‘Data collaboratives’ are key to using data for good
TM Forum Distinguished Fellow Jenny Huang reveals how her involvement in the 2019 Taiwan Presidential Hackathon highlighted the need for ICT companies to embrace ‘data collaboratives’ that go beyond the public-private partnership model to help companies securely exchange data for the greater good.
‘Data collaboratives’ are key to using data for good
In this first article of a two-part series, Jenny Huang, Founder of the International Free and Open Source Solutions Foundation (iFOSSF) and a TM Forum Distinguished Fellow, reveals how her involvement in the 2019 Taiwan Presidential Hackathon highlighted the need for ICT companies to embrace ‘data collaboratives’ that go beyond the public-private partnership model to help companies securely exchange data for the greater good. This approach will be key as data grows and becomes increasingly decentralized – and too heavy to move. It all started with a casual brunch conversation with one of the organizing committee members of the 2019 Taiwan Presidential Hackathon when I was in Taiwan visiting my parents early this year. We talked about the major shifts in the ICT sector towards software-defined and autonomous operations and how these advancements could profoundly impact all sectors by creating a new layer of utility infrastructure that is more intelligent, flexible and economical for all businesses and governments to provide their goods and services. Soon after this conversation, I was invited as a judge to help recruit, evaluate and coach the teams participating in the hackathon, which got its start in 2018 when Taiwan President Tsai Ing-wen organized the country’s first Presidential Hackathon as a three-month-long collaborative effort among Taiwanese business, government and civic coders to develop innovative apps for public benefit. The goal was to facilitate exchanges among data owners, data scientists and field experts to assemble the wisdom of crowds across government, industry, private and public sectors.
Ultimately, the government of Taiwan is striving to accelerate the optimization and improve effectiveness of public services. This year it opened the hackathon event to international teams with the aim of further expanding Taiwan’s digital footprint, setting itself as a role model in open government and open data, at least in the Asia region.
We were excited to receive 23 submissions from 15 countries, six of which were invited to Taiwan for the final competition. While the hackathon itself was exciting, what happened in the lead up to the event could have much greater impact.
OPAL’s shining light
Recently, I’ve been learning about ‘data collaboratives’, which are defined as: “a new form of collaboration, beyond the public-private partnership model, in which participants from different sectors – in particular companies – exchange their data to create public value.” This approach is a primary focus for the Presidential Hackathon. It’s also a basic tenet of the Open Algorithms for Better Decisions Project, better known as the OPAL Project, a non-profit alliance consisting of partners from the MIT Media Lab, Imperial College London, Orange, the World Economic Forum and Data-Pop Alliance which aims to unlock the potential of private sector data for public good by “sending the code to the data” in a safe, participatory and sustainable manner. (Editor’s note: for more about sending code to data, see this article.) The goal of the hackathons, especially with the inclusion of international teams this year, is for the Taiwanese government to create a platform for effective exchange of ideas for its long-term strategic planning and to identify potential partners. I started to think about possible synergy with the OPAL Project and decided to invite its co-founder, Nicolas De Cordes, who is also VP of Marketing Anticipation at Orange Group, to come to Taiwan to discuss how to leverage the attention and momentum of the hackathon as part of our initial stakeholder discussions. These talks were designed to: Watch the full interview with Joi Ito:
- Introduce the OPAL project, especially to make people aware of the large number of existing use cases available to illustrate how telecom data can be re-purposed to provide insights on infrastructure development. For example, the data could be used to help governments understand where to add schools or hospitals, or it could be used to challenge the accuracy of existing statistical data, such as unintentionally biased data sampling.
- Explore how privacy, AI and business models can be used to encourage private sector participation and collaboration to make open data work without unanticipated consequences. A great example of why these conversations are needed is reflected in this interview from The Atlantic with Joi Ito, Director of MIT Media Lab. He says: “Today we use technology such as AI to amplify human biases; instead we should use technology to illuminate biases… We need to use data to validate that the bias exists so that we can influence at the policy/decision-maker level based on the evidence. We can then use ML/AI to improve the situation based on an improved hypothesis.”
Setting the stage
During our intense, two-day open data conversations, we met with many diverse stakeholders and experts to discuss the future of data and its applications and implications for policies. First, we met with members of the Executive Yuan Board of Science and Technologies (BOST). (The Executive Yuan is commonly referred to as “The Cabinet”, which is the chief policymaking organization of the Taiwan government, and BOST reviews and coordinates the overall development of national science and technology policy.) In this session, representatives from the OPAL Project and BOST shared case studies using telecom data to inform policy development. One interesting example came from Chunghwa Telecom, which has been using real-time population data for evidence-based policy planning.
We also debated some interesting questions, such as whether anonymized data can really shield individual identity when evidence shows that just four spatio-temporal points of mobile movement data are enough to uniquely identify 95% of individuals (spatio-temporal points are a random collection of points, where each represents the time and location of a specific event). On the second day, we held an industry-focused discussion hosted by TWNIC (Taiwan Network Information Center, the organization in charge of domain name registration and IP address allocation in Taiwan) and DTA.taipei (Taiwan’s Digital Transformation Association, which promotes and facilitates digital transformation and digital economy. The meeting included representatives from hosting organizations, telecom providers, vendors, management consulting firms, etc., and we discussed the role of telecom in digital transformation, the impact of 5G and regulation. I had the honor of presenting on the topic of “Telco as Digital Transformation Enabler” based on my experiences in AT&T and engagement with member companies within TM Forum. Finally, we visited the Academia Sinica, the preeminent academic institution of Taiwan, which was founded in China in 1928 to promote and undertake scholarly research in the sciences and humanities. In this session the goal was to identify potential synergies and joint research projects where OPAL may be able to leverage resources from this elite research group and vice versa. These meetings showed that there are many open ears and open hands willing to collaborate, and all participants are looking forward to developing a concrete work plan to embrace data collaboratives in Taiwan and internationally. In the next blog in this series, Jenny will team up with TM Forum Chief Architect Dave Milham to offer ideas about how TM Forum members can engage with initiatives like the OPAL Project and Civil IOT Taiwan, a data service platform that aims to provide high-quality public IoT-based information to enable citizen engagement and co-creation of innovative community-based solutions. Stay tuned.