and developing economies. While expansion of economic activity in these areas presents numerous opportunities, the challenge for industry leaders will be finding and gaining access to reliable sources of water. This will likely be very difficult, as many developing countries are in areas of the world that are already depleted of fresh water. Industry leaders will need to consider this barrier to entry prior to establishing or expanding operations in these regions — or consider technologies, such as desalination, that would allow them to generate the amounts of water they would need.

AUTOMOTIVE

The automotive industry uses water in a variety of ways, such as for treatment and coating, washing, rinsing and cooling. According to the U.S. Geological Survey, over 32,000 gallons of water are required to produce one car. Additionally, many automotive companies have operations in developing nations that suffer from increasing water stress. Industry leaders should consider using advanced water management technologies to minimize disruption to their planned production levels due to water shortage.

PHARMACEUTICALS

Water management is of paramount importance to the pharmaceutical industry, which must operate under strict quality and purity standards. Additionally, water is a critical ingredient in both the production and administration of drugs. This industry faces a unique challenge in that it must consider the removal of by-products left in the water system post-production in order to avoid chemical buildup. As water scarcity increases, it is necessary to develop processes that can effectively remove pharmaceutical contaminants from the water system to guarantee its safe reuse.

As the global demand for safe, reliable water sources increases, current supplies will not be able to sustain future needs. Looking forward, country leaders will need to place an emphasis on and promote high-quality, renewable water practices and cooperation in solving this challenge, as water not only transcends borders but is also a basic human necessity regardless of country income or development status.

Spotlight: Water Shortage Impacts by Industry

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Emerging Risk Categories: Economic, Technological, Societal Industries Impacted: Financial Services, Technology, Healthcare & Life Sciences

Machine learning, also known as Analytics 3.0,

is the latest development in the field of data

analytics. Machine learning allows computers

to take in large amounts of data, process it, and

teach themselves new skills using that input.

It’s a way to achieve artificial intelligence, or AI,

using a “learn by doing” process.

Machine learning enables computers to learn

and act without being explicitly programmed.

It evolves from the study of pattern recognition

and the design and analysis of algorithms to

enable learning from data and make possible

data-driven predictions or decisions. It is so

pervasive today that many of us likely use it

several times a day without even knowing it.

In earlier stages of analytics development, the

companies that most benefited from the new

field were the information firms and online

companies that saw and seized the opportunities

of big data before others. The ability to provide

much needed data and information represented

a clear first mover’s advantage for these

companies. While the first movers in big data

were the big winners, their advantage won’t

last much longer as productivity levels out. The

evolution to Analytics 3.0 is a game changer

because the range of business problems that

intelligent automation — a mixture of AI and

machine learning — can solve is increasing

every day. At this stage, nearly every firm in any

industry can profit from intelligent automation.

Companies that invest immediately in machine

learning have the potential to gain long-term

benefits, profiting from the work of analytics

pioneers. To gain these benefits, companies

must rethink how the analysis of data can create

value for them in the context of Analytics 3.0.

In PreView, Volume 2, Issue 2, we highlighted

the challenges that investors in AI face,

including high research and development costs

and the difficulty of retaining people with the

right skill sets. Still, we believe that the long-

term benefits outweigh the costs. The biggest

downside of not adopting AI, and specifically

machine learning, early is that firms delay the

opportunities to profit and risk displacement by

the early movers.

Artificial Intelligence: The Effects of Machine Learning

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Beneficial Applications Versus Risks of Machine Learning

BENEFITS RISKS

• Climate change modeling: Accurate modeling depends on the ability to process a multitude of variable inputs to arrive at a scenario. Machine learning can dramatically increase the speed and accuracy of climate models.

• Autonomous vehicles: Machine learning is essential to the development of truly intelligent cars that can make quick unprogrammed “decisions” based on “observed” data, and to ensuring these cars function safely.

• Medical research: Machine learning can finally help bridge the “knowledge gap” in medicine. It will allow machines to analyze a plethora of patient data with much greater speed than humans are capable of, and suggest diagnoses or treatments that may be overlooked by the physician.

• Risk assessments: A machine trained on vast amounts of data and information can make accurate predictions about risk — but there are caveats, explored below.

• Machines may surpass humans’ highest level of intelligence to a point where they psychologically manipulate people and become destructive to humans.

• People may fail to fully align AI’s goals with the values of humanity, instead focusing on emotionless optimization processes, causing machines to make decisions that are not in the best interest of humans.

• Small or inadvertent errors or bias in the data, may be magnified in the long run as machines train themselves on the faulty inputs, leading to decisions not in the interest of all humans.

• Machines that operate on very large amounts of unrelated data may find patterns or correlations in the data that are meaningless or not actionable, at best, or actionable but wrong, at worst.

Key Considerations and Implications • The moral component — The level of

intelligence and “morality” that a machine exerts is a direct result of the data it receives. One consequence is that, based on the data input, machines may train themselves to work against the interest of some humans or be biased. Failure to erase bias from a machine algorithm may produce results that are not in line with the moral standards of society. Yet not all researchers, scientists and experts believe that AI will be hurtful to society. Some believe that AI can be developed to mirror the human brain and obtain human moralistic psychology to enhance society.

• Accuracy of risk assessments — Risk assess-ments are used in many areas of society to evaluate and measure the potential risks that may be involved in specific scenarios. The increasing popularity of using AI risk assess-ments to make important decisions on behalf of people is a direct result of the growing trust between humans and machines. However, there are serious implications to note when

using a machine learning system to make risk assessments. A quantitative analyst estimates that some machine learning strategies may fail up to 90 percent when tested in a real-life setting. The reason is that while algorithms used in machine learning are based on an almost infinite amount of items, much of this data is very similar. For these machines, finding a pattern would be easy, but finding a pattern that will fit every real-life scenario would be difficult.

• Transparency of algorithms — Supporters of creating transparency in AI advocate for the creation of a shared and regulated database that is not in possession of any one entity that has the power to manipulate the data; however, there are many reasons why corporations are not encouraging this. While transparency may be the solution to creating trust between users and machines, not all users of machine learning see a benefit there.

On the next page, we highlight some of the ways

these implications play out in several industries.

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BIAS IN MEDICINE

Today, artificial intelligence makes it possible to predict the likelihood of a heart attack with much better accuracy than before. While manual systems are able to make correct predictions with around 30 percent accuracy, a machine learning algorithm created at Carnegie Mellon University was able to raise the prediction accuracy to 80 percent. In a hospital, an 80 percent prediction theoretically would give a physician four hours to intervene before the occurrence of the life-threatening event.

However, the accuracy of risk assessments in the medical field may vary depending on the level of bias in the research used to train the machine learning algorithm. For instance, most heart disease research is conducted on men, even though heart attack symptoms between men and women differ in some important ways. If the system is trained to recognize heart attack symptoms found in men, the accuracy of predicting a heart attack in women diminishes and may result in a fatality. For that reason, people who are affected by decisions based on AI risk assessments will want to know how these decisions are systematically made.

TRANSPARENCY IN FINANCIAL ALGORITHMS

Hedge funds, which have always relied heavily on computers to find trends in financial data, are increasingly moving toward machine learning. Their goal is to be able to automatically recognize changes in the market and react quickly in ways quant models cannot. Most of these algorithms are proprietary, for a reason. The risk of having transparency in this case is that as one fund becomes successful using a certain algorithm, others will want to mimic that company’s machine learning method, diminishing everyone’s success and creating an artificial market environment. For this reason, any regulation that attempts to control the transparency of AI must be suitable and appropriate to the various scenarios where AI is used.

RESPONSIBILITY OF SELF-DRIVING CARS

The U.S. National Highway Traffic Safety Administration recently released guidelines for autonomous vehicles, requiring auto manufacturers to voluntarily submit their design, development, testing and deployment plans before going to market with their vehicles. Despite these efforts to increase the transparency around “the brains” deployed in autonomous vehicles, car manufacturers, tech companies and auto parts makers are in a tight competition to develop the software behind self-driving cars, and their need to keep development efforts under wraps to gain market advantage may end up hurting the future of autonomy.

In addition, the nature of machine learning itself makes it very difficult to prove that autonomous vehicles will operate safely. Traditional computer coding is written to meet safety requirements and then tested to verify if it was successful; however, machine learning allows a computer to learn and perform at its own pace and level of complexity. The more automakers are willing to be transparent about the data they input into the learning algorithms, the easier it will be for lawmakers and auto safety regulators to create laws that will ensure the safety of consumers.

Spotlight: Industry Implications

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The Effects of Populism on Trade and RegulationPopulism, defined as a belief in the power of

regular people and their right to have control

over their government as opposed to being

controlled by a small group of political insiders

or a wealthy elite, has started to influence

major events on the global economic and

political stage — but its effects have not yet

manifested themselves fully, or they are not yet

fully understood. While populism is certainly

not new, it has revealed itself recently in the

form of rallies against both foreign trade and

regulation, stemming from the notion that

these practices prevent domestic job growth

and redirect power and wealth from domestic

citizens and corporations to parties abroad. Due

to the speed at which citizens can now organize

and communicate, these movements are more

impactful, less predictable, and more difficult to

address than in the past. Recent events such as

Brexit, the U.S. presidential election and Italian

citizens’ response to proposed constitutional

overhauls evidence their magnitude.

The potential implications of such movements

create uncertainty. Globalization has facilitated

the interchange of worldviews, products, ideas

and culture for a long time and has accelerated

over the last three decades. Global trading

partners and supply chains can’t be cut off

through the proverbial turn of the spigot

without repercussions. Although more

restrictive trade policies theoretically create

domestic jobs, history shows these actions

can also result in job loss, trade wars and an

increase in the price of imports. If restrictive

trade policies give rise to protectionism, that

could precipitate a dangerous downward spiral.

If output declines, deflation occurs and/or

unemployment increases, populist governments

may be pressured to take pre-emptive action to

invigorate their economies, even if that means

limiting imports.

Further, repealing major regulatory

frameworks, such as the one created by the

Dodd-Frank Act, may reduce corporations’

costs of compliance and thus create more

jobs — but this can also leave critical risks

unmitigated. As citizens across the globe

witness the relative ease and power of modern

populist movements, it’s likely that more

movements will arise, making institutions of

global trade and regulatory infrastructures

subject to continuous, and often unpredictable,

change. This trend can have implications of

historic proportions for virtually all nations

and industries.

Cybersecurity Risk RevisitedIn the Volume 2, Issue 1 of PreView, published

in 2015, we highlighted major data breaches

and their financial and compliance-related

implications to select industries. Recently,

federal and state governments have emerged

prominently as targets of cybersecurity

concerns. These government hacks extend from

data breaches to suspicions of tampering with

the election process. To combat the increasing

threat of cybersecurity, the federal government

introduced the Cybersecurity National Action

Plan and also appointed the first Federal Chief

Information Security Officer. Cybersecurity will

continue to be an evolving and persistent risk to

individuals, companies and governments, and

thus a topic for future issues.

On the Radar

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Nanotechnology“Nanorobots: Where We Are Today and Why Their Future Has Amazing Potential,” by Peter Diamandis, Singularity Hub, May 16, 2016: http://singularityhub.com/2016/05/16/nanorobots-where-we-are-today-and-why-their-future-has-amazing-potential/.

“From Super Pills to Second Skin: Meet the Willy Wonka Revolutionizing Medicine,” by Amy Fleming, The Guardian, October 17, 2016: www.theguardian.com/lifeandstyle/2016/oct/17/robert-langer-nanotechnology-pioneer-willy-wonka-revolutionising-medicine.

“Nanomedicine To Combat Infections From Antimicrobial-Resistant Bacteria.” Article published by Nicolas Gouze, ETPN Secretariat in the publication ‘International Innovation’ (Issue 140): www.etp-nanomedicine.eu/public/about-nanomedicine/nanomedicine-applications/amr.

“Nanotechnology & You,” Nano.gov: www.nano.gov/you/nanotechnology-benefits.

The Global Water Crisis“Water Shortage May Cripple Global Power Supply,” by Pola Lem, Scientific American, March 18, 2016: www.scientificamerican.com/article/water-shortage-may-cripple-global-power-supply/.

“What Is Hydrology and What Do Hydrologists Do?” by Howard Perlman, USGS, December 2, 2016: http://water.usgs.gov/edu/hydrology.html.

“2016 UN World Water Development Report, Water and Jobs,” United Nations Educational, Scientific and Cultural Organization, 2016: www.unesco.org/new/en/natural-sciences/environment/water/wwap/wwdr/2016-water-and-jobs/.

Artificial Intelligence“Analytics 3.0 and Data-Driven Transformation,” by Chandramohan Kannusamy, Data Informed, March 7, 2016: http://data-informed.com/analytics-3-0-and-data-driven-transformation/.

“Machine Learning: Of Prediction and Policy,” The Economist, August 20, 2016: www.economist.com/news/finance-and-economics/21705329-governments-have-much-gain-applying-algorithms-public-policy.

“The Rise of the Artificially Intelligent Hedge Fund,” by Cade Metz, Wired.com, January 25, 2016: www.wired.com/2016/01/the-rise-of-the-artificially-intelligent-hedge-fund/.

On the Radar“2017 Markets Likely to Soar Higher Under Trump,” by Katina Stefanova, Forbes, January 1, 2017: www.forbes.com/sites/katinastefanova/2017/01/01/markets-in-2017-reagan-style-republicanism-meets-neo-populism/.

“Italy’s Populists Claim Victory in Referendum, But Chaos Looms,” by Silvia Marchetti, TIME, December 5, 2016: http://time.com/4590204/italy-referendum-matteo-renzi-populists/.

“Presidential Proclamation — National Cybersecurity Awareness Month, 2016,” The White House, Office of the Press Secretary, September 30, 2016: www.whitehouse.gov/the-press-office/2016/09/30/presidential-proclamation-national-cybersecurity-awareness-month-2016.

“Fact Sheet: Cybersecurity National Action Plan,” The White House, Office of the Press Secretary, February 9, 2016: www.whitehouse.gov/the-press-office/2016/02/09/fact-sheet-cybersecurity-national-action-plan.

Where to Learn More

Page 13: PreView: Protiviti's View on Emerging Risksthe future of the technology. Among them: ... • The environment — The energy industry could experience huge advantages from applications

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The risk areas summarized above will continue

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Continuing the Conversation

ContactsCory Gunderson Managing Director +1.212.708.6313 [email protected]

Matthew Moore Managing Director +1.704.972.9615 [email protected]

Jim DeLoachManaging Director [email protected]

Andrew ClintonManaging Director [email protected]