How will smart leaders create smarter systems of the future?

It starts with the people who transform the culture of how we work.

When we improve the ways we communicate with one another and dissolve institutional silos, we take the critical steps needed towards transformation. As I’ve previously cited, I am currently exploring workforce innovation at the National Cancer Institute (NCI). With a FY2018 budget of $5.6 billion, NCI is composed of 30 brilliant yet separate divisions, offices, and centers, each with their own unique vision and portfolio of resources; 69 NCI-designated Cancer Centers; several dozen federally appointed committees and hundreds of subsequent working groups. Strengthening connections between these valuable yet disconnected assets is proving to be a process of many ups and downs. Reconstructing business practices is no easy lift and it can take years for the impact to become clear, as evidenced in my 15 years to help redesign Detroit’s economic fabric. Big change requires small steps over a long time horizon.

Taking my research and development at NCI as an immediate example, it is clear that we need fresh teams within a collaborative infrastructure to achieve lofty 21st-century public health goals, such as automating the ways that patients access preventative cancer interventions and therapeutic cancer treatments. Implementation of lifesaving advancements will lean on artificial intelligence (AI) to create new forms of communication to supplement the explosion of our nation’s oncology needs. Solutions, supported by AI, will help mitigate some of the risks we face. These risks include shortage of oncologists over the next decade amidst soaring cancer demands, as noted in the American Society of Clinical Oncologist’s report on The State of Cancer in America. These facts underscore the urgency of optimizing federal agency data supply chains to help all of us make better decisions, faster. If our federal workforce remains disjointed and entrenched in static silos, we will not foster clear pictures of our data and we will continue to struggle to meet the health needs of our nation.

Relationships drive the future of work.

1. Workforce: keep our people at the center.

“Society already has plenty of experience dealing with problematic black boxes; the most common are called human beings.”

We must establish a more effective, efficient organizational structure. What will leaders need to support more direct interactions between disjointed data and help facilitate exchange between diverse teams (i.e. innovation) that at the core of smarter systems? This necessity, critical to AI, manifests across most of the federal spaces I interact with, including my work in supporting the White House Machine Learning and Artificial Intelligence R&D Subcommittee. When we improve the way our real-life leaders work together, we enable a future of easier and automated searching across our diverse and enriched data networks. Only when we begin to resolve some of our people problems, we can then invite everyday browsers to crawl a network of our research data (think of the Internet), or support industry leaders who have already been building tools to improve search between a variety of sources, like Google’s Knowledge Graph of real-world connections. AI can do the work of improving our networks once we have modeled good network behavior between ourselves as people, first.

2. Workplace: we accelerate the impact and outcomes of public health solutions by making better places for us to work together, better.

Exchange of information leads to innovation. Collaborative workforce engagement processes I led at The Work Department, the change management and social innovation consulting firm I founded in 2008 and led until 2017 to serve as a White House Presidential Innovation Fellow.

US Food and Drug Administration (FDA) Commissioner Scott Gottlieb, M.D. makes an astute point with regards to data and shared ways of working to produce data in one of his recent blog posts, A Cross-Cutting Data Enterprise for Real World Evidence. In response to reimagining the business practices that keep data (and the people who create the data) segregated, he acknowledges that “different groups may collect the same information in different ways” and yet one key in the effort to harmonize and optimize for better interoperability is bringing stakeholders together in shared spaces to work through a collaborative process. He notes how it is critical for teams of diverse people to agree “upon definitions that allow different groups to meaningfully share their data.”

I co-led and co-authored NCI’s Office of Workforce Planning and Development “Design Thinking 101” senior leadership course. This photo captures NCI’s senior leaders working through an inclusive decision-making process and exchanging critical information with one another in a more rapid method, most for the first time

3. Workflow: we don’t harmonize efforts as well and as frequently as we could.

As noted in a recent article in the Wall Street Journal on the work it takes to train AI like IBM Watson, “recommending personal medical treatment is a taller order. The software needs to be trained with data on what has worked in the past…that information is often recorded in different formats and owned by different (entities) and isn’t always complete or consistent.” It may be too late to surface every last byte from our legacy data treasure troves, however we can take more cues from other industries, like forms of “just in time” networks that prevail over the vestiges of America’s linear assembly models, postindustrial wreckage I know too well from my hometown Detroit.

The power of taking small steps start to generate big change begins with the freedom to make more decisions quickly.

Our siloed, federal workforce cannot compete in the modern global economy because silos aren’t meant to be beacons for people in a modern organization intended to serve 325.7 million people (US population). Silos are meant to store grains on a farm. What can we learn from the way information is successfully share in more complex systems, such as our brain, to inform innovation in our organizational workforce structure?
A communication ”traffic map of of the brain’s top white-matter pathways” provides inspiration on how smarter systems communicate. Credit: USC Institute for Neuroimaging and Informatics, sourced from Scientific American article on neural highway maps.

We must go deeper to rewire our organizational learning and memory systems to dissolve the barriers — the physical and intangible silos — that keep us from using smarter systems to tackle our ­nation’s most complex 21st-century problems. Reconstructing organizational architecture to be more compatible with deep learning architecture challenges us to reconsider what we imagined our individual identities to be. Redefining our culture — less collective focus on the technical “what” and more energy about redefining “how” will allow us to work together, better. It all starts with people and the culture of how we work. As the White House’s Matt Lira stated, when unveiling the modernization priorities of the Office of American Innovation,

“The challenge is not to deliver a shiny object but to build an organizational structure, continuously updating.”

Garry Kasparov, author of Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins, also notes that “education and retraining a workforce to adapt to change is far more effective than trying to preserve that workforce in some sort of…bubble. But that takes planning and sacrifice, words more associated with a game of chess than with today’s leaders.” It is we, the people, who can lead the way by showing others how to let go of our old barriers. We are responsible for the decisions about how we cultivate our future workforce, workplaces, and workflow to improve the delivery of our services to our citizen customers. We must dissolve the silos and continuously invest in a healthier leadership ecosystem to work together better as a smarter system of humans, first. AI can then amplify from the foundation we build as people.

Who else is going to step up and join those of us shaping the future of government?



Futurist, strategist, facilitator. Smart systems = healthier communities. Collaboration is the future of work.

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Nina Bianchi

Futurist, strategist, facilitator. Smart systems = healthier communities. Collaboration is the future of work.