healthcarereimagined

• Alessandro Di Fiore September 13, 2018

Summary.

Summary.   Planning was one of the cornerstones of management, but it’s now fallen out of fashion. It seems rigid, bureaucratic, and ill-suited to a volatile, unpredictable world. However, organizations still need some form of planning. And so, universally valuable, but desperately unfashionable, planning waits like a spinster in a Jane Austen novel for someone to recognize her worth. The answer is agile planning, a process that can coordinate and align with today’s agile-based teams. Agile planning also helps to resolve the tension between traditional planning’s focus on hard numbers, and the need for “soft data,” or human judgment.close

Planning has long been one of the cornerstones of management. Early in the twentieth century Henri Fayol identified the job of managers as to plan, organize, command, coordinate, and control. The capacity and willingness of managers to plan developed throughout the century. Management by Objectives (MBO) became the height of corporate fashion in the late 1950s. The world appeared predictable. The future could be planned. It seemed sensible, therefore, for executives to identify their objectives. They could then focus on managing in such a way that these objectives were achieved.

This was the capitalist equivalent of the Communist system’s five-year plans. In fact, one management theorist of the 1960s suggested that the best managed organizations in the world were the Standard Oil Company of New Jersey, the Roman Catholic Church and the Communist Party. The belief was that if the future was mapped out, it would happen.

Later, MBO evolved into strategic planning. Corporations developed large corporate units dedicated to it. They were deliberately detached from the day-to-day realities of the business and emphasized formal procedures around numbers. Henry Mintzberg defined strategic planning as “a formalized system for codifying, elaborating and operationalizing the strategies which companies already have.” The fundamental belief was still that the future could largely be predicted.

Now, strategic planning has fallen out of favor. In the face of relentless technological change, disruptive forces in industry after industry, global competition, and so on, planning seems like pointless wishful thinking.

And yet, planning is clearly essential for any company of any size. Look around your own organization. The fact that you have a place to work which is equipped for the job, and you and your colleagues are working on a particular project at a particular time and place, requires some sort of planning. The reality is that plans have to be made about the use of a company’s resources all of the time. Some are short-term, others stretch into an imagined future.

Universally valuable, but desperately unfashionable, planning waits like a spinster in a Jane Austen novel for someone to recognize her worth.

But executives are wary of planning because it feels rigid, slow, and bureaucratic. The Fayol legacy lingers. A 2016 HBR Analytics survey of 385 managers revealed that most executives were frustrated with planning because they believed that speed was important and that plans frequently changed anyway. Why engage in a slow, painful planning exercise when you’re not even going to follow the plan?

The frustrations with current planning practices intersect with another fundamental managerial trend: organizational agility. Reorganizing around small self-managing teams — enhanced by agility methods like Scrum and LeSS — is emerging as the route to the organizational agility required to compete in the fast-changing business reality. One of the key principles underpinning team-based agility is that teams autonomously decide their priorities and where to allocate their own resources.

The logic of centralized long-term strategic planning (done once a year at a fixed time) is the antithesis of an organization redesigned around teams who define their own priorities and resources allocation on a weekly basis.

But if planning and agility are both necessary, organizations have to make them work. They have to create a Venn diagram with planning on one side, agility on the other, and a practical and workable sweet-spot in the middle.  This is why the quest to rethink strategic planning has never been more urgent and critical. Planning twenty-first century style should be reconceived as agile planning.

Agile planning has a number of characteristics:

• frameworks and tools able to deal with a future that will be different;
• the ability to cope with more frequent and dynamic changes;
• the need for quality time to be invested for a true strategic conversation rather than simply being a numbers game;
• resources and funds are available in a flexible way for emerging opportunities.

The intersection of planning with organizational agility generates two other paramount requirements:

A process able to coordinate and align with agile teams

Agile organizations face the challenge of managing the local autonomy of squads (bottom-up input) consistently with a bigger picture represented by the tribe’s goals and by cross-tribe interdependencies and the strategic priorities of the organization (top-down view). Governing this tension requires new processes and routines for planning and coordination.

Consider the Dutch financial services firm ING Bank. It restructured its operations in the Netherlands by reorganizing 3,500 employees into agile squads. These are autonomous multidisciplinary teams (up to nine people per team) able to define their work and make business decisions quickly and flexibly. Squads are organized into a Tribe (of no more than 150 people), a collection of squads working on related areas.

ING Bank revisited its process and introduced routine meetings and formats to create alignment between and within tribes. Each tribe develops a QBR (Quarterly Business Review), a six-page document outlining tribe-level priorities, objectives and key results.   This is then discussed in a large alignment meeting (labelled the QBR Marketplace) attended by tribe leads and other relevant leaders. At this meeting one fundamental question is addressed: when we add up everything, does this contribute to our company’s strategic goals?

The alignment within a tribe happens at what is called a Portfolio Marketplace event: representatives of each of the squads which make up the tribe come together to agree on how the set goals are going to be achieved and to address opportunities for synergies.

The ING Bank example shows how the planning process is still necessary and essential to an agile company although in a different fashion with different processes, mechanisms and routines.

As more and more companies transform into agile organizations, agile planning will likely become the new normal replacing the traditional centralized planning approach.

A process that makes use of both limitless hard data and human judgment

Planners have traditionally been obsessed with gathering hard data on their industry, markets, competitors. Soft data — networks of contacts, talking with customers, suppliers and employees, using intuition and using the grapevine — have all but been ignored.

From the 1960s onwards, planning was built around analysis.  Now, thanks to Big Data, the ability to generate data is pretty well limitless.  This does not necessarily allow us to create better plans for the future.

Soft data is also vital. “While hard data may inform the intellect, it is largely soft data that generate wisdom. They may be difficult to ‘analyze’, but they are indispensable for synthesis — the key to strategy making,” saysHenry Mintzberg.

Companies need first to imagine possibilities and second, pick the one for which the most compelling argument can be made.  In deciding which is backed by the most compelling argument, they should indeed take into account all data that can be crunched. But in addition, they should use qualitative judgment.

In an agile organization, teams use design thinking and other exploratory techniques (plus data) to make rapid decisions and change the course on a weekly basis. Decision making is done by a team of people, offsetting in this way the potential biases of a single person making a decision based on her individual judgement. To some extent, an agile team-based organization enables the possibility to leverage qualitative data and judgement — combined today with infinite hard data — for better decisions.

Relying solely on hard data has unquestionably killed many potential great businesses. Take Nespresso, the coffee pod pioneer developed by Nestle.  Nespresso took off when it stopped targeting offices and started marketing itself to households. There was little data on how households would respond to the concept and whatever information was available suggested a perceived consumer value of just 25 Swiss centimes versus a company-wide threshold requirement of 40 centimes. The Nespresso team had to interpret the data skillfully to present a better case to top management. Because it believed strongly in the idea, it forced the company to take a bigger-than-usual risk. If Nestle had been guided solely by quantitative market research the concept would never have gotten off the ground.

The traditional planning approach needs to be revisited to better serve the purposes of the agile enterprise of the twenty-first century. Agile planning is the future of planning. This new approach will require two fundamental elements. First, replacing the traditional obsessions on hard data and playing the numbers-game with a more balanced co-existence of hard and soft data where judgment also plays an important role. Second, introducing new mechanisms and routines to ensure alignment between the hundreds of self-organizing autonomous local teams and the overarching goals and directions of the company.

• Alessandro Di Fiore is the founder and CEO of the European Centre for Strategic Innovation (ECSI) and ECSI Consulting. He is based in Boston and Milan. He can be reached at adifiore@ecsi-consulting.com. Follow him on twitter @alexdifiore.

Article link: https://hbr.org/2018/09/planning-doesnt-have-to-be-the-enemy-of-agile?

By CHRISTOPHER DANCY The ConversationOCTOBER 31, 2022

Will it have any significant impact?

Despite the important and ever-increasing role of artificial intelligence in many parts of modern society, there is very little policy or regulation governing the development and use of AI systems in the U.S. Tech companies have largely been left to regulate themselves in this arena, potentially leading to decisions and situations that have garnered criticism.

Google fired an employee who publicly raised concerns over how a certain type of AI can contribute to environmental and social problems. Other AI companies have developed products that are used by organizations like the Los Angeles Police Department where they have been shown to bolster existing racially biased policies.

There are some government recommendations and guidance regarding AI use. But in early October 2022, the White House Office of Science and Technology Policy added to federal guidance in a big way by releasing the Blueprint for an AI Bill of Rights.

The Office of Science and Technology says that the protections outlined in the document should be applied to all automated systems. The blueprint spells out “five principles that should guide the design, use, and deployment of automated systems to protect the American public in the age of artificial intelligence.” The hope is that this document can act as a guide to help prevent AI systems from limiting the rights of U.S. residents.

As a computer scientist who studies the ways people interact with AI systems – and in particular how anti-Blackness mediates those interactions – I find this guide a step in the right direction, even though it has some holes and is not enforceable.

IMPROVING SYSTEMS FOR ALL

The first two principles aim to address the safety and effectiveness of AI systems as well as the major risk of AI furthering discrimination.

To improve the safety and effectiveness of AI, the first principle suggests that AI systems should be developed not only by experts, but also with direct input from the people and communities who will use and be affected by the systems. Exploited and marginalized communities are often left to deal with the consequences of AI systems without having much say in their development. Research has shown that direct and genuine community involvement in the development process is important for deploying technologies that have a positive and lasting impact on those communities.

The second principle focuses on the known problem of algorithmic discrimination within AI systems. A well-known example of this problem is how mortgage approval algorithms discriminate against minorities. The document asks for companies to develop AI systems that do not treat people differently based on their race, sex or other protected class status. It suggests companies employ tools such as equity assessments that can help assess how an AI system may impact members of exploited and marginalized communities.

These first two principles address big issues of bias and fairness found in AI development and use.

PRIVACY, TRANSPARENCY AND CONTROL

The final three principles outline ways to give people more control when interacting with AI systems.

The third principle is on data privacy. It seeks to ensure that people have more say about how their data is used and are protected from abusive data practices. This section aims to address situations where, for example, companies use deceptive design to manipulate users into giving away their data. The blueprint calls for practices like not taking a person’s data unless they consent to it and asking in a way that is understandable to that person.

The next principle focuses on “notice and explanation.” It highlights the importance of transparency – people should know how an AI system is being used as well as the ways in which an AI contributes to outcomes that might affect them. Take, for example the New York City Administration for Child Services. Research has shown that the agency uses outsourced AI systems to predict child maltreatment, systems that most people don’t realize are being used, even when they are being investigated.

The AI Bill of Rights provides a guideline that people in New York in this example who are affected by the AI systems in use should be notified that an AI was involved and have access to an explanation of what the AI did. Research has shown that building transparency into AI systems can reduce the risk of errors or misuse.

The last principle of the AI Bill of Rights outlines a framework for human alternatives, consideration and feedback. The section specifies that people should be able to opt out of the use of AI or other automated systems in favor of a human alternative where reasonable.

As an example of how these last two principles might work together, take the case of someone applying for a mortgage. They would be informed if an AI algorithm was used to consider their application and would have the option of opting out of that AI use in favor of an actual person.

SMART GUIDELINES, NO ENFORCEABILITY

The five principles laid out in the AI Bill of Rights address many of the issues scholars have raised over the design and use of AI. Nonetheless, this is a nonbinding document and not currently enforceable.

It may be too much to hope that industry and government agencies will put these ideas to use in the exact ways the White House urges. If the ongoing regulatory battle over data privacy offers any guidance, tech companies will continue to push for self-regulation.

One other issue that I see within the AI Bill of Rights is that it fails to directly call out systems of oppression – like racism or sexism – and how they can influence the use and development of AI. For example, studies have shown that inaccurate assumptions built into AI algorithms used in health care have led to worse care for Black patients. I have argued that anti-Black racism should be directly addressed when developing AI systems. While the AI Bill of Rights addresses ideas of bias and fairness, the lack of focus on systems of oppression is a notable hole and a known issue within AI development.

Despite these shortcomings, this blueprint could be a positive step toward better AI systems, and maybe the first step toward regulation. A document such as this one, even if not policy, can be a powerful reference for people advocating for changes in the way an organization develops and uses AI systems.

Article link: https://www.nextgov.com/ideas/2022/10/white-houses-ai-bill-rights-outlines-five-principles-make-artificial-intelligence-safer-more-transparent-and-less-discriminatory/379101/

Christopher Dancy, Associate Professor of Industrial & Manufacturing Engineering and Computer Science & Engineering, Penn State

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Open-source code runs on every computer on the planet—and keeps America’s critical infrastructure going. DARPA is worried about how well it can be trusted

• Patrick Howell O’Neillarchive page

July 14, 2022

It’s not much of an exaggeration to say that the whole world is built on top of the Linux kernel—although most people have never heard of it.

It is one of the very first programs that load when most computers power up. It enables the hardware running the machine to interact with the software, governs its use of resources, and acts as the foundation of the operating system.

It is the core building block of nearly all cloud computing, virtually every supercomputer, the entire internet of things, billions of smartphones, and more.

But the kernel is also open source, meaning anyone can write, read, and use its code. And that’s got cybersecurity experts inside the US military seriously worried. Its open-source nature means the Linux kernel—along with a host of other pieces of critical open-source software—is exposed to hostile manipulation in ways that we still barely understand.

“People are realizing now: wait a minute, literally everything we do is underpinned by Linux,”  says Dave Aitel, a cybersecurity researcher and former NSA computer security scientist. “This is a core technology to our society. Not understanding kernel security means we can’t secure critical infrastructure.”

Related Story

The internet runs on free open-source software. Who pays to fix it?Volunteer-run projects like Log4J keep the internet running. The result is unsustainable burnout, and a national security risk when they go wrong.

Now DARPA, the US military’s research arm, wants to understand the collision of code and community that makes these open-source projects work, in order to better understand the risks they face. The goal is to be able to effectively recognize malicious actors and prevent them from disrupting or corrupting crucially important open-source code before it’s too late.

DARPA’s  “SocialCyber” program is an 18-month-long, multimillion-dollar project that will combine sociology with recent technological advances in artificial intelligence to map, understand, and protect these massive open-source communities and the code they create. It’s different from most previous research because it combines automated analysis of both the code and the social dimensions of open-source software.

“The open-source ecosystem is one of the grandest enterprises in human history,” says Sergey Bratus, the DARPA program manager behind the project.

“It’s now grown from enthusiasts to a global endeavor forming the basis of global infrastructure, of the internet itself, of critical industries and mission-critical systems pretty much everywhere,” he says. “The systems that run our industry, power grids, shipping, transportation.”

Threats to open source

Much of modern civilization now depends on an ever-expanding corpus of open-source code because it saves money, attracts talent, and makes a lot of work easier.

But while the open-source movement has spawned a colossal ecosystem that we all depend on, we do not fully understand it, experts like Aitel argue. There are countless software projects, millions of lines of code,  numerous mailing lists and forums, and an ocean of contributors whose identities and motivation are often obscure, making it hard to hold them accountable. 

That can be dangerous. For example, hackers have quietly inserted malicious code into open-source projects numerous times in recent years. Back doors can long escape detection, and, in the worst case, entire projects have been handed over to bad actors who take advantage of the trust people place in open-source communities and code. Sometimes there are disruptions or even takeovers of the very social networks that these projects depend on. Tracking it all has been mostly—though not entirely—a manual effort, which means it does not match the astronomical size of the problem.

Bratus argues that we need machine learning to digest and comprehend the expanding universe of code—meaning useful tricks like automated vulnerability discovery—as well as tools to understand the community of people who write, fix, implement, and influence that code. 

The ultimate goal is to detect and counteract any malicious campaigns to submit flawed code, launch influence operations, sabotage development, or even take control of open-source projects.

To do this, the researchers will use tools such as sentiment analysis to analyze the social interactions within open-source communities such as the Linux kernel mailing list, which should help identify who is being positive or constructive and who is being negative and destructive. 

The researchers want insight into what kinds of events and behavior can disrupt or hurt open-source communities, which members are trustworthy, and whether there are particular groups that justify extra vigilance. These answers are necessarily subjective. But right now there are few ways to find them at all.

Experts are worried that blind spots about the people who run open-source software make the whole edifice ripe for potential manipulation and attacks. For Bratus, the primary threat is the prospect of “untrustworthy code” running America’s critical infrastructure—a situation that could invite unwelcome surprises. 

Unanswered questions

Here’s how the SocialCyber program works. DARPA has contracted with multiple teams of what it calls “performers,” including small, boutique cybersecurity research shops with deep technical chops.

One such performer is New York–based Margin Research, which has put together a team of well-respected researchers for the task.

“There is a desperate need to treat open-source communities and projects with a higher level of care and respect,” said Sophia d’Antoine, the firm’s  founder. “A lot of existing infrastructure is very fragile because it depends on open source, which we assume will always be there because it’s always been there. This is walking back from the implicit trust we have in open-source code bases and software.”

Margin Research is focused on the Linux kernel in part because it’s so big and critical that succeeding here, at this scale, means you can make it anywhere else. The plan is to analyze both the code and the community in order to visualize and finally understand the whole ecosystem.

Margin’s work maps out who is working on what specific parts of open-source projects. For example, Huawei is currently the biggest contributor to the Linux kernel. Another contributor works for Positive Technologies, a Russian cybersecurity firm that—like Huawei—has been sanctioned by the US government, says Aitel. Margin has also mapped code written by NSA employees, many of whom participate in different open-source projects.

“This subject kills me,” says d’Antoine of the quest to better understand the open-source movement, “because, honestly, even the most simple things seem so novel to so many important people. The government is only just realizing that our critical infrastructure is running code that could be literally being written by sanctioned entities. Right now.”

This kind of research also aims to find underinvestment—that is critical software run entirely by one or two volunteers. It’s more common than you might think—so common that one common way software projects currently measure risk is the “bus factor”: Does this whole project fall apart if just one person gets hit by a bus? 

While the Linux kernel’s importance to the world’s computer systems may be the most pressing issue for SocialCyber, it will tackle other open-source projects too. Certain performers will focus on projects like Python, an open-source programming language used in a huge number of artificial-intelligence and machine-learning projects. 

The hope is that greater understanding will make it easier to prevent a future disaster, whether it’s caused by malicious activity or not. 

“Pretty much everywhere you look, you find open-source software,” says Bratus.“Even when you look at proprietary software, a recent study showed it’s actually 70% or more open source.”

“This is a critical infrastructure problem,” Aitel says. “We don’t have a grip on it. We need to get a grip on it. The potential impact is that malicious hackers will always have access to Linux machines. That includes your phone. It’s that simple.”

Article link: https://trib.al/U5Tu11y

• Ram Charan

September 19, 2022

Summary. The characteristics that help an organization succeed have changed over the past century. While a highly structured, top-down management style used to be companies’ preferred approach to organization, the internet has made this structure (and the layers of hierarchy that developed over decades) irrelevant. In this article, the author discusses how a successful organization today moves from mass markets to markets of one, routinely replaces core competencies, shifts to team-based structures, and manages from the outside in, among other features.

Organizations succeed over time only when they adapt to the speed and character of external change. Every aspect of an organization — from how it operates and is structured to how it is led — must match the current yet ever-shifting context in which it exists.

As the world changes at a faster pace than ever before, companies must change more rapidly as well. Yet the practices, structures, and behaviors at many large companies are not designed for such responsiveness. A century ago companies implemented such approaches because control, consistency, and predictability were top concerns; core competencies were cherished foundations to build on; and leaders viewed the world from inside the organization looking out.

To thrive today, however, companies must be able to detect external changes from the outside in and have a built-in fluidity so they can continually adapt. They need to focus on individual customers, make their core competencies dynamic, and rely on teams instead of a hierarchy — all by using the power of data and algorithms.

As we look back on a century of Harvard Business Review, we should also take time to look ahead — and recognize what the next iteration of a successful organization looks like.

Where the Organization Has Been

Since its founding, HBR has sought answers to fundamental questions such as these: What’s the best way to organize a business? What is the right structure, and how should day-to-day decisions be made?

About a century ago Henry Ford had a world-changing answer to these questions. He built a business around top-down management and assembly line mass production. By standardizing his automobiles and the steps taken to manufacture them, he lowered the cost per unit across the entire end-to-end value chain. That innovation, combined with his decision to raise workers’ pay to $5 per day, was adopted by other companies. This change drove industrial activity — making it possible for millions more people to own and enjoy everything from cars to Coca-Cola — and raised living standards around the world. Even as Ford’s company grew, though, its structure remained the same: a hierarchy in which business decisions were made in the C-suite and functions reported up to the president and chief executive.

What Makes a Successful Organization, According to HBR Readers

An organization that not only delivers on customers’ …

Alfred P. Sloan, Jr., CEO of Ford’s major competitor, General Motors (GM), decided to pursue a new strategy by offering different makes and models of cars for every budget in a range of styles and colors. GM used consumer research to segment the market, but it always kept the focus on markets large enough to ensure the manufacturing would be cost-effective. To manage multiple products and brands, Sloan realized that GM needed a different organizational structure too — one with divisions that each had a top leader responsible for profit and loss (P&L).

After World War II, large companies became even larger as they extended their sales and production and built networks of suppliers (what we now call “ecosystems”) in countries and even on continents other than their own. Many multinational corporations adopted a P&L organization structure to maintain control of their sprawling businesses.

In the 1950s, as industrial manufacturer General Electric (GE) prepared to adopt a P&L structure, it consulted with leading management thinker Peter Drucker, who pointed out that executives would need training to make the new system work. That led GE to create a 16-week course on how to be a general manager, birthing its now-famous training center in Crotonville, New York. Soon after, Harvard Business School created an Advanced Management Program course (which I taught for 30 years), and consulting firms created product lines around leadership training.

Companies continued to expand in size, breadth, and hierarchical levels, yet they also needed to coordinate across their existing structures. A host of companies — including TRW, Bechtel, Citibank, and Texas Instruments — began to use a matrix arrangement in which reporting relationships and accountability were shared across product, functional, and geographic structures.

In the 1990s, of course, the internet changed everything. Marc Andreessen co-created a browser that made the web useful for commercial purposes, coders began developing software and then algorithms to make decisions more quickly than humans can, and computer processing capacity became increasingly cheaper and more powerful.

Jeff Bezos saw the internet growing at 2,300% per annum, left his job at investment firm DE Shaw, and founded an online bookstore called Amazon, which has since morphed into not just the “everything store” but also the leading provider of web services to a host of other companies.

Where the Organization Is Now 

Bezos discovered early what every twenty-first-century leader should now know: We have entered an age of discontinuity in which breaks in the external world are deeper and more frequent, rendering prevailing organizational structures and practices ineffective, if not harmful. Successful organizations exploit those changes, as Amazon has since its inception, and take advantage of what’s new.

Current realities make it imperative that companies shift in several ways:

1. From mass market to markets of one.

Bezos recognized that an online retailer could offer far more choices than a local shop could, along with the convenience of delivery right to the customer’s home — all at a lower cost. This kind of affordable personalization and service was a new value proposition. What’s more, each transaction provided Amazon with data that its algorithmic engine could analyze to ensure that future offerings were better tailored to each consumer’s preferences, needs, and desires, or what I call “markets of one.” 

Businesses that use technology to predict and personalize what a vast number of individuals want at low incremental cost can scale up and increase cash gross margins. Companies that don’t make this shift will find it hard to compete.

2. From building on core competencies to routinely replacing them.

The conventional wisdom has been that companies should use their core competencies to sustain a competitive advantage. But in an age of discontinuity, this approach doesn’t work for long.

Leaders of every company today must ask these questions: Given changing external realities, is this core competence becoming less important or irrelevant? Do we still need to expend resources to support it, or are there new competencies we need to build and shift resources toward?

Right now, for example, if you don’t have a core competence in using algorithms, you will need to acquire or develop this capacity. Amazon eclipsed many retailers that were too slow to adapt, but now we see brick-and-mortar competitors such as Walmart building their data analytics and e-commerce capabilities.

Recruiting the right people and deploying them in ways that allow them to apply their expertise and energy are core competencies themselves and critical in the age of discontinuity. In an escalating war for talent, businesses that are the most skilled in acquiring and developing these competencies will have a distinct competitive advantage.

3. From hierarchical layers to a team-based structure.

Nearly every company needs to reduce the hierarchical layers that have accumulated in their organizations over time and channel more work to teams.

The benefits of doing so are manifold. When teams include people who are on the front lines, the information flow is both faster and more accurate; with this increased speed comes greater flexibility to respond to customer and market changes. The improved flow of information also creates transparency that removes a lot of organizational politics and encourages collaboration.

Next In

100 Years of HBR

Visualizing a Century of Management Ideas

How HBR’s coverage has evolved over time.

Fidelity Investments, the financial services firm, recently restructured its personal investing group in a team format. Each team has a clear mission and much autonomy in how to accomplish it. The roughly 5,000-person organization now has just three layers below the president and operates at lower cost and with shorter cycle times for innovation. The control function that managerial layers used to perform is now done through software that generates detailed metrics. Reports are produced 24/7 and highlight any red flags in the data.

4. From inside-out to outside-in management.

To keep a company competitive over the long term, leaders must know what is happening far beyond their own industry, geography, and existing customers.

Societal issues around sustainability, racial justice, and geopolitics affect many aspects of business, from strategy to the ability to hire the best talent. Today, for example, it is impossible to ignore the tricky issues raised by China’s intermixing of business and the Chinese Communist Party, which has a presence in every major Chinese company.

Business leaders need a wide lens and a routine for detecting early-warning signals of external changes. Some leaders set aside 10 minutes in every team meeting to discuss any new dynamics people are observing, sometimes prompted by a newspaper article or an outside event. When leaders repeatedly ask, “What’s new?” — as Jack Welch used to do when he was CEO of GE — they can help the organization develop an awareness of subtle shifts that might indicate where things are heading. The goal of such vigilance is to get the organization ready for change so it’s poised to drop what won’t work in the near future and jump on new opportunities.

The Path Ahead

Amazon is not alone in its adaptation to the age of discontinuity, but it continues to lead the charge, always reinvesting in its future.

Others must choose: Adapt or die. Some may be getting a late start in developing technologically driven personalization, dynamic core competencies, flatter and team-based hierarchies, and an outside-in focus. In many industries and geographies, however, there is still ample opportunity to build the structures and processes that take advantage of the new external realities. As companies start on that task, they should recognize that the best way to organize and manage a business is always changing — and that the answers to fundamental questions may be very different 100 years from now than they are today.

Article link: https://hbr.org/2022/09/what-defines-a-successful-organization?

• Ram Charan advises the CEOs and boards of some of the world’s biggest corporations and serves on seven boards. He is the author or coauthor of 33 books, such as Talent, Strategy, Risk: How Investors and Boards Are Redefining TSR and Talent Wins: The New Playbook for Putting People First (both from Harvard Business Review Press), and four of which are best sellers.

Greg Kidd Forbes Councils Member

Forbes Technology CouncilCOUNCIL POST| Membership (fee-based)

Oct 19, 2022,06:15am EDT

Greg Kidd, CEO and co-founder of Hard Yaka.

One of the most essential elements of participation in today’s information-based world is an individual’s digital identity. It’s the key that unlocks the world’s social and economic potential.

For all the utility and necessity of establishing our identities in the digital era, however, our current systems for doing so are overly complicated, often insecure and inherently exclusionary. As a result, the U.S. has fallen far behind other countries, including the U.K., Estonia and Sweden.

With these models in mind, regulators, particularly financial regulators, can foster the necessary innovation for modernizing America’s outdated identity systems. Updating U.S. regulations will provide clarity that will encourage private sector to leverage emerging technologies that already exist.

Broad-based digital identity reform would modernize our economic infrastructure and have immediate benefits for innovation. Over the long term, it would significantly improve our nation’s financial security and our ability to include the most economically vulnerable of our citizens. We know this, and we have the technological frameworks to get there. We just need our financial regulators to take up this challenge.

The Need For A Regulatory Refresh

A secure, reliable system of identity, at its core, is a two-way permission to act. It provides assurances for both sides of a transaction that they can know and trust one another, enabling us to shop, interact and work online, globally at any time.

The cost of inaction on this isn’t trivial. The U.S. represents 97% of all global identity records stolen. In 2020 alone, there were over 1,000 reported data breaches, compromising 155.8 million individuals—nearly half the U.S. population.

The situation is worse for the most vulnerable. Around one in ten Americans (11%) do not have a government-issued photo ID; numbers that disproportionately include people of color and low-income populations. In fact, one in four Black adults has no current government-issued photo ID. Similarly, just over one-third of American adults say they have a valid and unexpired U.S. passport (37%)—about the same percentage as those who have never had a passport at all (38%). Another one in five Americans (20%) has an expired or invalid passport. Just one in five Americans with a household income under $50,000 (21%) has a valid passport.

This means that even as our culture is taking important steps toward social justice and inclusion, the analog, legacy systems of establishing identity are excluding many from important systems, with a higher burden on the least privileged.

This was made crystal clear during the Covid-19 pandemic when some of the most vulnerable people were denied aidbecause they couldn’t prove their identities remotely.

What A Digital Identity System Might Look Like

Financial regulators play an outsized role in fostering the necessary innovation for modernizing America’s outdated identity systems.

Take the U.S. Treasury’s Financial Crimes Enforcement Network (FinCEN) Customer Identification Program (CIP) rule, which has only been minimally updated since 2003. Two decades ago, the requirements for proving identity were rooted in an analog face-to-face world. Today, financial institutions looking to digital technologies to enhance identity assurance are forced to navigate a web of uncertainty. Many are deterred, choosing to maintain the status quo, imposing significant costs on consumers, businesses and society at large.

Instead, they should follow the lead of the Financial Action Task Force, which sets international anti-money laundering standards, and eliminate all guidance suggesting that remote onboarding is necessarily more risky than face-to-face onboarding. Here a few ways to do so: 

1. Reduce the bureaucracy needed for one financial institution to place reliance on CIP conducted by another, helping make portable identity solutions more feasible.

2. Set standards for user-controlled verified identity solutions.

3. Promote private sector experimentation with digital identity solutions, including through the use of regulator-sponsored innovation programs.

Innovators can also help make it easier for financial institutions to adopt innovative solutions that involve portable identity by providing financial institutions with strong documentation about why solutions both meet their compliance obligations and provide equivalent or better assurance than traditional methods.

Swift action from U.S. regulators, along with innovators better meeting the needs of financial institutions, would have the following tangible benefits:

1. Enhanced Verification Standards. Digital identity solutions provide flexible tools for more robust verification processes relative to traditional onboarding methods. At the same time, customers have greater peace of mind knowing that their data is less vulnerable to being compromised.

2. Increased Financial Inclusion. A 2019 study by the FDIC found that 7.1 million homes in the U.S. (5.4%) were unbanked (meaning nobody in the household had a savings or checking account), including 14% of Black households, 12% of Latino households and over 16% of American Indian or Native Alaskan households. Similarly, 30% of people who live in low-income areas do not have a credit record. Digital identity solutions can provide the underbanked who lack traditional identifying documentation or credit history a clearer path toward inclusion in the regulated financial sector.

3. Increased Trust. Emerging digital identity solutions allow individuals to quickly and conveniently authenticate themselves without compromising their personal information.

4. Enhanced Security. Solutions that leverage the growing array of biometric tools available thanks to widespread smartphone adoption are also far more resilient to established forms of identity theft or fraud.

5. Simplified Onboarding. Modern identity solutions make onboarding simple, approachable and secure for customers, improving customer experience and improving industry competition.

Digital identity modernization is ultimately a win-win scenario. Financial institutions and customers benefit from existing technological advances that make the system simpler and more secure while expanding access and reach. Regulators benefit from better policy outcomes with the aid of more effective digital solutions.

We have the technological frameworks to get there. What we need is the will of regulators—both to update and amend rules while also supporting existing innovation programs and actively engaging with digital identity providers already operating in the financial services space.

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Article link: https://www.forbes.com/sites/forbestechcouncil/2022/10/19/why-its-time-for-a-regulatory-refresh-on-digital-identity/amp/

By ALEXANDRA KELLEYOCTOBER 18, 2022 11:40 AM ET

A report from the U.S. Chamber of Commerce underscored the environmental and consumer need for a digital government services modernization.

Work optimization and waste reduction are the two key factors behind the federal government’s need to update its digital services, with a new report from the Chamber of Commerce outlining the financial and operational benefits that come with modernization. 

Published by the lobbying group’s Technology Engagement Center, the report, titled “Government Digitization: Transforming Government to Better Serve Americans,” debuted on Monday. It captures the volume of government forms federal agencies rely on to provide government services.

These government processes include drivers’ license and passport applications and renewals, social security card applications, and health record access, among others.

“Increased government digitization doesn’t just mean saved time and money, it also means providing greater accountability and access to underserved communities when it comes to utilizing government services,” U.S. Chamber Technology Engagement Center Vice President Jordan Crenshaw said in prepared remarks. 

In total, there are 9,858 unique government forms used to access various services, and 106 billion such forms are processed annually, according to the report.

This culminates in about 10.5 billion hours American citizens spend filling out federal forms, which in turn use 2.25 million trees to create. Collecting and processing common government services using the current paper methods costs the federal government over $38.7 billion, based on statistics from June 2022.

The Department of Treasury stood out as having the highest number of unique forms at 1,838. Trailing the agency are the Department of Health and Human Services, the Department of Agriculture and the Department of Commerce.  

“Digitization will enable government agencies to cut costs, increase efficiency and reduce waste every day,” the report said. 

The Chamber encouraged Congress to conduct oversight examinations to see what paper processes can be digitized. A part of this process would ideally include lawmakers analyzing where to find funding to support IT modernization efforts. 

Researchers at the Chamber told Nextgovthat the digitization process could be supported by technologies like cloud computing, which enables better data streamlining and protection; blockchain softwares, which can track supply chain data; and artificial intelligence, which facilitates rapid data-based decision-making.

Experts within the Technology Engagement Center noted that this funding can potentially come from the Technology Modernization Fund, along with other avenues for similar modernization updates at the state level available via the American Rescue Plan.

Article link: https://www.nextgov.com/it-modernization/2022/10/paper-based-government-forms-cost-federal-agencies-378b/378566/

Cleveland Clinic is a Founding Partner in Quantum Innovation Hub

Cleveland Clinic has been selected as a founding partner and the leading healthcare system in a new initiative meant to spur collaboration and innovation in the quantum computing industry.

Based in Greater Washington D.C., the nonprofit development organization Connected DMV and a coalition of partners are developing the new Life Sciences and Healthcare Quantum Innovation Hub. Its purpose is to prepare the healthcare sector for the burgeoning quantum era and to align with key national and global efforts in life sciences and quantum technologies.

The U.S. Department of Commerce’s Economic Development Administration has awarded more than $600,000 to Connected DMV for development of the Hub. This will include formation of a collaborative of at least 25 organizations specializing in quantum technology and end-use applications.

Cleveland Clinic was invited to join the Quantum Innovation Hub because of its work to advance medical research through quantum computing. As the lead healthcare system in the coalition, Cleveland Clinic will help define quantum’s role in the future of healthcare and educate other health systems on the technology’s possibilities.

Quantum’s potential

Quantum computing is a radically different approach to information processing and data analysis. It is based on the principles of quantum physics, which describe how subatomic particles behave. By manipulating and measuring the actions of quantum particles, quantum computers can in theory solve problems too massive and complex for traditional computers, which are bound by the laws of classical physics. Quantum computers are still in an early phase of development, but they have the potential to advance medical research.

 “We believe quantum computing holds great promise for accelerating the pace of scientific discovery,” says Lara Jehi, MD, MHCDS, Cleveland Clinic’s Chief Research Information Officer. “As an academic medical center, research, innovation and education are integral parts of Cleveland Clinic’s mission. Quantum, AI [artificial intelligence] and other emerging technologies have the potential to revolutionize medicine. We look forward to working with partners across healthcare and life sciences to solve complex medical problems and change the course of diseases like cancer, heart conditions and neurodegenerative disorders.”

Collaborating with IBM

Last year, Cleveland Clinic announced a 10-year partnership with IBM to establish the Discovery Accelerator, a joint center focused on easing traditional bottlenecks in medical research through innovative technologies such as quantum computing, the hybrid cloud and artificial intelligence.

The partnership combines Cleveland Clinic’s medical expertise with the technology expertise of IBM, including the company’s leadership in quantum technology. IBM is installing the first private-sector on-premises Quantum System One computer in the United States on Cleveland Clinic’s main campus.

The Discovery Accelerator will allow Cleveland Clinic to contribute to Connected DMV’s hub by advancing the pace of discovery, using the IBM quantum computer in areas such as drug design, deciphering complex biological processes and developing personalized disease therapies.

Scaling up

The hub will be part of Connected DMV’s Potomac Quantum Innovation Center initiative, which aims to:

• Accelerate investment in, and research and development of, quantum computing.
• Develop an equitable and scalable talent pipeline to work in quantum computing.
• Increase collaboration among the public sector, academia, industry, community and investors to accelerate the value of quantum computing.

“Innovation is always iterative, and requires sustained collaboration between research, development and technology, and the industries that will benefit from the value generated,” says George Thomas, Chief Innovation Officer of Connected DMV and the leader of the Potomac Quantum Innovation Center initiative.

“Quantum has the potential to have a substantive impact on our society in the near future,” Thomas says. “The Life Sciences and Healthcare Quantum Innovation Hub will serve as the foundation for sustained focus and investment to accelerate and scale our path into the era of quantum.”

Article link: https://consultqd.clevelandclinic.org/how-were-bringing-the-power-of-quantum-computing-to-medical-research/?

February 16, 2022

Contributor: Robert Snow

Many government CIOs over- or underestimate the potential of robotic process automation (RPA). These strategies improve the chances of success.

In short:

• The hype around robotic process automation (RPA) can result in government CIOs understating its potential or overpromising its benefits.
• Common pitfalls include underestimating the total cost of ownership of RPA-based solutions and neglecting alternative and effective automation tools.
• To realize the true promise of RPA, adopt a structured approach to automation, establish a shared center of excellence to manage automation as a whole (not just as RPA) and pilot simple use cases with a clear return on investment to demonstrate value.

The popularity and use of robotic process automation (RPA) is expanding across governments around the world. Used more and more to perform mundane manual tasks, remove keying errors and reduce processing times, RPA ultimately frees up staff to focus on activities of higher value. 

Gartner expects that by 2024, 75% of governments will have at least three hyperautomation initiatives launched or underway, and RPA is a critical part of the modernization journey. You can help smooth the way by preemptively addressing potential blind spots in strategy. 

“Government business leaders tend to overhype or misunderstand the role of robotic process automation and end up underestimating the total cost of ownership (TCO) of RPA-based solutions,” says Dean Lacheca,Senior Director Analyst at Gartner. “There’s also a tendency to focus too narrowly on RPA rather than the wider topic of hyperautomation, which results in government communities of practice (COPs) and centers of excellence (COEs) not fully examining the automation tools and approaches needed for an effective hyperautomation strategy.”

Download now: Accelerate Digital for Future-Ready Government

Deploying RPA in digital government

Robotic process automation offers government organizations from all tiers and segments opportunities to streamline administration and optimize government processes. The ROI ranges from improved citizen experience to improved data quality — and the freeing up of the workforce to focus on more value-added activities.

Three ways to realize the true potential of RPA in government:

In the 2021 Gartner Digital Transformation Divergence Across Government Sectors Survey, 19% of government respondents said are already using RPA, with a further 33% indicating they intend to deploy RPA in the next two years. RPA’s popularity stems mostly from the operational efficiencies delivered, its ability to deliver benefits quickly and its use in automating legacy system processes.

To balance and quantify the “speed to value” benefits against total cost of ownership, improve your chances of success with the following three strategies.

1. Adopt a structured approach to automation that reviews processes and identifies a roadmap

The low cost of entry makes a business case for implementing RPA relatively obvious, but the total cost of ownership often becomes a challenge, especially for CIOs using RPA as a means to extend the life of legacy applications.

While RPA may look at first like a quick fix for an underlying problem, core legacy risks and technical debt remain. To better address this issue, take a structured approach, treating RPA as part of a larger suite of tools that augment or automate processes. Make clear whether RPA is being used as a productivity tool or an interim step on a longer modernization initiative — which also helps to manage stakeholders’ expectations. 

2. Establish a shared automation COE that includes RPA 

Government agencies increasingly use COPs and COEs to ensure the full realization of the benefits of automation tools such as RPA. As supported processes become increasingly complex, COEs and COPs help establish new controls that ensure the appropriate security, management and orchestration for automation solutions.

Automation solutions are not one-size-fits-all, and while there is always pressure to deliver better ROI, it’s never a good idea to simply scale the volume of scripts or bots as each one has its own maintenance and utilization costs. Even where an infrastructure is in place under an existing license, there may be limited skilled resources available to maximize ROI.

3. Pilot RPA on straightforward tasks with a clear ROI

Hype around RPA creates the false perception — especially among non-IT people — that it’s a simple way to deliver process efficiency targets. This distracts from the reality of how RPA is best used and what its benefits really are.

The proven benefits of government process automation and augmentation include increased efficiency, which helps to free the workforce to take on more productive work, fewer errors (and, as a result, increased data quality), and an improved citizen experience through faster processing time and reduced double handling.

A big part of your role in RPA is to demystify and position it correctly with government decision makers. Aim to identify specific RPA use cases that are not overly complex, possess structured data and have simple processing paths. 

Such use cases help you engender a better understanding of RPA tools and demonstrate some early benefits to the business. Also, these use cases will be an important part of a realistic change management process, and they can be an effective tool to gain support and manage expectations.

Take inspiration from RPA in action

With the growing popularity of RPA, examples abound of its tangible benefits to government organizations. A U.S. State of Federal RPA Report from November 2020 noted that preliminary results from the 23 programs assessed showed “the annualized hours saved by automations deployed increased from 285,651 to 848,336, a 195% increase.” The December 2021 report said the “federal RPA community has reduced over 1.4 million hours (and counting) of low-value work across the [U.S.] government to date.”

Regardless of mission or purpose, internal functions like finance,procurement, payroll and HR can all benefit from RPA’s ability to optimize tasks and processes. Scale will be the factor that influences the value of the benefits, but larger departments or organizations with significant procurement will reap most value.

Article link; https://www.gartner.com/en/articles/3-ways-for-government-cios-to-realize-the-true-potential-of-robotic-process-automation?

By LAUREN C. WILLIAMSJUNE 1, 2022

Pushing AI to the battlefield to help commanders make more informed decisions also means confronting the Defense Department’s worst enemy: the budget process.

The Defense Department has many predicaments to untangle when it comes to adopting emerging, and existing, technologies from workforce to acquisition. But when it comes to artificial intelligence, cultural and budget issues are the largest obstacles to widespread implementation, officials say.

“Implementation is the key to successful transformation” but is also “extraordinarily challenging” because it cuts across nearly everything the Defense Department does such as educating the workforce, acquisition,” Marine Corps Lt. Gen. Michael Groen, the outgoing director of the Defense Department’s Joint Artificial Intelligence Center, said during a keynote at the Atlantic Council event on May 26.

Groen continued saying that “cultural artifacts” from policy to budget execution accounted for 85% of the Defense Department’s broad implementation of artificial intelligence.

“Those cultural artifacts, whether that’s policy, whether that’s dealing with service budgets and service budget execution, getting authorization to operate on networks, ATO, networks and network policy, network security. The role of the department in all of those things, the relationship of the department with the services becomes a key conversation,” Groen said. 

Moving past those entrenched cultural dynamics means being willing to share capabilities, he said.

Margarita Konaev, a security and defense fellow at the Atlantic Council and Georgetown University’s Center for Security and Emerging Technology, described the Defense Department’s implementation of AI was like “working on a common goal but, unfortunately, on parallel tracks” and that improving alignment means investing in safe, reliable, secure, trusted AI that is battle-tested. 

“You will hear a lot about the urgency of implementing AI, magnified by the strategic competition with China, the changing nature of warfare, and the massive promise that AI has. That is all absolutely true and correct. But rushing towards the operational deployment of untested technologies that have not been effectively verified or assured…will end up being counterproductive,” Konaev said. 

Jaime Fitzgibbon, program manager for the Defense Innovation Unit’s AI and machine learning portfolio, said pushing AI to the battlefield to help commanders make more informed decisions also means confronting the Defense Department’s worst enemy: the budget process. 

“The capability is there…even DIU has pushed out prototypes that could help get that information that’s critical for decision-making up to the senior leaders, but…our budgetary cycles, you have to plan it five years ago, when the technology or even the data feed wasn’t around two years ago,” she said. 

Fitzgibbon said that conundrum is DOD’s “own worst enemy” and “everyone has a role in the problem and the solution,” which could include making funds available further down the command chain, perhaps even to the unit level, as some military needs are not communicated up to senior leaders. 

“And putting in an unfunded request that doesn’t get fulfilled for two years still doesn’t answer that capability challenge,” Fitzgibbon said.

Article link: https://www.nextgov.com/emerging-tech/2022/06/how-cultural-artifacts-impede-dods-ability-go-big-ai/367590/

By NICHOLAS PETERS The ConversationOCTOBER 13, 2022

Welcome to the world of quantum computing.

Unhackable communications devices, high-precision GPS and high-resolution medical imaging all have something in common. These technologies – some under development and some already on the market all rely on the non-intuitive quantum phenomenon of entanglement.

Two quantum particles, like pairs of atoms or photons, can become entangled. That means a property of one particle is linked to a property of the other, and a change to one particle instantly affects the other particle, regardless of how far apart they are. This correlation is a key resource in quantum information technologies.

For the most part, quantum entanglement is still a subject of physics research, but it’s also a component of commercially available technologies, and it plays a starring role in the emerging quantum information processing industry.

PIONEERS

The 2022 Nobel Prize in Physics recognized the profound legacy of Alain Aspect of France, John F. Clauser of the U.S. and Austrian Anton Zeilinger’s experimental work with quantum entanglement, which has personally touched me since the start of my graduate school career as a physicist. Anton Zeilinger was a mentor of my Ph.D. mentor, Paul Kwiat, which heavily influenced my dissertation on experimentally understanding decoherence in photonic entanglement.

Decoherence occurs when the environment interacts with a quantum object – in this case a photon – to knock it out of the quantum state of superposition. In superposition, a quantum object is isolated from the environment and exists in a strange blend of two opposite states at the same time, like a coin toss landing as both heads and tails. Superposition is necessary for two or more quantum objects to become entangled.

ENTANGLEMENT GOES THE DISTANCE

Quantum entanglement is a critical element of quantum information processing, and photonic entanglement of the type pioneered by the Nobel laureates is crucial for transmitting quantum information. Quantum entanglement can be used to build large-scale quantum communications networks.

On a path toward long-distance quantum networks, Jian-Wei Pan, one of Zeilinger’s former students, and colleagues demonstrated entanglement distribution to two locations separated by 764 miles (1,203 km) on Earth via satellite transmission. However, direct transmission rates of quantum information are limited due to loss, meaning too many photons get absorbed by matter in transit so not enough reach the destination.

Entanglement is critical for solving this roadblock, through the nascent technology of quantum repeaters. An important milestone for early quantum repeaters, called entanglement swapping, was demonstrated by Zeilinger and colleagues in 1998. Entanglement swapping links one each of two pairs of entangled photons, thereby entangling the two initially independent photons, which can be far apart from each other.

QUANTUM PROTECTION

Perhaps the most well known quantum communications application is Quantum Key Distribution (QKD), which allows someone to securely distribute encryption keys. If those keys are stored properly, they will be secure, even from future powerful, code-breaking quantum computers.

How quantum encryption keeps secrets safe.

While the first proposal for QKD did not explicitly require entanglement, an entanglement-based version was subsequently proposed. Shortly after this proposal came the first demonstration of the technique, through the air over a short distance on a table-top. The first demonstrations of entangement-based QKD were published by research groups led by Zeilinger, Kwiat and Nicolas Gisin were published in the same issue of Physical Review Letters in May 2000.

These entanglement-based distributed keys can be used to dramatically improve the security of communications. A first important demonstration along these lines was from the Zeilinger group, which conducted a bank wire transfer in Vienna, Austria, in 2004. In this case, the two halves of the QKD system were located at the headquarters of a large bank and the Vienna City Hall. The optical fibers that carried the photons were installed in the Vienna sewer system and spanned nine-tenths of a mile (1.45 km).

ENTANGLEMENT FOR SALE

Today, there are a handful of companies that have commercialized quantum key distribution technology, including my group’s collaborator Qubitekk, which focuses on an entanglement-based approach to QKD. With a more recent commercial Qubitekk system, my colleagues and I demonstrated secure smart grid communications in Chattanooga, Tennessee.

Quantum communications, computing and sensing technologies are of great interest to the military and intelligence communities. Quantum entanglement also promises to boost medical imaging through optical sensing and high-resolution radio frequency detection, which could also improve GPS positioning. There’s even a company gearing up to offer entanglement-as-a-service by providing customers with network access to entangled qubits for secure communications.

There are many other quantum applications that have been proposed and have yet to be invented that will be enabled by future entangled quantum networks. Quantum computers will perhaps have the most direct impact on society by enabling direct simulation of problems that do not scale well on conventional digital computers. In general, quantum computers produce complex entangled networks when they are operating. These computers could have huge impacts on society, ranging from reducing energy consumption to developing personally tailored medicine.

Finally, entangled quantum sensor networks promise the capability to measure theorized phenomena, such as dark matter, that cannot be seen with today’s conventional technology. The strangeness of quantum mechanics, elucidated through decades of fundamental experimental and theoretical work, has given rise to a new burgeoning global quantum industry.

Article link: https://www.nextgov.com/ideas/2022/10/nobel-winning-quantum-weirdness-undergirds-emerging-high-tech-industry-promising-better-ways-encrypting-communications-and-imaging-your-body/378244/

Nicholas Peters, Joint Faculty, University of Tennessee

This article is republished from The Conversation under a Creative Commons license. Read the original article.