Paul Duan

Paul Duan is demonstrating that the greatest limitation of today’s data sciences is not the technology itself, but rather the processes and agendas within institutions that can limit the technology’s potential. Thus, he’s set out to partner with existing governments while mobilizing a highly-skilled team of software developers, computer programmers and data science engineers to co-design parallel digital social services tools to be led and owned by the citizen sector.

Paul Duan envisions a world in which large social issues are being effectively addressed through efficient and effective citizen-led social services. Paul attempts to achieve this by utilizing data sciences and data engineering technology to play a critical role in solving the most pressing and universal social problems. He sees data engineering sciences as an opportunity to move beyond the simple provision of information, into a paradigm that creates true systems changing impact for all people. In order to do this, Paul recognizes that issues of data science for social good are not limited by the technologies available, but rather by the outdated institutionalized decision-making processes and ownership mindsets which were never designed to maximize the capabilities of data science in the first place. To curb this conflict Paul is applying his superior skills in data science and engineering and leveraging his influence within the data science community, along with open source technology, and is building new parallel social service systems. These systems are co-designed with existing institutions, yet 100% owned and evolved by the citizen sector it is designed to serve. In doing so, Paul believes these new parallel social services can be immune to administrative structures that are too often subject to political agendas, bureaucratic processes and even corruption.

In partnering with existing governments and institutions, Paul is able to embed new behaviors and mindsets that dismantle and disrupt outdated, preconceived roles and responsibilities, shifting perceived ownership and leadership from the government sector to the citizen sector. He is able to challenge administrators to change their self-view as the direct service provider and regulator. He then actively advocates against the idea that the citizen sector should merely be the passive adopter of a highly-generalized and imperfect social service that is vulnerable to regime changes and redundant processes. This all comes together as Paul co-develops a parallel, independent, virtual social service platform that places the ownership and evolution of the system directly into the hands of its beneficiaries.

Paul believes that by equipping any and all people with the ability to utilize current data for the good, the technology of data science and engineering cannot out run the systems set up to utilize them. So, to prove this, Paul is starting first with a notoriously bureaucratic system: "Pôle Emploi" and he is already demonstrating the transformative power of socially conscious data utilization through citizen owned services.

The average estimated time a person living in France can expect to be unemployed is 18 months. With a consistent rate of just around 10% in the last decade, France has one of the highest unemployment rates among developed countries in Western Europe. A compounding factor in the unemployment problem is a complex administrative system. While France does have a national social service – Pôle Emploi – tasked with supporting citizens to find jobs, the leadership of Pôle Emploi and the government mandated funding used to support it is subject to the policies and priorities of the government currently in place. With a national French election scheduled for spring 2017, a service like Pôle Emploi can become vulnerable to a regime change. In addition, the challenges of bureaucracy, inefficient processes and vulnerabilities to regime change can complicate the system’s ability to deliver critical social services to citizens in need.

Unfortunately, the paradox of a social service system designed to support its citizens, being vulnerable to the administration which runs it, is certainly not limited to France. Take for example the Affordable Care Act, signed into law in the United States in 2010. More commonly known as “Obamacare”, the law was a government mandated social service designed to bring health insurances to millions of un-insured U.S citizens unable to obtain affordable health coverage. Despite bringing an estimated 15 million citizens the ability to obtain health care coverage between 2010 and 2016, and reducing the rate of uninsured citizens from 18% to just over 13%, the Act still failed to reach millions of citizens rendered ineligible for coverage. In addition, the Act became a major point of political contention during the 2016 United States election and to-date remains vulnerable of being repealed, due to an administration change.

The reality is that globally, governments build and construct social services to address the most critical needs of their citizen base. It is without question that administrations – regardless of their political beliefs and views – universally see the need to address and improve large social issues such has unemployment, healthcare and education among their populations. They construct, fund and foster social services for their citizens. The challenge arises as these services are often constructed without the leadership or ownership of the citizens and beneficiaries it is designed to support. Instead created by their elected officials who are not only limited to designing highly generalized solutions which can fall short of reaching those most in need, but who are also vulnerable to political processes, bureaucracies and controls – and in extreme cases, corruption. As leadership changes, so to can the processes, bureaucracies and controls. This leads to inefficient and redundant execution of the service, as new political regimes prioritize their views over the primary need to support its citizen base.

Despite the best of intensions, social service systems are severely limited by the administrative bodies that create, fund and run them. New local and national leaderships make services vulnerable to change based on the political views of the new administration rather than to change based on the primary need of the beneficiaries it’s meant to serve. In order to ensure that social services are immune from these challenges, they must be led and owned by the citizen base it is designed to support.

Co-founded by Paul Duan in 2014, Bayes Impact is an international NGO with offices in the United States and France. Bayes Impact is developing a methodology for the creation of citizen-led and citizen - owned social services that is financed by government institutions.

A key element in Paul’s plan to create citizen-led services is to tackle what he calls the “giants” of societal issues. Issues such as healthcare, social justice and unemployment which are universally acknowledged as priorities, yet impossible to solve through generalized programs which if created, often fail to help those most vulnerable and in need. However, addressing these “giants” - as Paul calls them – provides Bayes Impact with some key advantages. For instance, governments often collect massive amounts of data on such social issues, making them the best opportunities to showcase the ability of data science engineering to re-organize a reservoir of scattered and incoherent information into highly tailored and useful information. Paul believes that access and navigation of this data is best done through partnership with the governments that collect it, rather than independent of them. By partnering with government agencies to access the data and co-design a service using that data, Paul argues that he is leveraging the government’s ability to collect highly detailed information from its citizens that would be unmatched through independent or commercial avenues. Bayes Impact has already piloted partnerships with the Sutter Health system (one of the largest hospital networks in California), the U.S Department of Veteran Affairs Services and France’s national employment agency – Pole Emploi.

An additional advantage to addressing the “giants” of social issues is that it allows for Bayes Impact to position itself as an advocate of digital social services among the citizen sector and to gain significant attention within the media. Paul believes this can stimulate “grassroots” movements at the local and national level around the concept of citizen-led social services while forcing government legislators, policy makers and influencers to take notice and meet the demands of the public. To date, Paul and his work with Bayes Impact has been featured by: Forbes.com - 30 under 30 social entrepreneurs for 2016, The Wall Street Journal, and Le Monde (one of the top national media outlets in France). With this type of media exposure Paul Duan has been able to share his vision of citizen-led services directly with the President of France - François Hollande through special invitation, to discuss unemployment in France. These opportunities are not just an attempt at media coverage, but an opportunity to grow the Bayes impact vision while leveraging the power of the media to influence political and administrative players to become more sensitized to a shifting role in how social services can and should be provided.

Just as important as being able to influence governments, is the strategic opportunity to co-design a social service product with current governments and institutions. Paul argues that working alongside government officials helps him and his team to better understand and navigate the institutional challenges and barriers that might bar a “great” product from being successfully implemented or launched to the citizen base it is meant to support. Paul identifies that this type of intimacy of a project based team, allows him and his Bayes colleagues to uncover the landscape of political dynamics and institutional relationships not always available through more public channels. This also helps to build a foundation of trust and influence between his team and their institutional counterparts. Such access to the inner-workings of these types of bureaucracies is not available when if his team is simply “commissioned” to deliver a product. These experiences have evolved the Bayes Impact partnership contract to include two critical and currently non-negotiable clauses. The first, is that all partnerships must be fully funded and finite, on a project by project basis. This is different from more traditional funding models, where funding is often distributed and renewed on an annual basis, over renewable contracts. This, Paul believes leaves valuable services vulnerable to administration changes and “power-plays”. It is important that a full commitment up front to “finish what is started” is understood by all partners. The second clause, is that sole ownership and all proprietary information from the final product is owned exclusively by Bayes Impact - which the NGO then promptly open sources and distributes freely upon completion. Through open sourcing all algorithms, formulas and the entire project methodology, Paul affirms that the product and the service becomes the ownership of everyone, nothing is proprietary, and the product can never be “pulled back” by a leadership change.

Once Paul has these strategic partnerships and contracts with agencies in place, Bayes Impact works to co-design and co-develop a product (often an online platform tied to a specialized algorithm) which best utilizes the data available. The key is to be able to produce a nuanced and tailored solution for any person that uses the product. For example, through their partnership with the Sutter Health system, Bayes Impact designed a program that predicted the re-admission risk rates of individual patient’s in order to improve Sutter’s care management procedures. The partnership with the U.S Department of Veteran Affairs, enabled Bayes Impact to co-design algorithms that helped the office identify mental health and unemployment issues for more than 21 million US veterans. Yet, Bayes’ biggest accomplishment to date is through its partnership with the government of France to create an unemployment service tool which not only provides a personalized guide for citizens through their employment journey, but also adapts its service provision through a simplified form of artificial intelligence (AI) to improve its recommendations and support to subsequent users based on the outcomes and success rates of previous users. This unprecedented partnership with the French government, gives Bayes Impact simultaneous access to multiple employment administrations and branches within France which are currently siloed. Communication and leadership between the branches is fragmented, which leads to frustration from citizens attempting to navigate employment services in France. The platform, which launched in November 2016, has already had more than 85,000 citizens registered, with positive qualitative feedback already being collected by restraints that have been able to find a job, Yet, Paul is much more excited about creating a system that can be continuously improved by anyone and everyone who uses it.

Looking to the future, Bayes Impact is launching a campaign to get one million users in France to benefit from the new employment platform, and is partnering with the Abul Latif Jameel Poverty Action Lab (J-PAL) to conduct an independent review of the impact of a citizen-led service, with results expected to be reported in February 2018. Already built, the platform is the first to fall under Bayes new partnership structure which means all algorithms are open sourced and the platform is built to resist any changes in national leadership, which is timely given the arrival of French elections in May 2017. Paul sees France a “key” leveraging country in stimulating citizen-led services across Europe. His agreement with France has already led to talks with key influencers in Belgium, Switzerland and Luxemburg. Paul hope to replicate and adapt the success to economic and employment issues there, ultimately positioning Bayes Impact as the UN of data sciences and citizen led/owned services.

Paul Duan is the child of Chinese immigrant parents who found themselves as part of the student lead protests in Tiananmen Square, Beijing in 1989. After fleeing from China to France to start a new life, Paul’s parents raised him to strive for excellence in his academic space, while instilling the values of shared responsibility and standing up for what is right.

While growing up, Paul understood the struggles and sacrifices that his parents made to give him a better life and found himself striving for academic excellence in order to make them proud. His academic strive coupled with a natural intellectual ability led Paul to the “top” of his class in many areas of his academic life. However at a young age, Paul found that the happiness that these academic accomplishments brought him were short lived and at times superficial. An introverted and shy young kid among his peers, Paul found more joy in helping others and looked for opportunities to use his intellectual skills in a way that shared his knowledge and made more meaningful connections. This desire led to Paul designing a free online platform at the age of 13, which taught teens how to design code on the internet. Paul also recalls being intrigued and fascinated by people with diverse backgrounds and circumstances. He would often seek out random conversations with new people in his early teenage years, in order to better understand the circumstances of people in his community, for example playing chess with senior citizens in the parks of Paris.

In his early 20’s, Paul found and opportunity to travel to the United States to continue his formal education, but was initially hindered by a school policy that would have prevented him from obtaining the necessary financial support to make the trip. Instead of accepting the policy, Paul maneuvered around the system and convinced his school that its primary duty was to provide him with this advanced education opportunity, which allowed Paul to attend Berkley University in California. While at Berkley, Paul co-led and designed an IT conference that attacked some of the biggest representatives in data science and technology including Google and Eventbrite. Paul credits his time at Berkley for inspiring him to see how his love of coding and data science could be combined with social justice issues and entrepreneurship. Paul was headhunted by Pay Pal before becoming a founding team member of Eventbrite where he excelled in his position securing an impressive salary before the age of 23. However, again despite his achievements, Paul found his happiness due to his success short lived. Remembering that as a teen, his joy came in sharing his abilities to help others, Paul left Eventbrite to create an NGO - Bayes Impact - under the compelling belief that data science can and should be used for social good.